Nicholas Charles Coops
Relevant Degree Programs
Complete these steps before you reach out to a faculty member!
- Familiarize yourself with program requirements. You want to learn as much as possible from the information available to you before you reach out to a faculty member. Be sure to visit the graduate degree program listing and program-specific websites.
- Check whether the program requires you to seek commitment from a supervisor prior to submitting an application. For some programs this is an essential step while others match successful applicants with faculty members within the first year of study. This is either indicated in the program profile under "Requirements" or on the program website.
- Identify specific faculty members who are conducting research in your specific area of interest.
- Establish that your research interests align with the faculty member’s research interests.
- Read up on the faculty members in the program and the research being conducted in the department.
- Familiarize yourself with their work, read their recent publications and past theses/dissertations that they supervised. Be certain that their research is indeed what you are hoping to study.
- Compose an error-free and grammatically correct email addressed to your specifically targeted faculty member, and remember to use their correct titles.
- Do not send non-specific, mass emails to everyone in the department hoping for a match.
- Address the faculty members by name. Your contact should be genuine rather than generic.
- Include a brief outline of your academic background, why you are interested in working with the faculty member, and what experience you could bring to the department. The supervision enquiry form guides you with targeted questions. Ensure to craft compelling answers to these questions.
- Highlight your achievements and why you are a top student. Faculty members receive dozens of requests from prospective students and you may have less than 30 seconds to peek someone’s interest.
- Demonstrate that you are familiar with their research:
- Convey the specific ways you are a good fit for the program.
- Convey the specific ways the program/lab/faculty member is a good fit for the research you are interested in/already conducting.
- Be enthusiastic, but don’t overdo it.
G+PS regularly provides virtual sessions that focus on admission requirements and procedures and tips how to improve your application.
Application of remote sensing technologies to forest productivity and conservation issues
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - Mar 2019)
Understanding pre-industrial fire patterns, in particular unburned or partially burned vegetation remnants, has become a research and forest management priority in Canada and beyond. To achieve these goals, it is crucial to better understand the variability of spatial fire patterns, as well as the relative importance of the environmental controls at broad scales. Open-source and freely available Landsat data has great potential to capture fire patterns in a repeatable and automated way across large and remote areas. However, critical challenges associated to (1) the reliance on very expensive field plot data for calibration/validation of the mortality maps; and (2) the lack of consistent spatial language and methods to analyze the spatial patterns, hindered the applicability of these methods across large areas and the comparability of the results obtained. The objective of this dissertation is to develop, test and demonstrate the value of a novel framework to help improve our understanding of historical spatial fire patterns across the Canadian boreal forest. The research advances our understanding of the variability and causality of spatial fire patterns across large remote boreal regions addressing both scientific and management communities. Major contributions from this research include:• Re-imagining how to capture and describe spatial fire patterns across large and remote areas of the boreal forest through an innovative and cost-effective framework that combines Landsat satellite data, polygons of mortality from aerial photo-interpretation and a consistent spatial language and metrics to capture key fire characteristics. • A demonstration of this new framework and how it can be extrapolated to other landscapes beyond the original formulation area. In particular, this research produced a fire pattern database comprising 507 new fires and 2.5 Mha – far in excess of any other study to date for the same area.• An examination of how the data generated could be used in combination with new tools and methods to reveal patterns of fire mortality not previously possible including (1) characterization and assessment of differences in fire pattern signatures between pre-defined ecological zonations, and (2) analysis of the interactions between spatial fire patterns and main biotic and abiotic environmental controls.
Cities strive for economic strength while recognize the necessity of being environmentally sustainable. The balance between economic development and the environment has been challenging particularly for cities in the pan Pacific region, which is seeing some of the most rapid urban growth rates. Remotely sensed satellite images offer much larger and more consistent spatial and temporal coverages than conventional census data therefore are increasingly being utilized for regional and global urban studies. Two key remote sensing datasets, namely urban vegetation cover derived from Landsat time series, and brightness generated from NOAA’s nighttime lights datasets to represent urban development were the focus of this dissertation. I first extracted annual urban vegetation characteristics using spectral indices (e.g. EVI) as well as a spectral mixture analysis from 1984 to 2012. Nighttime lights brightness was used to assess urban expansion and its relationship with census-derived variables. Lastly, I examined the relationships between urban development and the environment using Environment Kuznets Curve (EKC) theory as a lens, addressing how urban vegetation responds to urban nighttime brightness in 25 cities across the pan Pacific region. I identified inter- and intra-city patterns of vegetation and brightness changes that were strongly related to social and economic contexts. Spectral indices demonstrated opposing trends between urban vegetation and built-up area both spatially and temporally. Spectral mixture analysis successfully extracted the urban vegetation fraction at a sub-pixel level, setting a robust base for cross-city comparisons. I found that urban vegetation changed linearly both positively and negatively with urban brightness, particularly in higher income cities in North America. Pixels with statistically strong quadratic relationships between vegetation and brightness were less prevalent but more spatially clustered in comparison to those that expressed a linear relationship. Overall, there are three key contribution of this dissertation. Firstly, the integration of gap-free satellite images and innovative processing techniques unlocked new ways of informing urban environmental and socio-economic dynamics. Secondly, a classic econometric model (i.e. Granger causality test) was used to examine the casual relationship between census and remote sensing nighttime lights data. Lastly, a pixel-based model fitting was use to confirm EKC at a sub-city scale.
In western Canada, the effects of warming and increasing human activity may alter the structure, composition, and function of forests, producing quantitatively and qualitatively different understory light conditions. While difficult to measure directly, process-based models may facilitate inference of historical forest states. Yet, existing models are limited in the dynamics they represent. A promising new approach in hybrid modeling, first demonstrated here, is the fusion of machine learning and process-based models to simulate pattern-based processes. The objective of this dissertation was to simulate the effects of past-century climate and fire conditions on understory global solar irradiation trajectories across a 25.2 million ha landscape in Alberta, Canada. The LANDIS-II forest landscape model was applied to simulate past-century changes to competition, fire, and regeneration. Simulated tree species and age maps were classified into landcover types. A regression model of canopy light transmission as a function of landcover and site index showed good fit with field observations (R2 = 0.94) and was applied to a classification of LANDIS-II outputs. Canopy light transmission was multiplied by mean annual bare-earth global solar irradiation to produce understory light maps. Empirical and semi- mechanistic fire models were also applied. A variant of stochastic gradient descent was applied for parameter optimization, improving fire model performance (R² = 0.96; ΔR²= +0.14). Simulations showed a mild decline in forested area across the 1923-2012 period, attributable to a velocity of warming three times faster than migration. Migration was primarily controlled by fire and secondarily by regeneration. Simulated understory light levels declined across the period due to reduced mortality rates, preceding a likely long-term increase in light attributable to reduced regeneration rates. The key innovations of this work are as follows: characterization of human-dominated fire regimes in western Alberta (Chapter 4); advancement of the TACA-GEM regeneration model (Chapter 5); development of an algorithm for fire model parameter optimization (Chapter 6); development of new LiDAR models of canopy light transmission (Chapter 7); demonstration of a new hybrid modeling approach to simulating pattern-based processes, applied to understory light (Chapter 8); demonstration of long-term climatic regulation of understory solar irradiation through forest regeneration (Chapter 8).
The Arctic is currently experiencing some of the most dramatic warming effects globally due to climate change. Barren ground caribou (Rangifer tarandus groenlandicus) herds in Canada’s north are particularly susceptible to climate change as they occupy Arctic and sub-Arctic environments and as grazers respond directly to changing vegetation conditions.Examining the associations between barren ground caribou and their environment across their entire range presents specific and substantial challenges. Large herd ranges make in-situ habitat monitoring studies difficult and expensive. Additionally, the environments barren ground caribou inhabit are extremely remote and not spatially consistent between years. As such, new techniques are required that address the large scale, remote, and temporally variable nature of these animals. Within this PhD Dissertation, I integrate newly developed remotely sensed environmental data sets with multiple caribou data sets to explore how changing environmental conditions are affecting barren-ground caribou movement and habitat use in Canada’s north. Barren ground caribou’s effects on summer range productivity were assessed to explore top down controls on vegetation productivity. Based on my results, I argue that while there is some association between barren ground caribou density and future summer range vegetation productivity, it is unlikely that range degradation is a major cause of herd declines in the herds examined here. Habitat conditions (vegetation productivity, lichen mat condition, and fire disturbance) were documented across herd ranges to assess how barren ground caribou habitat is changing through time. These habitat conditions were then linked to movement metrics derived from barren ground caribou telemetry data to assess how changing habitat conditions are affecting caribou movement patterns. I found widespread, rapid changes in barren ground caribou habitat in line with predicted and documented climate change effects in the Arctic, and I detected significant alterations in movement metrics associated with these changes in habitat.In all cases, remotely sensed environmental indicators were useful for describing aspects of barren ground caribou habitat. I was able to link habitat conditions to barren ground caribou at both the individual and herd levels and described novel linkages between barren ground caribou and their environment.
Over the past decade, changes in climate have been sufficient to affect both the composition and function of forest ecosystems. The extent that projected climate change will continue to impact tree species vulnerabilities remains unclear and has been mainly assessed based on simple relationships between the distribution of mature trees and climate variables. The objective of this thesis was to assess the effects of regional climate and soil variations on the current and future distribution of 20 major conifer tree species across western North America and determine the impacts of changing environmental variables on tree species vulnerabilities. The spatial variation in properties of soil water availability and soil fertility was combined in the process-based model 3-PG to provide detailed projections of species shifts in response to changes in environmental conditions. The relative importance of limitations imposed on photosynthesis by suboptimal temperatures, frost, solar radiation, soil water and vapor pressure deficits was ranked in a decision tree analysis based on tree species occurrences across the region. The baseline distributions of the tree species were predicted with an average accuracy of 84% (κ = 0.79), based on their recorded presence and absence on 43,404 field survey plots. Inclusion of soil properties was crucial to improving the overall accuracy of the species distribution models and 75% of the species directly responded to changes in the soil water input. At the ecoregion level, this thesis identified the highest vulnerability of the 20 tree species analyzed to occur within the North American Deserts, particularly in the Thompson-Okanagan Plateau of British Columbia (BC). Comparison of areas suitable for tree species range expansion with a large empirical dataset on tree seedling occurrences in BC agreed on average 79%, serving as indicators of early species responses to climate shifts in the province. Outcomes of this thesis demonstrate species-specific responses to current and future climatic variations and can contribute to informing forest management for climate change adaptation.
Anthropogenic disturbance regimes are anticipated to overwhelm Earth’s ecosystems during the Anthropocene. Boreal forests are particularly at risk of significant transition due to human appropriation of renewable and non-renewable resources. Forestry and energy development in the boreal forest have three primary ecological consequences: suppression of historical disturbance regimes such as fire; emergence of novel ecosystems; and the eradication of ecological memory, which maintains ecological integrity. The objective of this dissertation is to improve our understanding of the pattern characteristics of anthropogenic disturbance regimes in order to mitigate the negative, unintended outcomes of managed boreal forests.Anthropogenic disturbance from forest harvesting and energy development was mapped for industrialized landscapes of Alberta, Canada between 1949 and 2012. A comparative analysis using spatial models of unsuppressed fires sampled across Alberta and Saskatchewan and aerially-interpreted forest inventory data revealed that the anthropogenic disturbance patterns were beyond the historical range-of-variability in terms of disturbed area, largest patch size, and undisturbed forest remnants. When the spatial data were segmented based on a recent period of intensive energy development, it was determined that energy development in Alberta was a major driver of cumulative anthropogenic disturbance patterns. Levels of undisturbed forest remnants within anthropogenic disturbances declined between 18-34% and edge density increased between 15-175% following energy development.Landscape-level patterns of forest cover changes were assessed using a time series of satellite imagery between 1985 and 2010. Forest disturbance was classified as resource extraction or fire in the Foothills of Alberta with 94% overall accuracy. The rate of resource extraction exceeded fire, accounting for 86% of annual forest disturbance, indicating that fire was suppressed in the landscape. A time series pattern analysis approach applied across Canada demonstrated that managed boreal forests were associated with rising edge density, declining core forest cover, and declining largest forest patch size. Boreal forests that had low disturbance rates were characterized by inherent forest cover pattern variation.This dissertation advanced new perspectives on conceptualizing, detecting, and characterizing patterns of anthropogenic disturbance regimes. Future work is identified primarily around the development and interpretation of landscape structure thresholds and transition indicators.
Forest structure is an important indicator of ecosystem function and carbon storage in above-ground biomass, yet observations of forest structure are scarce across Canada’s unmanaged bo-real. To reduce uncertainties in global carbon budgets, an improved understanding of spatial and temporal variability in forest structure is required across unmanaged boreal forests. The objective of this dissertation is to investigate how fire history and forest productivity together shape the structure of Canada’s boreal forests, and to develop methods to assess these relationships over large forested areas. Transects of airborne light detection and ranging (lidar) data, totaling 25,000 km in length, were collected across northern Canada in 2010, providing a unique opportunity to study spatial varia-bility in forest structure. To elucidate on the relationships between fire, productivity, and struc-ture, lidar measures of forest structure were combined with optical satellite indicators of disturb-ance history and forest productivity. Specifically, a 25-year chronosequence of forest regenera-tion following fire was developed, and the relationship between forest structure and productivity was assessed as a function of time since fire. In addition, the relationship between structure and productivity was assessed in stands with no recorded disturbances. Satellite-derived estimates of forest productivity were an important predictor of early stand de-velopment following fire, as lidar-derived estimates of canopy cover varied strongly along re-gional gradients of productivity after 15 years following fire (r = 0.63 – 0.72, p 50% canopy cover) prior to burning displayed faster growth and recovery compared to patches classified as open forest (20 – 50% canopy cover). Further, this research highlights the importance of monitoring multiple aspects of forest recovery, as lidar-derived estimates of canopy cover and stand height showed contrasting relationships to productivity in recently burned stands (1985 – 2009) as well as in stands with no recent disturbance. The results of this dissertation demonstrate the value of the airborne lidar transects for describing stand-level variability in forest structure over large areas, and demonstrate the need for lidar to validate wall-to-wall indicators of disturbance, productivity, and structure.
Over the last century Canadian boreal forests have warmed by 2-3° C, causing growing seasons to lengthen and alterations to annual productivity, which result in numerous responses from boreal tree species. Both disturbance and recovery cycles are affected, although change in northern Canadian boreal forests is difficult to detect, since they remain non-inventoried and lack detailed spatially explicit descriptive data. Through the use of Landsat time series, remote sensing offers the ability to map and monitor large forested areas over time to provide valuable information about boreal forests. The overall objective of this dissertation is to assess the capacity of remotely-sensed spectral time series to characterize forest recovery following disturbance in Canadian boreal forests.Major findings produced from the research presented in this dissertation show:• Boreal forest attributes are better estimated with Landsat time series metrics than single date information, and the inclusion of recovery metrics substantially improves accuracy• Choice of spectral index to monitor recovery is important, and the use of multiple spectral indexes can provide better and meaningful insights into forest recovery• The East/West division of the Boreal Shield ecozone is reinforced due differing spectral forest recovery trajectories that are suggestive of distinct recovery processes in each region. • Forest recovery rates are not fixed across the Boreal and Taiga Shield ecozones, with Taiga Shield spectral forest recovery rates showing a consistent positive trend, possibly indicating forests are recently recovering at an accelerated rate. The research presented in this dissertation advances the use of remote sensing to detect post-disturbance recovery in boreal forest ecosystems. Monitoring large forested areas such as the boreal for change is increasingly important as climatic conditions alter, and the spectral time series methods shown herein provide new tools to observe change in boreal forests. Future research directions are identified around first lengthening time series across longer periods of time, then extending these spectral time series approaches across jurisdictional lines in the pan-boreal region, and finally incorporating the data generated from these methods to be incorporated into carbon accounting frameworks.
Remote sensing is an important complementary data source to enable cost effective monitoring and mapping of biodiversity indicators over large extents in a consistent and repeatable manner. As such, remote sensing is capable of supporting the information needs of modern biodiversity conservation efforts. However, a number of critical challenges and opportunities deserve greater attention. The aim of this research is to advance the use of remote sensing and other geospatial techniques for large-area, multi-jurisdictional conservation of Canada’s boreal forest. Outcomes of this dissertation contributed to progress in each of four research themes: (i) assessing biodiversity across broad areas, (ii) identifying areas of high conservation priority (iii) evaluating the efficacy of current and hypothetical reserve networks, and (iv) incorporating future vegetation variability in conservation planning. The overall research findings indicate the tremendous capacity of the Canadian boreal forest to provide suitable areas for conservation investment and demonstrate the usefulness of these coarse-scale approaches for guiding ongoing research aimed at boreal conservation planning. Key findings included: (a) Reserves that were restricted to only intact forest landscapes were less flexible and efficient (more costly), (b) Reserves using accessibility (distance from road and human settlement) as a cost surrogate were able to satisfy a range of conservation targets and compactness levels while remaining remote from human influence, (c) Reserves (≥1000 km2;
Globally, buildings are responsible for more than 40% of energy demand and contribute more than 30% of CO₂ emissions. Various strategies and policies have been developed to reduce the negative of effects of energy use in the building sector, specifically targeting energy conservation and energy supply from renewable resources. As a basis for these strategies, decision-makers require estimates of existing energy demand. Traditionally, broad building sector energy estimates are derived using top-down modelling approaches that establish relations between energy use and variables such as income, fuel prices and gross domestic product. In contrast, individual building energy modelling has evolved sophisticated physically based simulations, populated by an abundance of variables related to building construction materials and components. However, for governments and decision-makers tasked with developing local strategies, techniques are needed to provide a detailed itemization of the building and environmental attributes that impact energy demand, as offered in building simulations, while maintaining the scalability to large areas provided in top-down models. Advances to geospatial technologies and datasets offer novel opportunities to satisfy these two conditions. Of particular interest is light detection and ranging (LiDAR), since it provides spatially contiguous measurements of urban form, otherwise unattainable across large areas. This dissertation presents a novel approach that integrates LiDAR data with building energy models to provide detailed and spatially contiguous estimates of energy demand in the residential building sector. LiDAR is used to augment building energy models by relating measured building form to internal energy components including envelope resistivity, fenestration and air leakage, and by assessing building envelope solar gains after accounting for local occlusions. Outcomes demonstrate that a LiDAR-based approach to building energy assessment is able to produce results that closely match those from manually informed building simulation software, thus offering a time and cost effective option for extensive and detailed analysis of energy demand. By presenting methods to decompose building energy demand into the site-specific components that influence energy end-use, this dissertation offers innovative opportunities to analyze and design spatially targeted building energy policies and strategies.
Advances in mobile computing provide an increasing number of possibilities for public participation in scientific research (PPSR). For example, a growing number of people have access to mobile computing devices, such as smartphones, equipped with sensors including a camera, global positioning system, the ability to record observations, and the ability transfer them over a network for collection and analysis. Literature has shown that PPSR-based approaches can have positive outcomes for volunteers (e.g., opportunities to pursue interests, develop skills, and influence decisions), for resource management (by providing data to inform management strategies), and for science. The objective of this dissertation is to explore how volunteers can use smartphones to collect data to inform forest management in a remote sensing project. The management of wildfires in communities near forested areas was chosen as a case study, and a smartphone application was developed and tested for collecting observations of the amount and arrangement of forest fuels by participants with a range of forestry experience living in fire-affected communities. First, to establish context, other projects using smartphones to collect Earth observation data were reviewed including related terms, concepts, challenges, and opportunities to identify methods of data collection and data processing. Second, questionnaires were given to the volunteers before and after using the application to collect data and were analyzed to understand the social and management considerations including the volunteers’ motivations, attitudes, and behaviours, and the potential of using a PPSR approach for wildfire management. Third, the locations where volunteers submitted data were re-measured and the quality of the data were assessed to provide guidelines for ensuring attribute accuracy and logical consistency. Fourth, the smartphone data was combined with multispectral remote sensing data and topography data to make estimates over broader areas. Finally, a framework was presented to direct future efforts using volunteered remote sensing data. This dissertation demonstrates an approach with potential to apply technology to help inform forest management in communities, with potentially positive outcomes for volunteers, communities, and forest managers.
The productivity of autotrophic organisms affects all life on Earth; hence, gaining insight in the variability of autotrophic productivity has received significant research interest. At cell to organism level, much knowledge has been gained under controlled conditions through laboratory analysis. At the stand level and beyond, control over the driving variables is limited, and hence experiments have relied on extensive time series, and geospatial analysis to observe changes in productivity across a wide range of environmental conditions. Significant technologies at these scales are eddy covariance that provides point sample estimates of productivity by measuring CO₂ fluxes between land and atmosphere, and remote sensing that provides for extrapolating eddy-covariance measurements across the landscape using canopy-reflectance data. Challenges in fusing eddy covariance with remote sensing relate to the limited capacity of airborne and spaceborne instruments to observe changes in the biophysical state of deep canopy strata; hence, eddy-covariance estimates that capture the productivity of an arbitrarily dense canopy volume are extrapolated based on top-of-canopy reflectance data. Proximal-sensing technology extends the acquisition of reflectance data to arbitrary locations within the canopy; however, these data are affected by the immediate canopy structure surrounding the sensor that introduces a sensor-location bias, and the direct use of these data in stand-level models is therefore challenging. This thesis explores the simulation of photosynthetic down-regulation using geometrically explicit forest models and meteorological records. The geometrically explicit models are constructed by combining laser-scanning data with tree-regeneration models, and are used to simulate a time series of leaf-level incident radiation. The parameters of a leaf-level photosynthesis model are then optimized against eddy-covariance productivity estimates. Finally, the potential of geometrically explicit models for the fusion of remote sensing and proximal sensing data is discussed.
The lodgepole pine (Pinus contorta) forests of British Columbia have been recently affected by mountain pine beetle (MPB) (Dendroctonus ponderosae), constituting one of the most destructive insect outbreaks in North America. In such a snow-dominated environment, a receding forest cover is associated with increases in snow accumulation during winter, enhancements of snowmelt rates and suppression of spring transpiration. These changes can elevate flooding risk and thus threaten society. However, the unprecedented extent of the disturbance and particular nature of the beetles’ severe but gradual effect on the forests’ integrity have challenged scientists aiming to quantify the real ecological impacts. Even though hydrologic models remain as the only tool currently available to evaluate the effects of MPB on hydrologic dynamics, they are impaired in their present form for relying on coarse and oversimplified characterizations of forest structure. Remote sensing technologies such as Airborne Laser Scanning (ALS), which provides detailed three-dimensional representations of canopy structure, offer a remarkable alternative to fill this knowledge gap. The main objective of this thesis is to determine how hydrologic modeling can be improved by remote sensing through a better characterization of forest structure. Given the variety and complexity of hydrologic models, the same research question is applied independently to the simplest forms of plot-level univariate empirical models and complex physically-based simulators operating at the watershed level. It was found that remotely-sensed forest metrics are better predictors of snow accumulation and ablation at the plot level than traditional ground-based variables, and that the accurate estimation of maximum snow accumulation and snow ablation with ultrasonic range devices significantly increases the quality of simple empirical models. It was also shown that a novel method, which minimizes the geometrical differences between ALS and traditional ground instruments’ data, was fundamental to obtain accurate plot-level estimates of forest structure metrics identified as primary drivers of snow processes. Wall-to-wall watershed-level coverage of hydrologically-relevant forest variables was successfully achieved by integrating ALS and Landsat metrics. The methods developed will result in better inputs for hydrologic models with the potential to improve the quality of snow process and streamflow predictions.
This thesis investigated observed responses of forest productivity to environmental changeand their predictability using semi-empirical carbon (C) cycle models in temperate-maritimeconifer forests in coastal British Columbia, Canada. Effects of environmental stress andhistorical responses to environmental trends were constrained using observations of grossprimary production (Pg) from eddy-covariance flux towers and stemwood growth (Gsw) andmortality (Msw) from permanent forest inventory plots.Observations suggested a long-term increasing trend in Gsw extending back to the Little IceAge, with decadal fluctuations in association with several 20th century drought episodes.Statistical models driven with climate variability, alone, could not reproduce the observedtrend in Gsw, while climate variability and sensitivity to carbon dioxide (CO₂), combined,expressed a moderately strong capacity to reproduce past trends and variability. Observationsalso indicated substantial wave-like fluctuations in Msw that could not be explained by standdensity-dependent processes, alone, while additional functions of drought sensitivity vialinear-threshold functions of evapotranspiration (ET) and precipitation (P) improved modelpredictions.The capacity to predict tree productivity was explored within a more mechanistic modellingframework, focusing on evaluation of physical principles used to simulate Pg in productionefficiency models (PEMs) and subsequent application within the established forestproductivity model, 3-PG, to simulate Pg, Gsw, and Msw. Comparison with observationshighlighted several deficiencies in the representation of environmental stress in PEMs thatrestrict the capacity to accurately simulate transient responses to environmental change, someof which arise from the model reduction and scaling techniques employed by PEMs, whileothers reflect unsettled physiological understanding. Consistent with regression modelsimulations, absence of CO₂ fertilization in 3-PG led to inability to reproduce observedtrends in Gsw.This research demonstrated that representation of environmental sensitivity in models of Gswand Msw does not lead to appreciable increases in model precision, yet is absolutely necessaryto achieve temporally-unbiased simulations at the regional scale. Findings also demonstratethe critical role of observation networks, including permanent forest inventories and longtermcontinuous meteorological and hydrological measurements as a necessary means ofadvancing and implementing model representation of environmental controls on forestproductivity.
No abstract available.
One of the critical issues in the prognoses of future climate change is a comprehensive understanding of the global carbon budget. Progress in C balance studies has been achieved either at stand or at continental scales. However, the coupled terrestrial carbon, nitrogen and hydrological dynamics are yet far from well understood and methods to estimate the land-atmosphere carbon fluxes at the landscape and regional scales are notably lacking. The major findings of this dissertation research are as follows: First, this dissertation improves our understanding of the terrestrial C processes, for example, at Douglas-fir stand in the Pacific Northwest: (i) Although the majority of carbon sequestration occurred during March through June, May through August was responsible for about 80% of the inter-annual variability of net ecosystem productivity (NEP). The major drivers of inter-annual variability of annual carbon fluxes were annual and spring mean temperatures (Ta) and water deficiency during late summer to autumn; (ii) Monthly GPP was linearly correlated with photosynthetic active radiation (Q) (r² = 0.85) and monthly Re was exponentially correlated with Ta (r² = 0.94); (iii) The responses of NEP to changes of Ta and Q were positive during the first and last four months of the year but were negative during the middle four months of the year. (iv) N fertilization increased annual NEP by ~83%, in the first year, resulted from increases in annual GPP by ~8% and from decreases in annual Re by ~5.8%. Secondly, this dissertation develops a pragmatic algorithm with synergy of footprint climatology and geospatial analyses for assessing the spatial representativeness of eddy-covariance flux tower measurements. This algorithm was then applied to the Canadian Carbon Program network. Thirdly, this dissertation develops an innovative up-scaling strategy by integrating ecosystem modeling, footprint climatology modeling, remote sensing, and data-model fusion for the scaling of C fluxes at stand, landscape and regional scales. And fourth, this dissertation develops an analytical scalar concentration footprint model to assess the influences of land surface heterogeneity on tower CO2 concentration measurements.Summarily, this dissertation research provides a sound basis for shaping future climate change adaptation policy related to carbon management
Information representing the species composition and structural configuration of forested ecosystems is critical for effective, sustainable management. In Canada, the methods employed to map forest species and structure vary, however, they conventionally include photogrammetric techniques. Despite common use, aerial photograph delineation and interpretation is time consuming and laborious, often yielding subjective results which cannot be easily updated, and is thus not well suited for quantitative mapping over extensive areas. In contrast, advanced methods for remotely quantifying forest characteristics show promise for improving conventional approaches. Two data sources of particular interest are hyperspectral and light detection and ranging (LiDAR). Hyperspectral sensors acquire data simultaneously in upwards of hundreds of narrow spectral channels, providing an unprecedented tool for differentiating between vegetation species. LiDAR systems directly measure the vertical distribution of foliage, providing detailed information on height, cover, and structure. This thesis integrated new generation remote sensing technologies with field data to improve forest species and structural information in the British Columbian southern Gulf Islands (SGI). Results indicate the objective was met, providing a state-of-the-art, step-by-step protocol for forest managers and ecologists to undertake detailed and accurate species and structural mapping of protected areas, while decreasing associated labor, time and subjectivity, and increasing repeatability, at a cost comparable, if not less, than conventional aerial photography. The unique outcomes of this thesis include the first spectral library of dominant tree species in Canada’s coastal Pacific Northwest, the first SGI inventory of LiDAR-metrics able to characterize and differentiate forest structure, significantly improved data for rare Garry oak habitat, markedly more detailed and accurate distribution information for 11 dominant tree species derived using an innovative classification approach and newly developed LiDAR metrics, and the first assessment in any environ of hyperspectral metrics for describing and differentiating avifaunal guilds based on diversity. In addition, results provide the first tree species heterogeneity predictions for the SGI, yielded through an object-based classification incorporating airborne hyperspectral data and space-borne multispectral data. The innovative methods described are not limited to the SGI, and can be replicated where targeted species/structural characteristics can be defined and differentiated based on hyperspectral-derived and/or LiDAR-derived metrics.
Bark beetle infestations in western Canada have caused damage at previously unrecorded levels. Conventional forest health surveys are conducted to collect information on these infestations; however, due to the widespread nature of attack digital remote sensing technologies have the potential to offer new methods to augment forest inventories. This thesis will investigate the utility of remotely sensed data to detect and monitor insect infestations and provide innovative approaches to determine forest health information. In the first section of the thesis the accuracies of conventional forest health surveys were reviewed and assessed in a series of plots at the edge of the infestation. Mitigation levels were shown to be 43%, which was inadequate to stop a doubling expansion rate. A review of the detection rates of digital remote sensing was also conducted and used in a simple expansion model to assess the capacity of digital techniques. In the second part of the thesis a series of innovative methods were applied over a hierarchy of remotely sensed data sets. Attacked trees identified during field surveys were delineated on fine scale imagery with an accuracy of 80.2%. From these delineations, tree [stem diameter (r = 0.71, p
Master's Student Supervision (2010-2017)
Observing landscape patterns at various temporal and spatial scales is central to mapping ecosystems. Traditionally, ecosystem mapping uses a combination of fieldwork and aerial photography interpretation. These methods, however, are time-consuming, prone to subjectivity, and difficult to update. Airborne Laser Scanning (ALS) is an advanced remote sensing technology that has increased in application in the past decade and has the potential to significantly increase and refine information content of ecosystem mapping, especially in the vertical dimension. ALS technology provides detailed information on topography and vegetation structure and has considerable potential to be used for terrestrial ecosystem classification and mapping. In this thesis, the potential to use ALS data to advance ecosystem mapping is examined. The current state of the science for using ALS data to classify and map key ecosystem attributes within an existing ecosystem mapping scheme is discussed by focusing on British Columbia’s Terrestrial Ecosystem Mapping (TEM) and its associated Predictive Ecosystem Mapping (PEM). Based on a detailed literature review, a site-specific case study was also developed with the goal of mapping TEM polygons for a forested landscape on Vancouver Island, British Columbia. To do so an object-based image analysis approach was used. The analysis examined which were the best suite of ALS-based terrain and vegetation metrics to define and distinguish individual site series. It established a workflow for the classification of site series within the study site and examined the capacity to map site series based on ALS derived values. Best segmentation parameters were first established and then the study area was classified for slope position-wetness and finally into the specific site series. In the classification of site series two approaches were used. One approach used only terrain metrics and the other incorporated vegetation metrics. Overall accuracies were 59% and 56% respectively. While this workflow requires refinement, it shows potential for improved accuracies by applying suggestions discussed.The thesis concludes with a discussion summarizing the findings of this research and highlighting future refinement to the methods applied in the case study, while also providing recommendations for the current application of ALS technology to TEM.
Vegetation structure is an important biodiversity indicator providing biological and physical environment that supports and maintains forest biodiversity. The airborne lidar (Light Detection and Ranging) systems have the advantage of directly measuring three-dimensional vegetation structure, and have been widely used in wildlife habitat mapping and species distribution modeling at the local scales. As lidar data are increasingly compiled into broad spatial coverage, the development of structural inventory and indicators to categorize habitat types and identify important patches would be beneficial to regional-level conservation planning and biodiversity monitoring. However, this area of research has not been adequately explored. Large-area mapping of critical habitat patches is also a fundamental step towards modeling habitat connectivity. Quantification and dynamic modeling of habitat connectivity under long-term influence of land cover change events provide insights into forest management and conservation planning, and including climate change constraints into the modeling framework also helps maintain ecosystem integrity and improve conservation effectiveness.Therefore, the objectives of this thesis are to 1) characterize vegetation structure and identify important habitat patches with critical structural traits using regional lidar dataset, and 2) build habitat networks to model connectivity dynamics under land cover change events. To do this, first, a novel approach using cluster analysis to process large-area lidar data into categorical classes representing natural groupings of habitat structure was applied to derive eight unique structure classes in the managed forested area in Alberta, Canada. Second, the structure classes indicating high levels of structure complexity combined with Landsat-derived forest cover types were used to identify important habitat patches to develop habitat networks. Lastly, spatial prioritization schemes based on different aspects of connectivity and climate constraints were generated and implemented through scenario-based simulations of land cover change events. Connectivity dynamics through the simulations were assessed and compared between scenarios. The result showed that the conservation strategies considering both habitat area and habitat spatial configuration were best at maintaining habitat connectivity, and taking climate constraints into consideration didn’t affect overall connectivity. Overall, this research provides an integrated approach to characterize habitat structure using large-area lidar data for dynamic connectivity modeling following land cover change simulations.
As of 2016, there were 57 community forestry organizations in British Columbia apart of various community forest agreements (CFA). Community forests allow for the development of multi-use management plans to reflect a diverse set of values. The availability of detailed information of the forested area is vital to maximizing a community’s benefits and profits. Airborne laser scanning (ALS) can provide estimates of conventional forest attributes, advance inventory attributes along with spatially describing ecosystem services (ES). This thesis combines ALS data, ground sampling data and vegetation resource inventory (VRI) data for the Sunshine Coast Community Forest (SCCF) located near Sechelt, British Columbia in a case study of the application of ALS data to benefit a community forest. Primary attributes (height, diameter at breast height, stem number, quadratic mean diameter, Lorey’s height, volume and biomass) were calculated using an area-based-approach. A secondary attribute (stem size distribution) was calculated using a two-parameter Weibull probability density function. Finally, a tertiary attribute - site indices - was calculated using maximum height from ALS. The reliability of primary attributes predictions varied, with stem number being the poorest (R²=0.51, p-value
Detailed observations of natural and anthropogenic disturbances that alter the forest structure and the distribution of carbon are essential to estimate changes in forest carbon sinks and sources. Remote sensing is one of the primary sources to provide observations of land cover and land-cover change for carbon studies and other ecological applications due to its ability to monitor the Earth’s surface on a regular and continuous basis. However, observations of change are often not attributed directly to an underlying disturbance type and are not well validated, especially in tropical areas.The overall objectives of this thesis are to 1) assess forest disturbances (natural and anthropogenic) and derive activity data for carbon budget modeling, and 2) estimate the impact of different activity data on the terrestrial carbon balance for REDD+ in Mexican tropical forests. To do so, a novel Multi-Source, Multi-Scale Disturbance (MS-D) assessment method was developed to: 1) characterize natural and anthropogenic forest disturbances; 2) obtain land-cover change observations; and 3) attribute land-cover changes to their most likely disturbance driver. Spatially-explicit layers of major disturbance types were generated in annual time steps for carbon modeling across the Yucatan Peninsula from 2005 to 2010. Using geospatial techniques and regression-tree analysis the MS-D approach successfully attributed 86% of land-cover changes derived from the MODIS satellite imagery to their underlying disturbance cause, creating synergies between remote-sensing products, forest inventory and ancillary datasets. Four remote-sensing products derived from Landsat and MODIS satellites were then compiled, providing inputs of activity data for carbon modeling with the CBM-CFS3. Two map sequences were generated for each product, with and without attributing land-cover changes to disturbance type with the MS-D approach. Annual carbon fluxes were simulated to compare the impact of: 1) spatial resolution, 2) temporal resolution, and 3) attribution/non-attribution of land-cover changes by disturbance type on carbon flux estimates. The results clearly demonstrated that different choices of satellite imagery and attribution of changes to disturbance types change the estimated carbon balance. This study provides an integral cost-effective approach to derive activity data for carbon modeling, and support policy and decision-making for forest monitoring and REDD+.
Improving our ability to track and monitor changes on Earth’s surface will inevitably enhance our ability to manage and monitor the biosphere. Remote Sensing technologies developed to monitor the Earth’s surface have already improved our understating of dynamic land cover change at a variety of scales. Fundamental to the identification of land cover change is the detection of abrupt disturbance events. These events constitute direct changes to the composition and structure of ecological systems and may have long lasting effects. In a forestry context it is important to identify disturbances in a timely manner in order to inform management decisions. The RapidEye constellation is a series of five identical Earth orbiting optical sensors capable of achieving five meter spatial resolution imagery with a daily return time. In this thesis we present two studies which assess the capacity of RapidEye to detect (1) stand replacing disturbances and (2) non-stand replacing disturbances in British Columbia. In the first study we develop a robust method to identify stand-replacing disturbances across seven regions in British Columbia. Overall accuracy for the classification of forest disturbance ranged from 83.65 ± 0.77% to 97.65 ± 0.25% for individual 25 X 25 km test locations.In the second study the utility of the RapidEye constellation to detect and characterize a low severity fire in a dry Western Canadian Forest was examined. Estimates of burn severity from field data were correlated with a selected suite of common spectral vegetation indices. All correlations between the ground estimates and vegetation indices produced significant results (p
Forests are considered important reservoirs of organic carbon and have been identified as essential in moderating climate change. Measuring the amount of carbon stored in forests helps improve our understanding of the carbon budget and help with climate change adaptation strategies. Therefore, effective and accurate methods in characterizing changing forest cover and biomass densities are needed.Both LiDAR (light detection and ranging) and radar (radio detection and ranging) technologies can contribute towards the study of forest biomass but one sensor alone cannot provide all the information necessary to monitor forests. Understanding and investigating synergies between different remotely sensed data sets provides new and innovative opportunities to monitor forests.The overall objective reported in this thesis is to demonstrate novel methods to integrate two remotely sensed data sets (i.e., radar and LiDAR) for the application of biomass estimation. This research was divided into two main questions: (1) can shorter wavelength radar variables provide improved biomass estimates when combined with LiDAR data; and (2) can the use of space-borne radar extend aboveground biomass estimates over a larger area using spatial modeling methods.In the first study, relationships between biomass and biomass components with LiDAR and radar data were examined through regression analyses to determine the best combined parameters to estimate biomass. Results indicated that integrating radar variables to a LiDAR-derived model of aboveground biomass helped explain an additional 17.9% of the variability in crown biomass. This corresponded in an improvement in crown biomass estimates of 10% RMSE. Furthermore, InSAR coherence magnitudes from C-band and L-band radars provided the best estimate of aboveground biomass using radar alone.In the second study, aboveground biomass transects derived from plot-based field data and LiDAR, and wall-to-wall radar were spatially integrated using three kriging techniques. The results indicated the importance of correlation between primary and secondary variables when using these kriging approaches. Also a 1000 m distance between biomass transects, was found to provide reasonable compromise between ease of use, accuracy, and cost of obtaining LiDAR data for the study area. Insights into other opportunities for further development in spatial modeling techniques are discussed.
Natural variability and disturbance events drive spatial and temporal variation in ecosystem processes and play key roles in ecosystem variety and the maintenance of species diversity. As a result, an improved understanding of the links between natural environmental variability and species diversity is needed to guide prioritisation of conservation and management actions. Ontario, the second largest province in Canada, covering approximately 1 million km², is environmentally diverse and is subject to a large amount of natural and anthropogenic disturbances. Remote sensing is uniquely capable of monitoring dynamic ecosystems over large areas in a repeatable and cost effective manner and has been shown to provide considerable benefit to assess species distribution and biodiversity.This thesis (1) examines an approach for detecting natural variability and disturbances of vegetation productivity from a remote sensing time-series and (2) demonstrates the use of satellite-derived indicators for the characterisation of moose habitat across Ontario. First, an approach was developed to assess temporal trends in vegetation productivity which utilised a Theil-Sen’s non-parametric statistical trend test over a 6-year period (2003-2008) of ten-day composites of Medium Resolution Imaging Spectroradiometer (MERIS) fraction of Photosynthetically Active Radiation (fPAR). Results indicated that this novel remote sensing approach can be used to characterise trends in landscape productivity patterns over large areas and can aid in provincial and national monitoring activities. Second, the research investigated the application of remotely sensed indicators such as vegetation productivity, land cover, topography, snow cover and natural and anthropogenic disturbances to predict moose occurrence and abundance. Results indicated that remotely sensed indicators were significantly correlated to moose habitat suitability with moose distribution being more accurately estimated than moose abundance. In addition to providing insights into the relative importance of the predictor covariates for moose occurrence and abundance, this study creates opportunities for further development of spatial models that closely examine the occurrence/abundance-habitat relationships which are highly valuable for habitat management decisions.
National parks in western Canada experience wildland fire events at differing frequencies, intensities, and burn severities. These episodic disturbances have varying implications for various biotic and abiotic processes and patterns. To predict burn severity, the differenced Normalized Burn Ratio (dNBR) algorithm, derived from Landsat imagery, has been used extensively throughout the wildland fire community. Researchers have often employed this approach to study the effects of fire across multiple contrasting landscapes. Many remote sensing scientists have concluded that incorporating pre-fire information into the current remote sensing dNBR methodology may make such models more transferable. In the first study the main purpose was to investigate the accuracies of the absolute dNBR versus its relative form (RdNBR) to estimate burn severity, in which was hypothesized that RdNBR would outperform dNBR based on former research by Miller and Thode (2007). The secondary purpose was to examine and compare the accuracies of RdNBR and dNBR algorithms in pre-fire landscapes with low canopy closure and high heterogeneity. Results indicate that the RdNBR-derived model did not estimate burn severity more accurately than dNBR (65.2% versus 70.2% classification accuracy, respectively) nor indicate improved estimates in the more heterogeneous and low canopy cover landscapes. In addition, we concluded that RdNBR is no more effective than dNBR at the regional, individual, and fine-scale vegetation levels. The results herein support the continued use of both the dNBR and RdNBR methods and the pursuit of developing regional models.In the second study, we compare the transferability of an overall model and those stratified by land cover and ecozone. Our second objective was to test the statistical benefit of incorporating pre- and post-fire information into standard dNBR approaches. We determined that an overall dNBR derived model successfully estimated burn severity for the majority of our study fires, which supports its transferability across multiple western Canadian landscapes. Results indicate that both pre- and post-fire remote sensing information provides a means of further understanding the different post-fire responses as well as showing minimal statistical burn severity estimates across the majority of fires, however, significant improvement was evident for three of the ten study fires.
- Evaluation of Ground Surface Models Derived from Unmanned Aerial Systems with Digital Aerial Photogrammetry in a Disturbed Conifer Forest (2019)
- Examining the Multi-Seasonal Consistency of Individual Tree Segmentation on Deciduous Stands Using Digital Aerial Photogrammetry (DAP) and Unmanned Aerial Systems (UAS) (2019)
- A National Assessment of Wetland Status and Trends for Canada’s Forested Ecosystems Using 33 Years of Earth Observation Satellite Data (2018)
- Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling (2018)
- Determining Optimal Video Length for the Estimation of Building Height through Radial Displacement Measurement from Space (2018)
ISPRS International Journal of Geo-Information
- Enhancing the Estimation of Stem-Size Distributions for Unimodal and Bimodal Stands in a Boreal Mixedwood Forest with Airborne Laser Scanning Data (2018)
- Reply to Vauhkonen: Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347 (2018)
- Vegetation Phenology Driving Error Variation in Digital Aerial Photogrammetrically Derived Terrain Models (2018)
- Spatial and Temporal Variability of Potential Evaporation across North American Forests (2017)
- Attributing changes in land cover using independent disturbance datasets: a case study of the Yucatan Peninsula, Mexico (2016)
Mascorro, Vanessa S. and Coops, Nicholas C. and Kurz, Werner A. and Olguin, Marcela
Regional Environmental Change 16 (1) 213-228
- Differentiation of Alternate Harvesting Practices Using Annual Time Series of Landsat Data (2016)
- Effect of topographic correction on forest change detection using spectral trend analysis of Landsat pixel-based composites (2016)
Chance, Curtis M. and Hermosilla, Txomin and Coops, Nicholas C. and Wulder, Michael A. and White, Joanne C.
International Journal of Applied Earth Observation and Geoinformation 44 186-194
- Enhancing Forest Growth and Yield Predictions with Airborne Laser Scanning Data: Increasing Spatial Detail and Optimizing Yield Curve Selection through Template Matching (2016)
- Forest recovery trends derived from Landsat time series for North American boreal forests (2016)
Pickell, Paul D. and Hermosilla, Txomin and Frazier, Ryan J. and Coops, Nicholas C. and Wulder, Michael A.
International Journal of Remote Sensing 37 (1) 138-149
- In Memorium: Thomas Hilker (2016)
- Using Remotely-Sensed Land Cover and Distribution Modeling to Estimate Tree Species Migration in the Pacific Northwest Region of North America (2016)
Coops, Nicholas C. and Waring, Richard H. and Plowright, Andrew and Lee, Joanna and Dilts, Thomas E.
Remote Sensing 8 (1)
- A Process-Based Approach to Estimate Chinese Fir (Cunninghamia lanceolata) Distribution and Productivity in Southern China under Climate Change (2015)
Lu, Yuhao and Coops, Nicholas C. and Wang, Tongli and Wang, Guangyu
Forests 6 (2) 360-379
- Agree on biodiversity metrics to track from space (2015)
Skidmore, Andrew K. and Pettorelli, Nathalie and Coops, Nicholas C. and Geller, Gary N. and Hansen, Matthew and Lucas, Richard and Muecher, Caspar A. and O'Connor, Brian and Paganini, Marc and Pereira, Henrique Miguel and Schaepman, Michael E. and Turner, Woody and Wang, Tiejun and Wegmann, Martin
Nature 523 (7561) 403-405
- An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites (2015)
Hermosilla, Txomin and Wulder, Michael A. and White, Joanne C. and Coops, Nicholas C. and Hobart, Geordie W.
Remote Sensing of Environment 158 220-234
- Attenuation of urban agricultural production potential and crop water footprint due to shading from buildings and trees (2015)
Johnson, Mark S. and Lathuilliere, Michael J. and Tooke, Thoreau R. and Coops, Nicholas C.
Environmental Research Letters 10 (6)
- Augmenting Site Index Estimation with Airborne Laser Scanning Data (2015)
Tompalski, Piotr and Coops, Nicholas C. and White, Joanne C. and Wulder, Michael A.
Forest Science 61 (5) 861-873
- Boreal Shield forest disturbance and recovery trends using Landsat time series (2015)
Frazier, Ryan J. and Coops, Nicholas C. and Wulder, Michael A.
Remote Sensing of Environment 170 317-327
- Canadian Journal Remote Sensing Special Issue "36th Canadian Symposium on Remote Sensing" June 8-11, 2011 Exploring Synergies (2015)
Coops, Nicholas C. and Power, Desmond and Leblon, Brigitte
Canadian Journal of Remote Sensing 41 (3) 246
- Characterizing residual structure and forest recovery following high-severity fire in the western boreal of Canada using Landsat time-series and airborne lidar data (2015)
Bolton, Douglas K. and Coops, Nicholas C. and Wulder, Michael A.
Remote Sensing of Environment 163 48-60
- Comparing ALS and Image-Based Point Cloud Metrics and Modelled Forest Inventory Attributes in a Complex Coastal Forest Environment (2015)
White, Joanne C. and Stepper, Christoph and Tompalski, Piotr and Coops, Nicholas C. and Wulder, Michael A.
Forests 6 (10) 3704-3732
- Comparing patterns in forest stand structure following variable harvests using airborne laser scanning data (2015)
Nijland, Wiebe and Coops, Nicholas C. and Macdonald, S. Ellen and Nielsen, Scott E. and Bater, Christopher W. and Stadt, J. John
Forest Ecology and Management 354 272-280
- Comparing Stem Volume Predictions of Coastal Douglas-Fir Stands in British Columbia Using a Simple Physiological Model and LiDAR Remote Sensing (2015)
Lu, Yuhao and Coops, Nicholas C. and Bolton, Douglas K. and Wang, Tongli and Wang, Guangyu
Forest Science 61 (3) 586-596
- Detecting forest damage after a low-severity fire using remote sensing at multiple scales (2015)
Arnett, John T. T. R. and Coops, Nicholas C. and Daniels, Lori D. and Falls, Robert W.
International Journal of Applied Earth Observation and Geoinformation 35 239-246
- Embedding sustainability learning pathways across the university (2015)
Marcus, Jean and Coops, Nicholas C. and Ellis, Shona and Robinson, John
Current Opinion in Environmental Sustainability 16 7-13
- Enriching ALS-Derived Area-Based Estimates of Volume through Tree-Level Downscaling (2015)
Tompalski, Piotr and Coops, Nicholas C. and White, Joanne C. and Wulder, Michael A.
Forests 6 (8) 2608-2630
- Estimating Forest Site Productivity Using Airborne Laser Scanning Data and Landsat Time Series (2015)
Tompalski, Piotr and Coops, Nicholas C. and White, Joanne C. and Wulder, Michael A. and Pickell, Paul D.
Canadian Journal of Remote Sensing 41 (3) 232-245
- Evaluating the impact of leaf-on and leaf-off airborne laser scanning data on the estimation of forest inventory attributes with the area-based approach (2015)
White, Joanne C. and Arnett, John T. T. R. and Wulder, Michael A. and Tompalski, Piotr and Coops, Nicholas C.
Canadian Journal of Forest Research 45 (11) 1498-1513
- Global satellite monitoring of climate-induced vegetation disturbances (2015)
McDowell, Nate G. and Coops, Nicholas C. and Beck, Pieter S. A. and Chambers, Jeffrey Q. and Gangodagamage, Chandana and Hicke, Jeffrey A. and Huang, Cho-ying and Kennedy, Robert and Krofcheck, Dan J. and Litvak, Marcy and Meddens, Arjan J. H. and Muss, Jordan and Negron-Juarez, Robinson and Peng, Changhui and Schwantes, Amanda M. and Swenson, Jennifer J. and Vernon, Louis J. and Williams, A. Park and Xu, Chonggang and Zhao, Maosheng and Running, Steve W.
Trends in Plant Science 20 (2) 114-123
- How an entry-level, interdisciplinary sustainability course revealed the benefits and challenges of a university-wide initiative for sustainability education (2015)
Coops, Nicholas C. and Marcus, Jean and Construt, Ileana and Frank, Erica and Kellett, Ron and Mazzi, Eric and Munro, Alison and Nesbit, Susan and Riseman, Andrew and Robinson, John and Schultz, Anneliese and Sipos, Yona
International Journal of Sustainability in Higher Education 16 (5) 729-747
- Indicators of vegetation productivity under a changing climate in British Columbia, Canada (2015)
Holmes, Keith R. and Coops, Nicholas C. and Nelson, Trisalyn A. and Fontana, Fabio M. A. and Wulder, Michael A.
Applied Geography 56 135-144
- Inferring drought and heat sensitivity across a Mediterranean forest region in southwest Western Australia: a comparison of approaches (2015)
Brouwers, N. C. and van Dongen, R. and Matusick, G. and Coops, N. C. and Strelein, G. and Hardy, G.
Forestry 88 (4) 454-464
- Integrating optical satellite data and airborne laser scanning in habitat classification for wildlife management (2015)
Nijland, W. and Coops, N. C. and Nielsen, S. E. and Stenhouse, G.
International Journal of Applied Earth Observation and Geoinformation 38 242-250
- Large Area Mapping of Annual Land Cover Dynamics Using Multitemporal Change Detection and Classification of Landsat Time Series Data (2015)
Franklin, Steven E. and Ahmed, Oumer S. and Wulder, Michael A. and White, Joanne C. and Hermosilla, Txomin and Coops, Nicholas C.
Canadian Journal of Remote Sensing 41 (4) 293-314
- Past-century decline in forest regeneration potential across a latitudinal and elevational gradient in Canada (2015)
Erickson, Adam and Nitschke, Craig and Coops, Nicholas and Cumming, Steven and Stenhouse, Gordon
Ecological Modelling 313 94-102
- Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics (2015)
Hermosilla, Txomin and Wulder, Michael A. and White, Joanne C. and Coops, Nicholas C. and Hobart, Geordie W.
Remote Sensing of Environment 170 121-132
- Remote sensing and object-based techniques for mapping fine-scale industrial disturbances (2015)
Powers, Ryan P. and Hermosilla, Txomin and Coops, Nicholas C. and Chen, Gang
International Journal of Applied Earth Observation and Geoinformation 34 51-57
- Remote sensing proxies of productivity and moisture predict forest stand type and recovery rate following experimental harvest (2015)
Nijland, Wiebe and Coops, Nicholas C. and Macdonald, S. Ellen and Nielsen, Scott E. and Bater, Christopher W. and White, Barry and Ogilvie, Jae and Stadt, John
Forest Ecology and Management 357 239-247
- Spatial data, analysis approaches, and information needs for spatial ecosystem service assessments: a review (2015)
Andrew, Margaret E. and Wulder, Michael A. and Nelson, Trisalyn A. and Coops, Nicholas C.
Giscience & Remote Sensing 52 (3) 344-373
- Technological Advancement in Tower-Based Canopy Reflectance Monitoring: The AMSPEC-III System (2015)
Tortini, Riccardo and Hilker, Thomas and Coops, Nicholas C. and Nesic, Zoran
Sensors 15 (12) 32020-32030
- The grazing impacts of four barren ground caribou herds (Rangifer tarandus groenlandicus) on their summer ranges: An application of archived remotely sensed vegetation productivity data (2015)
Rickbeil, Gregory J. M. and Coops, Nicholas C. and Adamczewski, Jan
Remote Sensing of Environment 164 314-323
- The spatial patterns of anthropogenic disturbance in the western Canadian boreal forest following oil and gas development (2015)
Pickell, Paul D. and Andison, David W. and Coops, Nicholas C. and Gergel, Sarah E. and Marshall, Peter L.
Canadian Journal of Forest Research 45 (6) 732-743
- Using Stochastic Ray Tracing to Simulate a Dense Time Series of Gross Primary Productivity (2015)
van Leeuwen, Martin and Coops, Nicholas C. and Black, T. Andrew
Remote Sensing 7 (12) 17272-17290
- Virtual constellations for global terrestrial monitoring (2015)
Wulder, Michael A. and Hilker, Thomas and White, Joanne C. and Coops, Nicholas C. and Masek, Jeffrey G. and Pflugmacher, Dirk and Crevier, Yves
Remote Sensing of Environment 170 62-76
- Assessing coastal species distribution models through the integration of terrestrial, oceanic and atmospheric data (2014)
Rickbeil, Gregory J. M. and Coops, Nicholas C. and Drever, Mark C. and Nelson, Trisalyn A.
Journal of Biogeography 41 (8) 1614-1625
- Assessing conservation regionalization schemes: employing a beta diversity metric to test the environmental surrogacy approach (2014)
Rickbeil, Gregory J. M. and Coops, Nicholas C. and Andrew, Margaret E. and Bolton, Douglas K. and Mahony, Nancy and Nelson, Trisalyn A.
Diversity and Distributions 20 (5) 503-514
- Assessing scalar concentration footprint climatology and land surface impacts on tall-tower CO2 concentration measurements in the boreal forest of central Saskatchewan, Canada (2014)
Chen, Baozhang and Zhang, Huifang and Coops, Nicholas C. and Fu, Dongjie and Worthy, Douglas E. J. and Xu, Guang and Black, T. Andy
Theoretical and Applied Climatology 118 (1-2) 115-132
- Assessing the quality of forest fuel loading data collected using public participation methods and smartphones (2014)
Ferster, Colin J. and Coops, Nicholas C.
International Journal of Wildland Fire 23 (4) 585-590
- Changes in vegetation photosynthetic activity trends across the Asia-Pacific region over the last three decades (2014)
Chen, Baozhang and Xu, Guang and Coops, Nicholas C. and Ciais, Philippe and Innes, John L. and Wang, Guangyu and Myneni, Ranga B. and Wang, Tongli and Krzyzanowski, Judi and Li, Qinglin and Cao, Lin and Liu, Ying
Remote Sensing of Environment 144 28-41
- Characterization of aboveground biomass in an unmanaged boreal forest using Landsat temporal segmentation metrics (2014)
Frazier, Ryan J. and Coops, Nicholas C. and Wulder, Michael A. and Kennedy, Robert
Isprs Journal of Photogrammetry and Remote Sensing 92 137-146
- Characterizing a Decade of Disturbance Events Using Landsat and MODIS Satellite Imagery in Western Alberta, Canada for Grizzly Bear Management (2014)
White, Carson F. H. and Coops, Nicholas C. and Nijland, Wiebe and Hilker, Thomas and Nelson, Trisalyn A. and Wulder, Michael A. and Nielsen, Scott E. and Stenhouse, Gordon
Canadian Journal of Remote Sensing 40 (5) 336-347
- Comparison of remote sensing and ground-based methods for determining residue burn pile wood volumes and biomass (2014)
Trofymow, J. A. and Coops, N. C. and Hayhurst, D.
Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 44 (3) 182-194
- Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data (2014)
Hermosilla, T. and Coops, N. C. and Ruiz, L. A. and Moskal, L. M.
Remote Sensing Letters 5 (4) 332-341
- Detecting Stand-Replacing Disturbance using RapidEye Imagery: a Tasseled Cap Transformation and Modified Disturbance Index (2014)
Arnett, John T. T. R. and Coops, Nicholas C. and Gergel, Sarah E. and Falls, Robert W. and Baker, Russell H.
Canadian Journal of Remote Sensing 40 (1) 1-14
- Estimating Forest Stand Age from LiDAR-Derived Predictors and Nearest Neighbor Imputation (2014)
Racine, Etienne B. and Coops, Nicholas C. and St-Onge, Benoit and Begin, Jean
Forest Science 60 (1) 128-136
- Estimating moose (Alces alces) occurrence and abundance from remotely derived environmental indicators (2014)
Michaud, Jean-Simon and Coops, Nicholas C. and Andrew, Margaret E. and Wulder, Michael A. and Brown, Glen S. and Rickbeil, Gregory J. M.
Remote Sensing of Environment 152 190-201
- Estimation of forest structural variables using small-footprint full-waveform LiDAR in a subtropical forest, China (2014)
Cao, Lin and Coops, Nicholas and Hermosilla, Txomin and Dai, Jinsong and Weng, Q and Gamba, P and Xian, G and Wang, G and Zhu, J
2014 Third International Workshop on Earth Observation and Remote Sensing Applications (Eorsa 2014)
- Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data (2014)
Hermosilla, Txomin and Ruiz, Luis A. and Kazakova, Alexandra N. and Coops, Nicholas C. and Moskal, L. Monika
International Journal of Wildland Fire 23 (2) 224-233
- Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models (2014)
Varhola, Andres and Coops, Nicholas C. and Alila, Younes and Weiler, Markus
Hydrological Processes 28 (15) 4433-4448
- Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics (2014)
Nijland, Wiebe and Nielsen, Scott E. and Coops, Nicholas C. and Wulder, Michael A. and Stenhouse, Gordon B.
Journal of Applied Remote Sensing 8
- Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe (2014)
D'Odorico, Petra and Gonsamo, Alemu and Pinty, Bernard and Gobron, Nadine and Coops, Nicholas and Mendez, Elias and Schaepman, Michael E.
Remote Sensing of Environment 142 141-154
- Make Earth observations open access (2014)
Wulder, Michael A. and Coops, Nicholas C.
Nature 513 (7516) 30-31
- Mapping Above- and Below-Ground Biomass Components in Subtropical Forests Using Small-Footprint LiDAR (2014)
Cao, Lin and Coops, Nicholas C. and Innes, John and Dai, Jinsong and She, Guanghui
Forests 5 (6) 1356-1373
- Mapping demand for residential building thermal energy services using airborne LiDAR (2014)
Tooke, Thoreau Rory and van der Laan, Michael and Coops, Nicholas C.
Applied Energy 127 125-134
- Monitoring anthropogenic disturbance trends in an industrialized boreal forest with Landsat time series (2014)
Pickell, Paul D. and Hermosilla, Txomin and Coops, Nicholas C. and Masek, Jeffrey G. and Franks, Shannon and Huang, Chengquang
Remote Sensing Letters 5 (9) 783-792
- Monitoring of a National-Scale Indirect Indicator of Biodiversity Using a Long Time-Series of Remotely Sensed Imagery (2014)
Coops, Nicholas C. and Fontana, Fabio M. A. and Harvey, Gillian K. A. and Nelson, Trisalyn A. and Wulder, Michael A.
Canadian Journal of Remote Sensing 40 (3) 179-191
- Monitoring plant condition and phenology using infrared sensitive consumer grade digital cameras (2014)
Nijland, Wiebe and de Jong, Rogier and de Jong, Steven M. and Wulder, Michael A. and Bater, Chris W. and Coops, Nicholas C.
Agricultural and Forest Meteorology 184 98-106
- Pixel-Based Image Compositing for Large-Area Dense Time Series Applications and Science (2014)
White, J. C. and Wulder, M. A. and Hobart, G. W. and Luther, J. E. and Hermosilla, T. and Griffiths, P. and Coops, N. C. and Hall, R. J. and Hostert, P. and Dyk, A. and Guindon, L.
Canadian Journal of Remote Sensing 40 (3) 192-212
- Potentials and limitations for estimating daytime ecosystem respiration by combining tower-based remote sensing and carbon flux measurements (2014)
Hilker, Thomas and Hall, Forrest G. and Coops, Nicholas C. and Black, Andrew T. and Jassal, Rachhpal and Mathys, Amanda and Grant, Nicholas
Remote Sensing of Environment 150 44-52
- Predicting building ages from LiDAR data with random forests for building energy modeling (2014)
Tooke, Thoreau Rory and Coops, Nicholas C. and Webster, Jessica
Energy and Buildings 68 603-610
- Process-Based Modeling to Assess the Effects of Recent Climatic Variation on Site Productivity and Forest Function across Western North America (2014)
Waring, Richard H. and Coops, Nicholas C. and Mathys, Amanda and Hilker, Thomas and Latta, Greg
Forests 5 (3) 518-534
- Research Note Assessing the Impact of Field of View on Monitoring Understory and Overstory Phenology Using Digital Repeat Photography (2014)
Vartanian, M. and Nijland, W. and Coops, N. C. and Bater, C. and Wulder, M. A. and Stenhouse, G.
Canadian Journal of Remote Sensing 40 (2) 85-91
- Simulating the impacts of error in species and height upon tree volume derived from airborne laser scanning data (2014)
Tompalski, Piotr and Coops, Nicholas C. and White, Joanne C. and Wulder, Michael A.
Forest Ecology and Management 327 167-177
- Soil water availability effects on the distribution of 20 tree species in western North America (2014)
Mathys, Amanda and Coops, Nicholas C. and Waring, Richard H.
Forest Ecology and Management 313 144-152
- Using Small-Footprint Discrete and Full-Waveform Airborne LiDAR Metrics to Estimate Total Biomass and Biomass Components in Subtropical Forests (2014)
Cao, Lin and Coops, Nicholas C. and Hermosilla, Txomin and Innes, John and Dai, Jinsong and She, Guanghui
Remote Sensing 6 (8) 7110-7135
- A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach (2013)
White, Joanne C. and Wulder, Michael A. and Varhola, Andres and Vastaranta, Mikko and Coops, Nicholas C. and Cook, Bruce D. and Pitt, Doug and Woods, Murray
Forestry Chronicle 89 (6) 722-723
- A point obstruction stacking (POSt) approach to wall irradiance modeling across urban environments (2013)
Tooke, Thoreau Rory and Coops, Nicholas C. and Christen, Andreas
Building and Environment 60 234-242
- A remote sensing approach to biodiversity assessment and regionalization of the Canadian boreal forest (2013)
Powers, Ryan P. and Coops, Nicholas C. and Morgan, Jessica L. and Wulder, Michael A. and Nelson, Trisalyn A. and Drever, Charles R. and Cumming, Steven G.
Progress in Physical Geography 37 (1) 36-62
- A review of earth observation using mobile personal communication devices (2013)
Ferster, Colin J. and Coops, Nicholas C.
Computers & Geosciences 51 339-349
- A Review of Remote Sensing for Urban Energy System Management and Planning (2013)
Tooke, Thoreau Rory and Coops, Nicholas C. and IEEE
2013 Joint Urban Remote Sensing Event (Jurse) 167-170
- A systems approach to carbon cycling and emissions modeling at an urban neighborhood scale (2013)
Kellett, Ronald and Christen, Andreas and Coops, Nicholas C. and van der Laan, Michael and Crawford, Ben and Tooke, Thoreau Rory and Olchovski, Irina
Landscape and Urban Planning 110 48-58
- An Exploratory Assessment of a Smartphone Application for Public Participation in Forest Fuels Measurement in the Wildland-Urban Interface (2013)
Ferster, Colin J. and Coops, Nicholas C. and Harshaw, Howard W. and Kozak, Robert A. and Meitner, Michael J.
Forests 4 (4) 1199-1219
- Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations (2013)
Coggins, Sam B. and Coops, Nicholas C. and Hilker, Thomas and Wulder, Michael A.
International Journal of Applied Earth Observation and Geoinformation 21 444-452
- Automated reconstruction of tree and canopy structure for modeling the internal canopy radiation regime (2013)
van Leeuwen, Martin and Coops, Nicholas C. and Hilker, Thomas and Wulder, Michael A. and Newnham, Glenn J. and Culvenor, Darius S.
Remote Sensing of Environment 136 286-300
- Bias in lidar-based canopy gap fraction estimates (2013)
Vaccari, Simone and van Leeuwen, Martin and Calders, Kim and Coops, Nicholas C. and Herold, Martin
Remote Sensing Letters 4 (4) 391-399
- Biodiversity Indicators Show Climate Change Will Alter Vegetation in Parks and Protected Areas. (2013)
Holmes, Keith R. and Nelson, Trisalyn A. and Coops, Nicholas C. and Wulder, Michael A.
Diversity-Basel 5 (2) 352-373
- Characterization of an alpine tree line using airborne LiDAR data and physiological modeling (2013)
Coops, Nicholas C. and Morsdorf, Felix and Schaepman, Michael E. and Zimmermann, Niklaus E.
Global Change Biology 19 (12) 3808-3821
- Characterizations of anthropogenic disturbance patterns in the mixedwood boreal forest of Alberta, Canada (2013)
Pickell, Paul D. and Andison, David W. and Coops, Nicholas C.
Forest Ecology and Management 304 243-253
- Describing avifaunal richness with functional and structural bioindicators derived from advanced airborne remotely sensed data (2013)
Jones, Trevor G. and Arcese, Peter and Sharma, Tara and Coops, Nicholas C.
International Journal of Remote Sensing 34 (8) 2689-2713
- Ecosystem classifications based on summer and winter conditions (2013)
Andrew, Margaret E. and Nelson, Trisalyn A. and Wulder, Michael A. and Hobart, George W. and Coops, Nicholas C. and Farmer, Carson J. Q.
Environmental Monitoring and Assessment 185 (4) 3057-3079
- Essential Biodiversity Variables (2013)
Pereira, H. M. and Ferrier, S. and Walters, M. and Geller, G. N. and Jongman, R. H. G. and Scholes, R. J. and Bruford, M. W. and Brummitt, N. and Butchart, S. H. M. and Cardoso, A. C. and Coops, N. C. and Dulloo, E. and Faith, D. P. and Freyhof, J. and Gregory, R. D. and Heip, C. and Hoeft, R. and Hurtt, G. and Jetz, W. and Karp, D. S. and McGeoch, M. A. and Obura, D. and Onoda, Y. and Pettorelli, N. and Reyers, B. and Sayre, R. and Scharlemann
Science 339 (6117) 277-278
- Estimation of aerodynamic roughness of a harvested Douglas-fir forest using airborne LiDAR (2013)
Paul-Limoges, E. and Christen, A. and Coops, N. C. and Black, T. A. and Trofymow, J. A.
Remote Sensing of Environment 136 225-233
- Estimation of watershed-level distributed forest structure metrics relevant to hydrologic modeling using LiDAR and Landsat (2013)
Varhola, Andres and Coops, Nicholas C.
Journal of Hydrology 487 70-86
- Exploring the ecological processes driving geographical patterns of breeding bird richness in British Columbia, Canada (2013)
Fitterer, Jessica L. and Nelson, Trisalyn A. and Coops, Nicholas C. and Wulder, Michael A. and Mahony, Nancy A.
Ecological Applications 23 (4) 888-903
- Forest inventory stand height estimates from very high spatial resolution satellite imagery calibrated with lidar plots (2013)
Mora, Brice and Wulder, Michael A. and Hobart, Geordie W. and White, Joanne C. and Bater, Christopher W. and Gougeon, Francois A. and Varhola, Andres and Coops, Nicholas C.
International Journal of Remote Sensing 34 (12) 4406-4424
- Integrating accessibility and intactness into large-area conservation planning in the Canadian boreal forest (2013)
Powers, Ryan P. and Coops, Nicholas C. and Nelson, Trisalyn and Wulder, Michael A. and Drever, C. Ronnie
Biological Conservation 167 371-379
- Integrating airborne LiDAR and space-borne radar via multivariate kriging to estimate above-ground biomass (2013)
Tsui, Olivier W. and Coops, Nicholas C. and Wulder, Michael A. and Marshall, Peter L.
Remote Sensing of Environment 139 340-352
- Investigating the agreement between global canopy height maps and airborne Lidar derived height estimates over Canada (2013)
Bolton, Douglas K. and Coops, Nicholas C. and Wulder, Michael A.
Canadian Journal of Remote Sensing 39 S139-S151
- Measuring forest structure along productivity gradients in the Canadian boreal with small-footprint Lidar (2013)
Bolton, Douglas K. and Coops, Nicholas C. and Wulder, Michael A.
Environmental Monitoring and Assessment 185 (8) 6617-6634
- Prediction of Wood Fiber Attributes from LiDAR-Derived Forest Canopy Indicators (2013)
Hilker, Thomas and Frazer, Gordon W. and Coops, Nicholas C. and Wulder, Michael A. and Newnham, Glenn J. and Stewart, James D. and van Leeuwen, Martin and Culvenor, Darius S.
Forest Science 59 (2) 231-242
- Remote sensing of transpiration and heat fluxes using multi-angle observations (2013)
Hilker, Thomas and Hall, Forrest G. and Coops, Nicholas C. and Collatz, James G. and Black, T. Andrew and Tucker, Compton J. and Sellers, Piers J. and Grant, Nicholas
Remote Sensing of Environment 137 31-42
- Status and prospects for LiDAR remote sensing of forested ecosystems (2013)
Wulder, M. A. and Coops, N. C. and Hudak, A. T. and Morsdorf, F. and Nelson, R. and Newnham, G. and Vastaranta, M.
Canadian Journal of Remote Sensing 39 S1-S5
- The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning (2013)
White, Joanne C. and Wulder, Michael A. and Vastaranta, Mikko and Coops, Nicholas C. and Pitt, Doug and Woods, Murray
Forests 4 (3) 518-536
- Towards the Operational Use of Satellite Hyperspectral Image Data for Mapping Nutrient Status and Fertilizer Requirements in Australian Plantation Forests (2013)
Sims, Neil C. and Culvenor, Darius and Newnham, Glenn and Coops, Nicholas C. and Hopmans, Peter
Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (2) 320-328
- Vegetation phenology can be captured with digital repeat photography and linked to variability of root nutrition in Hedysarum alpinum (2013)
Nijland, W. and Coops, N. C. and Coogan, S. C. P. and Bater, C. W. and Wulder, M. A. and Nielsen, S. E. and McDermid, G. and Stenhouse, G. B.
Applied Vegetation Science 16 (2) 317-324
- What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series? (2013)
Coops, Nicholas C. and Schaepman, Michael E. and Mucher, Caspar A.
Landscape Ecology 28 (8) 1529-1543
- A simple technique for co-registration of terrestrial LiDAR observations for forestry applications (2012)
Hilker, Thomas and Coops, Nicholas C. and Culvenor, Darius S. and Newnham, Glenn and Wulder, Michael A. and Bater, Christopher W. and Siggins, Anders
Remote Sensing Letters 3 (3) 239-247
- Accelerating regrowth of temperate-maritime forests due to environmental change (2012)
Hember, Robbie A. and Kurz, Werner A. and Metsaranta, Juha M. and Black, T. Andy and Guy, Robert D. and Coops, Nicholas C.
Global Change Biology 18 (6) 2026-2040
- Assessing the impact of N-fertilization on biochemical composition and biomass of a Douglas-fir canopy-A remote sensing approach (2012)
Hilker, Thomas and Lepine, Lucie and Coops, Nicholas C. and Jassal, Rachhpal S. and Black, T. Andrew and Wulder, Michael A. and Ollinger, Scott and Tsui, Olivier and Day, Michelle
Agricultural and Forest Meteorology 153 124-133
- Assessing the utility of LiDAR to differentiate among vegetation structural classes (2012)
Jones, Trevor G. and Coops, Nicholas C. and Sharma, Tara
Remote Sensing Letters 3 (3) 231-238
- Beta-diversity gradients of butterflies along productivity axes (2012)
Andrew, Margaret E. and Wulder, Michael A. and Coops, Nicholas C. and Baillargeon, Guy
Global Ecology and Biogeography 21 (3) 352-364
- Characterising spatiotemporal environmental and natural variation using a dynamic habitat index throughout the province of Ontario (2012)
Michaud, Jean-Simon and Coops, Nicholas C. and Andrew, Margaret E. and Wulder, Michael A.
Ecological Indicators 18 303-311
- Characterizing spatial representativeness of flux tower eddy-covariance measurements across the Canadian Carbon Program Network using remote sensing and footprint analysis (2012)
Chen, Baozhang and Coops, Nicholas C. and Fu, Dongjie and Margolis, Hank A. and Amiro, Brian D. and Black, T. Andrew and Arain, M. Altaf and Barr, Alan G. and Bourque, Charles P. -A. and Flanagan, Lawrence B. and Lafleur, Peter M. and McCaughey, J. Harry and Wofsy, Steven C.
Remote Sensing of Environment 124 742-755
- Comparison of Terrestrial and Airborne LiDAR in Describing Stand Structure of a Thinned lodgepole Pine Forest (2012)
Hilker, Thomas and Coops, Nicholas C. and Newnham, Glenn J. and van Leeuwen, Martin and Wulder, Michael A. and Stewart, Jim and Culvenor, Darius S.
Journal of Forestry 110 (2) 97-104
- Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: I. Model formulation (2012)
Hall, Forrest G. and Hilker, Thomas and Coops, Nicholas C.
Remote Sensing of Environment 121 301-308
- Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: II Model implementation and validation (2012)
Hilker, Thomas and Hall, Forrest G. and Tucker, Compton J. and Coops, Nicholas C. and Black, T. Andrew and Nichol, Caroline J. and Sellers, Piers J. and Barr, Alan and Hollinger, David Y. and Munger, J. W.
Remote Sensing of Environment 121 287-300
- Digital high spatial resolution aerial imagery to support forest health monitoring: the mountain pine beetle context (2012)
Wulder, Michael A. and White, Joanne C. and Coggins, Sam and Ortlepp, Stephanie M. and Coops, Nicholas C. and Heath, Jamie and Mora, Brice
Journal of Applied Remote Sensing 6
- Estimation of forest structure metrics relevant to hydrologic modelling using coordinate transformation of airborne laser scanning data (2012)
Varhola, A. and Frazer, G. W. and Teti, P. and Coops, N. C.
Hydrology and Earth System Sciences 16 (10) 3749-3766
- Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison (vol 222, pg 3236, 2011) (2012)
Wang, Z. and Grant, R. F. and Arain, M. A. and Chen, B. N. and Coops, N. and Hember, R. and Kurz, W. A. and Price, D. T. and Stinson, G. and Trofymow, J. A. and Yeluripati, J. and Chen, Z.
Ecological Modelling 226 140
- Generation of a novel 1 km NDVI data set over Canada, the northern United States, and Greenland based on historical AVHRR data (2012)
Fontana, Fabio M. A. and Coops, Nicholas C. and Khlopenkov, Konstantin V. and Trishchenko, Alexander P. and Riffler, Michael and Wulder, Michael A.
Remote Sensing of Environment 121 171-185
- Identification of de facto protected areas in boreal Canada (2012)
Andrew, Margaret E. and Wulder, Michael A. and Coops, Nicholas C.
Biological Conservation 146 (1) 97-107
- Integrated irradiance modelling in the urban environment based on remotely sensed data (2012)
Tooke, Thoreau Rory and Coops, Nicholas C. and Christen, Andreas and Gurtuna, Ozgur and Prevot, Arthur
Solar Energy 86 (10) 2923-2934
- Lidar calibration and validation for geometric-optical modeling with Landsat imagery (2012)
Chen, Gang and Wulder, Michael A. and White, Joanne C. and Hilker, Thomas and Coops, Nicholas C.
Remote Sensing of Environment 124 384-393
- Lidar plots - a new large-area data collection option: context, concepts, and case study (2012)
Wulder, Michael A. and White, Joanne C. and Bater, Christopher W. and Coops, Nicholas C. and Hopkinson, Chris and Chen, Gang
Canadian Journal of Remote Sensing 38 (5) 600-618
- Lidar sampling for large-area forest characterization: A review (2012)
Wulder, Michael A. and White, Joanne C. and Nelson, Ross F. and Naesset, Erik and Orka, Hans Ole and Coops, Nicholas C. and Hilker, Thomas and Bater, Christopher W. and Gobakken, Terje
Remote Sensing of Environment 121 196-209
- Linking ground-based to satellite-derived phenological metrics in support of habitat assessment (2012)
Coops, Nicholas C. and Hilker, Thomas and Bater, Christopher W. and Wulder, Michael A. and Nielsen, Scott E. and McDermid, Greg and Stenhouse, Gordon
Remote Sensing Letters 3 (3) 191-200
- Modeling lodgepole and jack pine vulnerability to mountain pine beetle expansion into the western Canadian boreal forest (2012)
Coops, Nicholas C. and Wulder, Michael A. and Waring, Richard H.
Forest Ecology and Management 274 161-171
- Modelling the ecosystem indicators of British Columbia using Earth observation data and terrain indices (2012)
Fitterer, Jessica L. and Nelson, Trisalyn A. and Coops, Nicholas C. and Wulder, Michael A.
Ecological Indicators 20 151-162
- Prediction of soil properties using a process-based forest growth model to match satellite-derived estimates of leaf area index (2012)
Coops, Nicholas C. and Waring, Richard H. and Hilker, Thomas
Remote Sensing of Environment 126 160-173
- Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest (2012)
Tsui, Olivier W. and Coops, Nicholas C. and Wulder, Michael A. and Marshall, Peter L. and McCardle, Adrian
Isprs Journal of Photogrammetry and Remote Sensing 69 121-133
- A process-based approach to estimate lodgepole pine (Pinus contorta Dougl.) distribution in the Pacific Northwest under climate change (2011)
Coops, Nicholas C. and Waring, Richard H.
Climatic Change 105 (1-2) 313-328
- Assessing eddy-covariance flux tower location bias across the Fluxnet-Canada Research Network based on remote sensing and footprint modelling (2011)
Chen, Baozhang and Coops, Nicholas C. and Fu, Dongjie and Margolis, Hank A. and Amiro, Brian D. and Barr, Alan G. and Black, T. Andrew and Arain, M. Altaf and Bourque, Charles P-A and Flanagan, Lawrence B. and Lafleur, Peter M. and McCaughey, J. Harry and Wofsy, Steven C.
Agricultural and Forest Meteorology 151 (1) 87-100
- Assessment of standing wood and fiber quality using ground and airborne laser scanning: A review (2011)
van Leeuwen, Martin and Hilker, Thomas and Coops, Nicholas C. and Frazer, Gordon and Wulder, Michael A. and Newnham, Glenn J. and Culvenor, Darius S.
Forest Ecology and Management 261 (9) 1467-1478
- Biweekly disturbance capture and attribution: case study in western Alberta grizzly bear habitat (2011)
Hilker, Thomas and Coops, Nicholas C. and Gaulton, Rachel and Wulder, Michael A. and Cranston, Jerome and Stenhouse, Gordon
Journal of Applied Remote Sensing 5
- Characterizing stand-replacing disturbance in western Alberta grizzly bear habitat, using a satellite-derived high temporal and spatial resolution change sequence (2011)
Gaulton, Rachel and Hilker, Thomas and Wulder, Michael A. and Coops, Nicholas C. and Stenhouse, Gordon
Forest Ecology and Management 261 (4) 865-877
- Comparing the impacts of mitigation and non-mitigation on mountain pine beetle populations (2011)
Coggins, Sam B. and Coops, Nicholas C. and Wulder, Michael A. and Bater, Christopher W. and Ortlepp, Stephanie M.
Journal of Environmental Management 92 (1) 112-120
- Comparison of a regional-level habitat index derived from MERIS and MODIS estimates of canopy-absorbed photosynthetically active radiation (2011)
Coops, Nicholas C. and Michaud, Jean-Simon and Andrew, Margaret E. and Wulder, Michael A.
Remote Sensing Letters 2 (4) 327-336
- DESIGN AND INSTALLATION OF A CAMERA NETWORK ACROSS AN ELEVATION GRADIENT FOR HABITAT ASSESSMENT (2011)
Bater, Christopher W. and Coops, Nicholas C. and Wulder, Michael A. and Nielsen, Scott E. and McDermid, Greg and Stenhouse, Gordon B.
Instrumentation Science & Technology 39 (3) 231-247
- Determination of ecosystem carbon-stock distributions in the flux footprint of an eddy-covariance tower in a coastal forest in British Columbia (2011)
Ferster, Colin J. and Trofymow, J. A. (Tony) and Coops, Nicholas C. and Chen, Baozhang and Black, T. Andrew and Gougeon, Francois A.
Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 41 (7) 1380-1393
- Estimates of bark beetle infestation expansion factors with adaptive cluster sampling (2011)
Coggins, Sam B. and Coops, Nicholas C. and Wulder, Michael A.
International Journal of Pest Management 57 (1) 11-21
- Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America (2011)
Coops, Nicholas C. and Waring, Richard H.
Ecological Modelling 222 (13) 2119-2129
- Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison (2011)
Wang, Z. and Grant, R. F. and Arain, M. A. and Chen, B. N. and Coops, N. and Hember, R. and Kurz, W. A. and Price, D. T. and Stinson, G. and Trofymow, J. A. and Yeluripati, J. and Chen, Z.
Ecological Modelling 222 (17) 3236-3249
- Exploring the Utility of Hyperspectral Imagery and LiDAR Data for Predicting Quercus garryana Ecosystem Distribution and Aiding in Habitat Restoration (2011)
Jones, Trevor G. and Coops, Nicholas C. and Sharma, Tara
Restoration Ecology 19 245-256
- Fragmentation regimes of Canada's forests (2011)
Wulder, Michael A. and White, Joanne C. and Coops, Nicholas C.
Canadian Geographer-Geographe Canadien 55 (3) 288-300
- How do butterflies define ecosystems? A comparison of ecological regionalization schemes (2011)
Andrew, Margaret E. and Wulder, Michael A. and Coops, Nicholas C.
Biological Conservation 144 (5) 1409-1418
- Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space (2011)
Hilker, Thomas and Coops, Nicholas C. and Hall, Forrest G. and Nichol, Caroline J. and Lyapustin, Alexei and Black, T. Andrew and Wulder, Michael A. and Leuning, Ray and Barr, Alan and Hollinger, David Y. and Munger, Bill and Tucker, Compton J.
Journal of Geophysical Research-Biogeosciences 116
- Landscape Controls on Structural Variation in Eucalypt Vegetation Communities: Woronora Plateau, Australia (2011)
Jenkins, Ross B. and Coops, Nicholas C.
Australian Geographer 42 (1) 1-17
- Mapping site indices for five Pacific Northwest conifers using a physiologically based model (2011)
Coops, Nicholas C. and Gaulton, Rachel and Waring, Richard H.
Applied Vegetation Science 14 (2) 268-276
- Modeling the occurrence of 15 coniferous tree species throughout the Pacific Northwest of North America using a hybrid approach of a generic process-based growth model and decision tree analysis (2011)
Coops, Nicholas C. and Waring, Richard H. and Beier, Clayton and Roy-Jauvin, Raphael and Wang, Tongli
Applied Vegetation Science 14 (3) 402-414
- Modeling to discern nitrogen fertilization impacts on carbon sequestration in a Pacific Northwest Douglas-fir forest in the first-postfertilization year (2011)
Chen, Baozhang and Coops, Nicholas C. and Black, T. Andy and Jassal, Rachhpals S. and Chen, Jing M. and Johnson, Mark
Global Change Biology 17 (3) 1442-1460
- Patterns of protection and threats along productivity gradients in Canada (2011)
Andrew, Margaret E. and Wulder, Michael A. and Coops, Nicholas C.
Biological Conservation 144 (12) 2891-2901
- PHOTOSYNSAT, photosynthesis from space: Theoretical foundations of a satellite concept and validation from tower and spaceborne data (2011)
Hall, Forrest G. and Hilker, Thomas and Coops, Nicholas C.
Remote Sensing of Environment 115 (8) 1918-1925
- Predicting satellite-derived patterns of large-scale disturbances in forests of the Pacific Northwest Region in response to recent climatic variation (2011)
Waring, Richard H. and Coops, Nicholas C. and Running, Steven W.
Remote Sensing of Environment 115 (12) 3554-3566
- Stability of Sample-Based Scanning-LiDAR-Derived Vegetation Metrics for Forest Monitoring (2011)
Bater, Christopher W. and Wulder, Michael A. and Coops, Nicholas C. and Nelson, Ross F. and Hilker, Thomas and Naesset, Erik
Ieee Transactions on Geoscience and Remote Sensing 49 (6) 2385-2392
- The transferability of a dNBR-derived model to predict burn severity across 10 wildland fires in western Canada (2011)
Soverel, Nicholas O. and Coops, Nicholas C. and Perrakis, Daniel D. B. and Daniels, Lori D. and Gergel, Sarah E.
International Journal of Wildland Fire 20 (4) 518-531
- Tracking plant physiological properties from multi-angular tower-based remote sensing (2011)
Hilker, Thomas and Gitelson, Anatoly and Coops, Nicholas C. and Hall, Forrest G. and Black, T. Andrew
Oecologia 165 (4) 865-876
- Tree structure influences on rooftop-received solar radiation (2011)
Tooke, Thoreau Rory and Coops, Nicholas C. and Voogt, James A. and Meitner, Michael J.
Landscape and Urban Planning 102 (2) 73-81
- Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment (2011)
Bater, Christopher W. and Coops, Nicholas C. and Wulder, Michael A. and Hilker, Thomas and Nielsen, Scott E. and McDermid, Greg and Stenhouse, Gordon B.
Environmental Monitoring and Assessment 180 (1-4) 1-13
- Validation of modeled carbon-dioxide emissions from an urban neighborhood with direct eddy-covariance measurements (2011)
Christen, A. and Coops, N. C. and Crawford, B. R. and Kellett, R. and Liss, K. N. and Olchovski, I. and Tooke, T. R. and van der Laan, M. and Voogt, J. A.
Atmospheric Environment 45 (33) 6057-6069
- A geographical approach to identifying vegetation-related environmental equity in Canadian cities (2010)
Tooke, Thoreau R. and Klinkenberg, Brian and Coops, Nicholas C.
Environment and Planning B-Planning & Design 37 (6) 1040-1056
- A New Low-Cost, Stand-Alone Sensor System for Snow Monitoring (2010)
Varhola, Andres and Wawerla, Jens and Weiler, Markus and Coops, Nicholas C. and Bewley, Daniel and Alila, Younes
Journal of Atmospheric and Oceanic Technology 27 (12) 1973-1978
- A NEW, AUTOMATED, MULTIANGULAR RADIOMETER INSTRUMENT FOR TOWER-BASED OBSERVATIONS OF CANOPY REFLECTANCE (AMSPEC II) (2010)
Hilker, Thomas and Nesic, Zoran and Coops, Nicholas C. and Lessard, Dominic
Instrumentation Science & Technology 38 (5) 319-340
- A Provincial and Regional Assessment of the Mountain Pine Beetle Epidemic in British Columbia: 1999-2008 (2010)
Wulder, M. A. and Ortlepp, S. M. and White, J. C. and Nelson, T. and Coops, N. C.
Journal of Environmental Informatics 15 (1) 1-13
- Aerial Photography: A Rapidly Evolving Tool for Ecological Management (2010)
Morgan, Jessica L. and Gergel, Sarah E. and Coops, Nicholas C.
Bioscience 60 (1) 47-59
- Assessing changes in forest fragmentation following infestation using time series Landsat imagery (2010)
Coops, Nicholas C. and Gillanders, Steve N. and Wulder, Michael A. and Gergel, Sarah E. and Nelson, Trisalyn and Goodwin, Nicholas R.
Forest Ecology and Management 259 (12) 2355-2365
- Assessing the impact of current and projected climates on Douglas-Fir productivity in British Columbia, Canada, using a process-based model (3-PG) (2010)
Coops, Nicholas C. and Hember, Robbie A. and Waring, Richard H.
Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 40 (3) 511-524
- Assessing the utility of airborne hyperspectral and LiDAR data for species distribution mapping in the coastal Pacific Northwest, Canada (2010)
Jones, Trevor G. and Coops, Nicholas C. and Sharma, Tara
Remote Sensing of Environment 114 (12) 2841-2852
- Assessing the utility of lidar remote sensing technology to identify mule deer winter habitat (2010)
Coops, Nicholas C. and Duffe, Jason and Koot, Cathy
Canadian Journal of Remote Sensing 36 (2) 81-88
- Canopy surface reconstruction from a LiDAR point cloud using Hough transform (2010)
Van Leeuwen, Martin and Coops, Nicholas C. and Wulder, Michael A.
Remote Sensing Letters 1 (3) 125-132
- Characterizing temperate forest structural and spectral diversity with Hyperion EO-1 data (2010)
White, Joanne C. and Gomez, Cristina and Wulder, Michael A. and Coops, Nicholas C.
Remote Sensing of Environment 114 (7) 1576-1589
- Characterizing the forest fragmentation of Canada's national parks (2010)
Soverel, Nicholas O. and Coops, Nicholas C. and White, Joanne C. and Wulder, Michael A.
Environmental Monitoring and Assessment 164 (1-4) 481-499
- Comparing canopy metrics derived from terrestrial and airborne laser scanning in a Douglas-fir dominated forest stand (2010)
Hilker, Thomas and van Leeuwen, Martin and Coops, Nicholas C. and Wulder, Michael A. and Newnham, Glenn J. and Jupp, David L. B. and Culvenor, Darius S.
Trees-Structure and Function 24 (5) 819-832
- Curve fitting of time-series Landsat imagery for characterizing a mountain pine beetle infestation (2010)
Goodwin, Nicholas R. and Magnussen, Steen and Coops, Nicholas C. and Wulder, Michael A.
International Journal of Remote Sensing 31 (12) 3263-3271
- Employing ground-based spectroscopy for tree-species differentiation in the Gulf Islands National Park Reserve (2010)
Jones, Trevor G. and Coops, Nicholas C. and Sharma, Tara
International Journal of Remote Sensing 31 (4) 1121-1127
- Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada (2010)
Soverel, Nicholas O. and Perrakis, Daniel D. B. and Coops, Nicholas C.
Remote Sensing of Environment 114 (9) 1896-1909
- Estimating the reduction in gross primary production due to mountain pine beetle infestation using satellite observations (2010)
Coops, Nicholas C. and Wulder, Michael A.
International Journal of Remote Sensing 31 (8) 2129-2138
- Estimation of Light-use Efficiency of Terrestrial Ecosystem from Space: A Status Report (2010)
Coops, Nicholas C. and Hilker, Thomas and Hall, Forrest G. and Nichol, Caroline J. and Drolet, Guillaume G.
Bioscience 60 (10) 788-797
- Forest canopy effects on snow accumulation and ablation: An integrative review of empirical results (2010)
Varhola, Andres and Coops, Nicholas C. and Weiler, Markus and Moore, R. Dan
Journal of Hydrology 392 (3-4) 219-233
- Implications of differing input data sources and approaches upon forest carbon stock estimation (2010)
Wulder, Michael A. and White, Jo