Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and...Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.展开更多
The Asia-Pacific(AP)region has experienced faster warming than the global average in recent decades and has experienced more climate extremes,however little is known about the response of vegetation growth to these ch...The Asia-Pacific(AP)region has experienced faster warming than the global average in recent decades and has experienced more climate extremes,however little is known about the response of vegetation growth to these changes.The updated Global Inventory Modeling and Mapping Studies third-generation global satellite Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index dataset and gridded reanalysis climate data were used to investigate the spatiotemporal changes in both trends of vegetation dynamic indicators and climatic variables.We then further analyzed their relations associated with land cover across the AP region.The main findings are threefold:(1)at continental scales the AP region overall experienced a gradual and significant increasing trend in vegetation growth during the last three decades,and this NDVI trend corresponded with an insignificant increasing trend in temperature;(2)vegetation growth was negatively and significantly correlated with the Pacific Decadal Oscillation index and the El Niño/Southern Oscillation(ENSO)in AP;and(3)at pixel scales,except for Australia,both vegetation growth and air temperature significantly increased in the majority of study regions and vegetation growth spatially correlated with temperature;In Australia and other water-limited regions vegetation growth positively correlated with precipitation.展开更多
Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects.Herein,we summarize a project characterizing the change history of Canada’s forested e...Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects.Herein,we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984-2012.Using the Composite2Change approach,we applied spectral trend analysis to annual best-available-pixel(BAP)surface reflectance image composites produced from Landsat TM and ETM+imagery.A total of 73,544 images were used to produce 29 annual image composites,generating∼400 TB of interim data products and resulting in∼25 TB of annual gap-free reflectance composites and change products.On average,10%of pixels in the annual BAP composites were missing data,with 86%of pixels having data gaps in two consecutive years or fewer.Change detection overall accuracy was 89%.Change attribution overall accuracy was 92%,with higher accuracy for standreplacing wildfire and harvest.Changes were assigned to the correct year with an accuracy of 89%.Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested ecosystems.The methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.展开更多
Volunteered data sources are readily available due to advances in electronic communications technology.For example,smartphones provide tools to collect ground-based observations over broad areas from a diverse set of ...Volunteered data sources are readily available due to advances in electronic communications technology.For example,smartphones provide tools to collect ground-based observations over broad areas from a diverse set of data collectors,including people with,and without,extensive training.In this study,volunteers used a smartphone application to collect ground-based observations.Forest structural components were then estimated over a broader area using high spatial resolution RapidEye remote sensing imagery(5 spectral bands 440–850 nm,5 m spatial resolution)and a digital elevation model following a three nearest neighbor approach(K-NN).Participants with professional forestry experience on average chose highpriority fuel load locations near buildings,while nonprofessional participants chose a broader range of conditions over a larger extent.When used together,the professional and nonprofessional observations provided a more complete assessment of forest conditions.A generalized framework is presented that utilizes K-NN imputation tools for estimating the distribution of forest fuels using remote sensing and topography variables,ensuring spatial representation,checking attribute accuracy,and evaluating predictor variables.Frameworks to integrate volunteered data from smartphone platforms with remote sensing may contribute toward more complete Earth observation for Digital Earth.展开更多
Aims Canopy height is a key driver of forest biodiversity and carbon cycling.Accurate estimates of canopy height are needed for assess-ing mechanisms relating to ecological patterns and processes of tree height limita...Aims Canopy height is a key driver of forest biodiversity and carbon cycling.Accurate estimates of canopy height are needed for assess-ing mechanisms relating to ecological patterns and processes of tree height limitations.At global scales forest canopy height patterns are largely controlled by climate,while local variation at fine scales is due to differences in disturbance history and local patterns in envir-onmental conditions.The relative effect of local environmental driv-ers on canopy height is poorly understood partly due to gaps in data on canopy height and methods for examining limiting factors.Here,we used airborne laser scanning(ALS)data on vegetation structure of boreal forests to examine the effects of environmental factors on potential maximum forest canopy height.Methods Relationships between maximum canopy height from ALS meas-ures and environmental variables were examined to assess factors limiting tree height.Specifically,we used quantile regression at the 0.90 quantile to relate maximum canopy height with environmental characteristics of climate(i.e.mean annual temperature[MAT]and mean annual precipitation),terrain(i.e.slope)and depth-to-water(DTW)across a 33000 km2 multiple use boreal forest landscape in northeast Alberta,Canada.Important Findings Maximum canopy height was positively associated with MAT,ter-rain slope and terrain-derived DTW,collectively explaining 33.2%of the variation in heights.The strongest explanatory variable was DTW explaining 26%of canopy height variation with peatland forests having naturally shorter maximum canopy heights,but also more sites currently at their maximum potential height.In con-trast,the most productive forests(i.e.mesic to xeric upland forests)had the fewest sites at their potential maximum height,illustrating the effects of long-term forest management,wildfires and general anthropogenic footprints on reducing the extent and abundance of older,taller forest habitat in Alberta’s boreal forest.展开更多
Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper...Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper,we characterized the historical space–time relationships between climate and a suite of indirect indicators of biodiversity,known as the Dynamic Habitat Index(DHI)to identify where climate variability is co-occurring with changes in biodiversity indicators.We represented biodiversity using three indirect indicators generated from 1987 to 2007 National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer images.By quantifying and clustering temporal variability in climate data,we defined eight homogeneous climate variability zones,where we then analyzed the DHI.Results identified unique areas of change in climate,such as the Hudson Plains,that explain significant variations in DHI.Past variability in temperatures and growing season index had a strong influence on observed vegetation productivity and seasonality changes throughout Canada’s boreal.Variation in precipitation,for most of the area,was not associated with DHI changes.The methodology presented here enables assessment of spatial–temporal relationships between biodiversity and climate variability and characterizes distinctive zones of variation that may be used for prioritization and planning to ensure long-term biodiversity conservation in Canada.展开更多
Free and open access to the Landsat archive has enabled the detection and delineation of an unprecedented number of fire events across the globe.Despite the availability and potential of these data,few studies have an...Free and open access to the Landsat archive has enabled the detection and delineation of an unprecedented number of fire events across the globe.Despite the availability and potential of these data,few studies have analysed residual vegetation patterns and/or partial mortality of fire across the Canadian boreal forest,and those available,are either incomplete or inaccurate.Further,they all differ in the methods and spatial language,which makes it difficult for managers to interpret fire patterns over large areas.There is an urgent need for methods to help unify fire pattern observations across the Canadian boreal forest.This study explores the capacity of the Landsat data archive when coupled with a recently developed fire mapping approach and a robust spatial language to characterize and compare tree mortality patterns across the boreal plains ecozone,Canada.With 507 fires 2.5 Mha mapped,this study represents the most comprehensive analysis of mortality patterns for study area.Summaries from this demonstration generated an accurate characterization of the fire patterns the various ecoregions based on seven key fire metrics.The comparison between ecoregions revealed differences in the amount of residual vegetation,which in turn suggested various climate,topography and/or vegetation ecosystem drivers.展开更多
文摘Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.
基金supported by a research grant(41271116)funded by the National Science Foundation of China and a research grant(2013BAC03B04)+2 种基金National Key Technology Support Program and a research grant(2012ZD010)the Key Project for the Strategic Science Plan in Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences(CAS)Jiangsu Provincial‘double creation’program.
文摘The Asia-Pacific(AP)region has experienced faster warming than the global average in recent decades and has experienced more climate extremes,however little is known about the response of vegetation growth to these changes.The updated Global Inventory Modeling and Mapping Studies third-generation global satellite Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index dataset and gridded reanalysis climate data were used to investigate the spatiotemporal changes in both trends of vegetation dynamic indicators and climatic variables.We then further analyzed their relations associated with land cover across the AP region.The main findings are threefold:(1)at continental scales the AP region overall experienced a gradual and significant increasing trend in vegetation growth during the last three decades,and this NDVI trend corresponded with an insignificant increasing trend in temperature;(2)vegetation growth was negatively and significantly correlated with the Pacific Decadal Oscillation index and the El Niño/Southern Oscillation(ENSO)in AP;and(3)at pixel scales,except for Australia,both vegetation growth and air temperature significantly increased in the majority of study regions and vegetation growth spatially correlated with temperature;In Australia and other water-limited regions vegetation growth positively correlated with precipitation.
文摘Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects.Herein,we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984-2012.Using the Composite2Change approach,we applied spectral trend analysis to annual best-available-pixel(BAP)surface reflectance image composites produced from Landsat TM and ETM+imagery.A total of 73,544 images were used to produce 29 annual image composites,generating∼400 TB of interim data products and resulting in∼25 TB of annual gap-free reflectance composites and change products.On average,10%of pixels in the annual BAP composites were missing data,with 86%of pixels having data gaps in two consecutive years or fewer.Change detection overall accuracy was 89%.Change attribution overall accuracy was 92%,with higher accuracy for standreplacing wildfire and harvest.Changes were assigned to the correct year with an accuracy of 89%.Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested ecosystems.The methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.
基金National Science and Engineering Research Council(NSERC)Discovery grant to Coops and a NSERC Engage to Ferster,Coops,and Valhallaunder University of British Columbia ethics application H12-00257.
文摘Volunteered data sources are readily available due to advances in electronic communications technology.For example,smartphones provide tools to collect ground-based observations over broad areas from a diverse set of data collectors,including people with,and without,extensive training.In this study,volunteers used a smartphone application to collect ground-based observations.Forest structural components were then estimated over a broader area using high spatial resolution RapidEye remote sensing imagery(5 spectral bands 440–850 nm,5 m spatial resolution)and a digital elevation model following a three nearest neighbor approach(K-NN).Participants with professional forestry experience on average chose highpriority fuel load locations near buildings,while nonprofessional participants chose a broader range of conditions over a larger extent.When used together,the professional and nonprofessional observations provided a more complete assessment of forest conditions.A generalized framework is presented that utilizes K-NN imputation tools for estimating the distribution of forest fuels using remote sensing and topography variables,ensuring spatial representation,checking attribute accuracy,and evaluating predictor variables.Frameworks to integrate volunteered data from smartphone platforms with remote sensing may contribute toward more complete Earth observation for Digital Earth.
文摘Aims Canopy height is a key driver of forest biodiversity and carbon cycling.Accurate estimates of canopy height are needed for assess-ing mechanisms relating to ecological patterns and processes of tree height limitations.At global scales forest canopy height patterns are largely controlled by climate,while local variation at fine scales is due to differences in disturbance history and local patterns in envir-onmental conditions.The relative effect of local environmental driv-ers on canopy height is poorly understood partly due to gaps in data on canopy height and methods for examining limiting factors.Here,we used airborne laser scanning(ALS)data on vegetation structure of boreal forests to examine the effects of environmental factors on potential maximum forest canopy height.Methods Relationships between maximum canopy height from ALS meas-ures and environmental variables were examined to assess factors limiting tree height.Specifically,we used quantile regression at the 0.90 quantile to relate maximum canopy height with environmental characteristics of climate(i.e.mean annual temperature[MAT]and mean annual precipitation),terrain(i.e.slope)and depth-to-water(DTW)across a 33000 km2 multiple use boreal forest landscape in northeast Alberta,Canada.Important Findings Maximum canopy height was positively associated with MAT,ter-rain slope and terrain-derived DTW,collectively explaining 33.2%of the variation in heights.The strongest explanatory variable was DTW explaining 26%of canopy height variation with peatland forests having naturally shorter maximum canopy heights,but also more sites currently at their maximum potential height.In con-trast,the most productive forests(i.e.mesic to xeric upland forests)had the fewest sites at their potential maximum height,illustrating the effects of long-term forest management,wildfires and general anthropogenic footprints on reducing the extent and abundance of older,taller forest habitat in Alberta’s boreal forest.
基金This research was supported by GEOIDE(GEOmatics for Informed DEcisions)the Ivey Foundationand the Canada Program of The Nature Conservancy.The project was conducted at the universities of British Columbia and Victoria,and was undertaken as an extension of the‘BioSpace:Biodiversity monitoring with Earth Observation data’project jointly funded by the Canadian Space Agency(CSA)Government Related Initiatives Program(GRIP),Canadian Forest Service(CFS)Pacific Forestry Centre(PFC),and the University of British Columbia(UBC).We thank Chuck Rumsey,Steve Cumming,Kim Lisgo,Pierre Vernier,Ryan Powers and Fiona Schmiege low for support and engaging discussions throughout the project.
文摘Climate drives ecosystem processes and impacts biodiversity.Biodiversity patterns over large areas,such as Canada’s boreal,can be monitored using indirect indicators derived from remotely sensed imagery.In this paper,we characterized the historical space–time relationships between climate and a suite of indirect indicators of biodiversity,known as the Dynamic Habitat Index(DHI)to identify where climate variability is co-occurring with changes in biodiversity indicators.We represented biodiversity using three indirect indicators generated from 1987 to 2007 National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer images.By quantifying and clustering temporal variability in climate data,we defined eight homogeneous climate variability zones,where we then analyzed the DHI.Results identified unique areas of change in climate,such as the Hudson Plains,that explain significant variations in DHI.Past variability in temperatures and growing season index had a strong influence on observed vegetation productivity and seasonality changes throughout Canada’s boreal.Variation in precipitation,for most of the area,was not associated with DHI changes.The methodology presented here enables assessment of spatial–temporal relationships between biodiversity and climate variability and characterizes distinctive zones of variation that may be used for prioritization and planning to ensure long-term biodiversity conservation in Canada.
基金Saskatchewan Environment,fRI Research Healthy Landscapes Program,the government of the Northwest Territories,Bandaloop Landscape-Ecosystem Services,and an NSERC Discovery and Engage grant to Coops(RGPIN 311926-13 and EGP 503226-16).
文摘Free and open access to the Landsat archive has enabled the detection and delineation of an unprecedented number of fire events across the globe.Despite the availability and potential of these data,few studies have analysed residual vegetation patterns and/or partial mortality of fire across the Canadian boreal forest,and those available,are either incomplete or inaccurate.Further,they all differ in the methods and spatial language,which makes it difficult for managers to interpret fire patterns over large areas.There is an urgent need for methods to help unify fire pattern observations across the Canadian boreal forest.This study explores the capacity of the Landsat data archive when coupled with a recently developed fire mapping approach and a robust spatial language to characterize and compare tree mortality patterns across the boreal plains ecozone,Canada.With 507 fires 2.5 Mha mapped,this study represents the most comprehensive analysis of mortality patterns for study area.Summaries from this demonstration generated an accurate characterization of the fire patterns the various ecoregions based on seven key fire metrics.The comparison between ecoregions revealed differences in the amount of residual vegetation,which in turn suggested various climate,topography and/or vegetation ecosystem drivers.
