Mapping with height and spectral remote sensing implies that environment and forest structure jointly constrain tree community composition in temperate coniferous forests of eastern Washington, United States

Maps of species composition are important for assessing a wide range of ecosystem functions in forested landscapes, including processes shaping community structure at broader (e.g., climate) and finer (e.g., disturbance) scales. Incorporating recently available remotely sensed datasets has the poten...

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Published in:Frontiers in Forests and Global Change Vol. 5; p. 962816
Main Authors: Bell, David M., Gregory, Matthew J., Churchill, Derek J., Smith, Annie C.
Format: Journal Article
Language:English
Published: Lausanne Frontiers Media SA 22.11.2022
Frontiers Media S.A
Subjects:
Abundance
Accuracy
Aerial photography
Climate change
Community composition
Community structure
Composition
Coniferous forests
Coniferous trees
digital aerial photogrammetry (DAP)
Ecological function
Environmental factors
Environmental gradient
Forest management
forest mapping
Forests
Landsat satellites
Mapping
nearest neighbor imputation
Photogrammetry
Plant species
Relative abundance
Remote sensing
Satellite imagery
Satellite photography
Sentinel-2
Species composition
Temperate forests
Topography
tree community
Vegetation mapping
United States > US
ISSN:2624-893X, 2624-893X
Online Access:Get full text
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Abstract Maps of species composition are important for assessing a wide range of ecosystem functions in forested landscapes, including processes shaping community structure at broader (e.g., climate) and finer (e.g., disturbance) scales. Incorporating recently available remotely sensed datasets has the potential to improve species composition mapping by providing information to help predict species presence and relative abundance. Using USDA Forest Service Forest Inventory and Analysis plot data and the gradient nearest neighbor imputation modeling approach in eastern Washington, USA, we developed tree species composition and structure maps based on climate, topography, and two sources of remote sensing: height from digital aerial photogrammetry (DAP) of pushbroom aerial photography and Sentinel-2 multispectral satellite imagery. We tested the accuracy of these maps based on their capacity to predict species occurrence and proportional basal area for 10 coniferous tree species. In this study region, climate, topography, and location explained much of the species occurrence patterns, while both DAP and Sentinel-2 data were also important in predicting species proportional basal area. Overall accuracies for the best species occurrence model were 68–92% and R 2 for the proportional basal area was 0.08–0.55. Comparisons of model accuracy with and without remote sensing indicated that adding some combination of DAP metrics and/or Sentinel-2 imagery increased R 2 for the proportional basal area by 0.25–0.45, but had minor and sometimes negative effects on model skill and accuracy for species occurrence. Thus, species ranges appear most strongly constrained by environmental gradients, but abundance depends on forest structure, which is often determined by both environment and disturbance history. For example, proportional basal area responses to moisture limitation and canopy height varied by species, likely contributing to regional patterns of species dominance. However, local-scale examples indicated that remotely sensed forest structures representing recent disturbance patterns likely impacted tree community composition. Overall, our results suggest that characterizing geospatial patterns in tree communities across large landscapes may require not only environmental factors like climate and topography, but also information on forest structure provided by remote sensing.
AbstractList Maps of species composition are important for assessing a wide range of ecosystem functions in forested landscapes, including processes shaping community structure at broader (e.g., climate) and finer (e.g., disturbance) scales. Incorporating recently available remotely sensed datasets has the potential to improve species composition mapping by providing information to help predict species presence and relative abundance. Using USDA Forest Service Forest Inventory and Analysis plot data and the gradient nearest neighbor imputation modeling approach in eastern Washington, USA, we developed tree species composition and structure maps based on climate, topography, and two sources of remote sensing: height from digital aerial photogrammetry (DAP) of pushbroom aerial photography and Sentinel-2 multispectral satellite imagery. We tested the accuracy of these maps based on their capacity to predict species occurrence and proportional basal area for 10 coniferous tree species. In this study region, climate, topography, and location explained much of the species occurrence patterns, while both DAP and Sentinel-2 data were also important in predicting species proportional basal area. Overall accuracies for the best species occurrence model were 68–92% and R2 for the proportional basal area was 0.08–0.55. Comparisons of model accuracy with and without remote sensing indicated that adding some combination of DAP metrics and/or Sentinel-2 imagery increased R2 for the proportional basal area by 0.25–0.45, but had minor and sometimes negative effects on model skill and accuracy for species occurrence. Thus, species ranges appear most strongly constrained by environmental gradients, but abundance depends on forest structure, which is often determined by both environment and disturbance history. For example, proportional basal area responses to moisture limitation and canopy height varied by species, likely contributing to regional patterns of species dominance. However, local-scale examples indicated that remotely sensed forest structures representing recent disturbance patterns likely impacted tree community composition. Overall, our results suggest that characterizing geospatial patterns in tree communities across large landscapes may require not only environmental factors like climate and topography, but also information on forest structure provided by remote sensing.
Maps of species composition are important for assessing a wide range of ecosystem functions in forested landscapes, including processes shaping community structure at broader (e.g., climate) and finer (e.g., disturbance) scales. Incorporating recently available remotely sensed datasets has the potential to improve species composition mapping by providing information to help predict species presence and relative abundance. Using USDA Forest Service Forest Inventory and Analysis plot data and the gradient nearest neighbor imputation modeling approach in eastern Washington, USA, we developed tree species composition and structure maps based on climate, topography, and two sources of remote sensing: height from digital aerial photogrammetry (DAP) of pushbroom aerial photography and Sentinel-2 multispectral satellite imagery. We tested the accuracy of these maps based on their capacity to predict species occurrence and proportional basal area for 10 coniferous tree species. In this study region, climate, topography, and location explained much of the species occurrence patterns, while both DAP and Sentinel-2 data were also important in predicting species proportional basal area. Overall accuracies for the best species occurrence model were 68–92% and R 2 for the proportional basal area was 0.08–0.55. Comparisons of model accuracy with and without remote sensing indicated that adding some combination of DAP metrics and/or Sentinel-2 imagery increased R 2 for the proportional basal area by 0.25–0.45, but had minor and sometimes negative effects on model skill and accuracy for species occurrence. Thus, species ranges appear most strongly constrained by environmental gradients, but abundance depends on forest structure, which is often determined by both environment and disturbance history. For example, proportional basal area responses to moisture limitation and canopy height varied by species, likely contributing to regional patterns of species dominance. However, local-scale examples indicated that remotely sensed forest structures representing recent disturbance patterns likely impacted tree community composition. Overall, our results suggest that characterizing geospatial patterns in tree communities across large landscapes may require not only environmental factors like climate and topography, but also information on forest structure provided by remote sensing.
Author Bell, David M.
Smith, Annie C.
Gregory, Matthew J.
Churchill, Derek J.
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Cites_doi 10.1016/j.rse.2013.08.048
10.1890/ES11-00114.1
10.1016/j.ecolmodel.2011.03.033
10.1139/X10-024
10.1890/ES15-00203.1
10.1007/s10980-015-0218-0
10.1007/s10980-016-0414-6
10.1016/j.foreco.2021.119764
10.1016/j.rse.2016.08.013
10.1890/13-1015.1
10.2307/1938672
10.1890/ES11-00345.1
10.1016/j.foreco.2021.120004
10.1007/s10980-012-9703-x
10.1109/TGRS.1984.350619
10.3390/rs11080929
10.1016/j.foreco.2016.04.051
10.1016/j.jag.2021.102318
10.1002/ecs2.2108
10.1126/science.1128834
10.1016/j.rse.2016.01.017
10.1111/j.1654-1103.2010.01244.x
10.1016/j.rse.2013.12.013
10.1016/j.foreco.2020.118554
10.1016/j.rse.2015.11.024
10.1111/j.1365-2699.2009.02268.x
10.1139/cjfr-2017-0346
10.3390/rs14143433
10.1002/ecm.1241
10.1111/gcb.12026
10.1111/j.1365-2664.2006.01214.x
10.1002/eap.2433
10.1007/s00442-016-3792-1
10.3390/rs13214297
10.1016/j.foreco.2017.05.017
10.1038/s41586-022-04959-9
10.1007/s40725-019-00087-2
10.1007/978-0-387-77318-6
10.1016/j.tplants.2014.10.008
10.1139/X10-064
10.1002/ecs2.1472
10.3390/rs5126481
10.3390/rs11101197
10.1016/j.rse.2019.111535
10.1086/507711
10.3390/f6103704
10.1016/j.rse.2018.02.064
10.1890/10-0312.1
10.1016/0034-4257(80)90044-9
10.1139/cjfr-2013-0401
10.1139/x02-011
10.1016/j.rse.2018.11.012
10.3390/rs9070659
10.1016/j.foreco.2014.09.014
10.1016/j.foreco.2018.10.041
10.1016/j.rse.2019.01.019
10.1111/ele.13568
10.1111/j.2007.0906-7590.05171.x
10.1890/130066
10.1080/02827581.2012.686625
10.1111/ddi.12125
10.1016/j.foreco.2006.01.014
10.1002/ecs2.1424
10.1016/j.isprsjprs.2018.01.006
10.1126/science.aaa9933
10.1098/rstb.2015.0178
10.1016/j.rse.2007.03.032
10.1111/j.1365-2664.2007.01348.x
10.1080/01431160121472
10.3955/046.092.0104
10.3390/rs12040610
10.1111/j.1539-6924.2006.00707.x
10.1038/nclimate1693
10.1002/ecs2.2838
10.1109/JSTARS.2019.2938388
10.1016/0034-4257(92)90056-P
10.1016/j.rse.2009.12.018
10.1016/j.foreco.2012.02.002
10.1080/07038992.2016.1207484
10.1641/0006-3568(2004)054[0535:LRIEAO]2.0.CO;2
10.1186/1750-0680-8-1
10.1016/j.foreco.2017.11.004
10.1016/j.rse.2006.09.034
10.1890/1051-0761(2007)017[0018:IOEDAO]2.0.CO;2
10.1016/j.foreco.2015.03.016
10.2737/PNW-GTR-911
10.1111/j.2006.0906-7590.04596.x
10.1088/1748-9326/aa9d9e
10.1371/journal.pone.0156720
10.1002/rse2.7
10.1111/2041-210X.12180
10.1073/pnas.1617464114
10.1016/j.rse.2017.06.031
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References McGaughey (B62) 2016
Ter Braak (B86) 1986; 67
Beaudoin (B10) 2014; 44
Laurin (B56) 2016; 176
Walsh (B89) 1980; 9
Kennedy (B52) 2014; 12
Westerling (B92) 2016; 371
Ohmann (B69) 2014; 151
Fassnacht (B33) 2016; 186
Franklin (B37) 2013; 19
Shi (B82) 2019; 12
Thompson (B87) 2020; 23
Stohlgren (B83) 2006; 26
Elith (B32) 2006; 29
Gorelick (B41) 2017; 202
Strunk (B85) 2020; 237
Allen (B3) 2015; 6
Canham (B17) 2010; 91
Strunk (B84) 2022; 14
Wilson (B97) 2018; 137
Ohmann (B70) 2007; 17
Dobrowski (B29) 2013; 19
Hoscilo (B48) 2019; 11
Battles (B9) 2018
Malcolm (B60) 2021; 13
(B77) 2020
Kolb (B55) 2016; 380
Ohmann (B68) 2002; 32
DeMeo (B28) 2018; 92
Powell (B74) 2010; 114
Chastain (B19) 2019; 221
Millar (B65) 2015; 349
Burns (B15) 1990
Henderson (B46) 2019; 10
Mildrexler (B64) 2016; 173
Duveneck (B31) 2015; 347
Rehfeldt (B78) 2006; 167
Axelsson (B7) 2021; 100
Coops (B25) 2011; 222
Goodbody (B40) 2019; 5
Pasquarella (B72) 2018; 210
Davis (B27) 2015
Kane (B50); 40
Williams (B96) 2012; 3
Zhang (B101) 2018; 48
Crist (B26) 1984; 22
Prichard (B75) 2021; 31
Ohmann (B71) 2011; 22
Westerling (B93) 2006; 313
Wilson (B98) 2012; 271
Forzieri (B36) 2022; 7923
Puletti (B76) 2018; 42
Cohen (B22) 2004; 54
Cohen (B24) 2001; 22
Hall (B43) 2006; 225
Gesch (B38) 2007
Flood (B34) 2013; 5
Savage (B80) 2017; 399
Kennedy (B53) 2018; 13
Kleiber (B54) 2008
Aubin (B6) 2018; 9
Schoennagel (B81) 2017; 114
Haugo (B44) 2015; 335
Pollock (B73) 2014; 5
Brown (B14) 2017; 183
Dormann (B30) 2007; 30
McRoberts (B63) 2007; 110
Flood (B35) 2017; 9
Tomppo (B88) 2008; 112
Hessburg (B47) 2015; 30
Kane (B51); 40
Adams (B1) 2020; 12
Moritz (B66) 2012; 3
Loehman (B58) 2017; 32
Allouche (B4) 2006; 43
Clark (B21) 2017; 87
Lutz (B59) 2010; 37
White (B95) 2015; 6
Astola (B5) 2019; 223
Zimmermann (B102) 2007; 44
Bohlin (B13) 2012; 27
Gesch (B39) 2002; 68
Cansler (B18) 2022; 504
Littell (B57) 2011; 2
Grabska (B42) 2019; 11
Wang (B90) 2016; 11
Agne (B2) 2018; 409
(B91) 2020
Canham (B16) 2016; 7
Isaacson (B49) 2012; 27
North (B67) 2022; 507
Bell (B12) 2021; 479
Cohen (B23) 1992; 41
He (B45) 2015; 1
White (B94) 2016; 42
Riley (B79) 2016; 7
Barros (B8) 2019; 433
Wilson (B99) 2013; 8
McDowell (B61) 2015; 20
Bechtold (B11) 2005
Clark (B20) 2014; 24
Zald (B100) 2014; 143
References_xml – volume: 151
  start-page: 3
  year: 2014
  ident: B69
  article-title: Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2013.08.048
– volume: 2
  start-page: art102
  year: 2011
  ident: B57
  article-title: Managing uncertainty in climate-driven ecological models to inform adaptation to climate change.
  publication-title: Ecosphere
  doi: 10.1890/ES11-00114.1
– volume: 42
  start-page: 32
  year: 2018
  ident: B76
  article-title: Use of Sentinel-2 for forest classification in Mediterranean environments.
  publication-title: Ann. Silvic. Res.
– volume: 222
  start-page: 2119
  year: 2011
  ident: B25
  article-title: Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America.
  publication-title: Ecol. Model.
  doi: 10.1016/j.ecolmodel.2011.03.033
– volume: 40
  start-page: 761
  ident: B51
  article-title: Comparisons between field- and LiDAR-based measures of stand structural complexity.
  publication-title: Canad. J. For. Res.
  doi: 10.1139/X10-024
– volume: 6
  start-page: 129
  year: 2015
  ident: B3
  article-title: On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene.
  publication-title: Ecosphere
  doi: 10.1890/ES15-00203.1
– year: 1990
  ident: B15
  article-title: Silvics of North America
  publication-title: Agriculture Handbook 654
– volume: 30
  start-page: 1805
  year: 2015
  ident: B47
  article-title: Restoring fire-prone Inland Pacific landscapes: seven core principles.
  publication-title: Landscape Ecol.
  doi: 10.1007/s10980-015-0218-0
– volume: 32
  start-page: 1447
  year: 2017
  ident: B58
  article-title: Interactions of landscape disturbances and climate change dictate ecological pattern and process: spatial modeling of wildfire, insect, and disease dynamics under future climates.
  publication-title: Landscape Ecol.
  doi: 10.1007/s10980-016-0414-6
– volume: 504
  start-page: 119764
  year: 2022
  ident: B18
  article-title: Previous wildfires and management treatments moderate subsequent fire severity.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2021.119764
– volume: 186
  start-page: 64
  year: 2016
  ident: B33
  article-title: Review of studies on tree species classification from remotely sensed data.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2016.08.013
– volume: 24
  start-page: 990
  year: 2014
  ident: B20
  article-title: More than the sum of the parts: forest climate response from joint species distribution models.
  publication-title: Ecol. Appl.
  doi: 10.1890/13-1015.1
– volume: 67
  start-page: 1167
  year: 1986
  ident: B86
  article-title: Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis.
  publication-title: Ecology
  doi: 10.2307/1938672
– volume: 3
  start-page: 1
  year: 2012
  ident: B66
  article-title: Climate change and disruptions to global fire activity.
  publication-title: Ecosphere
  doi: 10.1890/ES11-00345.1
– volume: 507
  start-page: 120004
  year: 2022
  ident: B67
  article-title: Operational resilience in western US frequent-fire forests.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2021.120004
– volume: 27
  start-page: 529
  year: 2012
  ident: B49
  article-title: Detection of relative differences in phenology of forest species using Landsat and MODIS.
  publication-title: Landscape Ecol.
  doi: 10.1007/s10980-012-9703-x
– volume: 22
  start-page: 256
  year: 1984
  ident: B26
  article-title: A physically-based transformation of Thematic Mapper data — The TM Tasseled Cap.
  publication-title: IEEE Trans. Geosci. Remote Sens.
  doi: 10.1109/TGRS.1984.350619
– volume: 11
  start-page: 929
  year: 2019
  ident: B48
  article-title: Mapping forest type and tree species on a regional scale using multi-temporal sentinel-2 data.
  publication-title: Remote Sens.
  doi: 10.3390/rs11080929
– volume: 380
  start-page: 321
  year: 2016
  ident: B55
  article-title: Observed and anticipated impacts of drought on forest insects and diseases in the United States.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2016.04.051
– volume: 100
  start-page: 102318
  year: 2021
  ident: B7
  article-title: Tree species classification using Sentinel-2 imagery and Bayesian inference.
  publication-title: Int J Appl. Earth Obs. Geoinf.
  doi: 10.1016/j.jag.2021.102318
– volume: 9
  start-page: e02108
  year: 2018
  ident: B6
  article-title: Tree vulnerability to climate change: improving exposure-based assessments using traits as indicators of sensitivity.
  publication-title: Ecosphere
  doi: 10.1002/ecs2.2108
– volume: 313
  start-page: 940
  year: 2006
  ident: B93
  article-title: Warming and earlier spring increase Western U.S. forest wildfire activity.
  publication-title: Science
  doi: 10.1126/science.1128834
– volume: 176
  start-page: 163
  year: 2016
  ident: B56
  article-title: Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2016.01.017
– volume: 22
  start-page: 660
  year: 2011
  ident: B71
  article-title: Mapping gradients of community composition with nearest-neighbour imputation: extending plot data for landscape analysis.
  publication-title: J. Veg. Sci.
  doi: 10.1111/j.1654-1103.2010.01244.x
– volume: 143
  start-page: 26
  year: 2014
  ident: B100
  article-title: Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2013.12.013
– volume: 479
  start-page: 118554
  year: 2021
  ident: B12
  article-title: Quantifying regional trends in large live tree and snag availability in support of forest management.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2020.118554
– volume: 173
  start-page: 314
  year: 2016
  ident: B64
  article-title: A forest vulnerability index based on drought and high temperatures.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2015.11.024
– volume: 37
  start-page: 936
  year: 2010
  ident: B59
  article-title: Climatic water deficit, tree species ranges, and climate change in Yosemite National Park.
  publication-title: J. Biogeogra.
  doi: 10.1111/j.1365-2699.2009.02268.x
– volume: 48
  start-page: 461
  year: 2018
  ident: B101
  article-title: Integrating forest inventory data and MODIS data to map species-level biomass in chinese boreal forests.
  publication-title: Canad. J. For. Res.
  doi: 10.1139/cjfr-2017-0346
– volume: 14
  start-page: 3433
  year: 2022
  ident: B84
  article-title: Pushbroom photogrammetric heights enhance state-level forest attribute mapping with landsat and environmental gradients.
  publication-title: Remote Sens.
  doi: 10.3390/rs14143433
– volume: 87
  start-page: 34
  year: 2017
  ident: B21
  article-title: Generalized joint attribute modeling for biodiversity analysis: median-zero, multivariate, multifarious data.
  publication-title: Ecol. Monogra.
  doi: 10.1002/ecm.1241
– volume: 19
  start-page: 241
  year: 2013
  ident: B29
  article-title: The climate velocity of the contiguous United States during the 20th century.
  publication-title: Glob. Change Biol.
  doi: 10.1111/gcb.12026
– volume: 43
  start-page: 1223
  year: 2006
  ident: B4
  article-title: Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS).
  publication-title: J. Appl. Ecol.
  doi: 10.1111/j.1365-2664.2006.01214.x
– volume: 31
  start-page: e02433
  year: 2021
  ident: B75
  article-title: Adapting western North American forests to climate change and wildfires: 10 common questions.
  publication-title: Ecol. Appl.
  doi: 10.1002/eap.2433
– volume: 183
  start-page: 643
  year: 2017
  ident: B14
  article-title: Making sense of metacommunities: dispelling the mythology of a metacommunity typology.
  publication-title: Oecologia
  doi: 10.1007/s00442-016-3792-1
– volume: 13
  start-page: 4297
  year: 2021
  ident: B60
  article-title: Use of Sentinel-2 Data to Improve Multivariate Tree Species Composition in a Forest Resource Inventory.
  publication-title: Remote Sens.
  doi: 10.3390/rs13214297
– volume: 399
  start-page: 9
  year: 2017
  ident: B80
  article-title: Mapping post-disturbance forest landscape composition with Landsat satellite imagery.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2017.05.017
– volume: 7923
  start-page: 534
  year: 2022
  ident: B36
  article-title: Emerging signals of declining forest resilience under climate change.
  publication-title: Nature
  doi: 10.1038/s41586-022-04959-9
– volume: 5
  start-page: 55
  year: 2019
  ident: B40
  article-title: Digital aerial photogrammetry for updating area-based forest inventories: A review of opportunities, challenges, and future directions.
  publication-title: Curr. For. Rep.
  doi: 10.1007/s40725-019-00087-2
– year: 2008
  ident: B54
  publication-title: Applied Econometrics with R.
  doi: 10.1007/978-0-387-77318-6
– volume: 20
  start-page: 114
  year: 2015
  ident: B61
  article-title: Global satellite monitoring of climate-induced vegetation disturbances.
  publication-title: Trends Plant Sci.
  doi: 10.1016/j.tplants.2014.10.008
– year: 2018
  ident: B9
  article-title: Innovations in measuring and manageing forest carbon stocks in California
  publication-title: A report for California’s Fourth Climate Change Assessment. CCCA4-CNRA-2018-014
– volume: 40
  start-page: 774
  ident: B50
  article-title: Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data.
  publication-title: Canad. J. For. Res.
  doi: 10.1139/X10-064
– volume: 7
  start-page: e01472
  year: 2016
  ident: B79
  article-title: Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots.
  publication-title: Ecosphere
  doi: 10.1002/ecs2.1472
– volume: 5
  start-page: 6481
  year: 2013
  ident: B34
  article-title: Seasonal composite landsat TM/ETM+ images using the medoid (a Multi-Dimensional Median).
  publication-title: Remote Sens.
  doi: 10.3390/rs5126481
– volume: 11
  start-page: 1197
  year: 2019
  ident: B42
  article-title: Forest stand species mapping using the sentinel-2 time series.
  publication-title: Remote Sens.
  doi: 10.3390/rs11101197
– volume: 237
  start-page: 111535
  year: 2020
  ident: B85
  article-title: Evaluation of pushbroom DAP relative to frame camera DAP and lidar for forest modeling.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2019.111535
– volume: 167
  start-page: 1123
  year: 2006
  ident: B78
  article-title: Empirical analyses of plant-climate relationships for the Western United States.
  publication-title: Int. J. Plant Sci.
  doi: 10.1086/507711
– volume: 6
  start-page: 3704
  year: 2015
  ident: B95
  article-title: Comparing ALS and image-based point cloud metrics and modelled forest inventory attributes in a complex coastal forest environment.
  publication-title: Forests
  doi: 10.3390/f6103704
– volume: 210
  start-page: 193
  year: 2018
  ident: B72
  article-title: Improved mapping of forest type using spectral-temporal Landsat features.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2018.02.064
– volume: 91
  start-page: 3433
  year: 2010
  ident: B17
  article-title: Frequency, not relative abundance, of temperate tree species varies along climate gradients in eastern North America.
  publication-title: Ecology
  doi: 10.1890/10-0312.1
– volume: 9
  start-page: 11
  year: 1980
  ident: B89
  article-title: Coniferous tree species mapping using LANDSAT data.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/0034-4257(80)90044-9
– year: 2007
  ident: B38
  article-title: The national elevation dataset. Pages 99–118
  publication-title: Digital elevational model technologies and applications: The DEM Users Manual
– volume: 44
  start-page: 521
  year: 2014
  ident: B10
  article-title: Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery.
  publication-title: Canad. J. For. Res.
  doi: 10.1139/cjfr-2013-0401
– volume: 32
  start-page: 725
  year: 2002
  ident: B68
  article-title: Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A.
  publication-title: Canad. J. For. Res.
  doi: 10.1139/x02-011
– volume: 221
  start-page: 274
  year: 2019
  ident: B19
  article-title: Empirical cross sensor comparison of Sentinel-2A and 2B MSI, Landsat-8 OLI, and Landsat-7 ETM+ top of atmosphere spectral characteristics over the conterminous United States.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2018.11.012
– volume: 9
  start-page: 659
  year: 2017
  ident: B35
  article-title: Comparing Sentinel-2A and Landsat 7 and 8 Using Surface Reflectance over Australia.
  publication-title: Remote Sens.
  doi: 10.3390/rs9070659
– volume: 335
  start-page: 37
  year: 2015
  ident: B44
  article-title: A new approach to evaluate forest structure restoration needs across Oregon and Washington, USA.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2014.09.014
– volume: 433
  start-page: 514
  year: 2019
  ident: B8
  article-title: Improving long-term fuel treatment effectiveness in the National Forest System through quantitative prioritization.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2018.10.041
– volume: 223
  start-page: 257
  year: 2019
  ident: B5
  article-title: Comparison of sentinel-2 and landsat 8 imagery for forest variable prediction in boreal region.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2019.01.019
– volume: 23
  start-page: 1314
  year: 2020
  ident: B87
  article-title: A process-based metacommunity framework linking local and regional scale community ecology.
  publication-title: Ecol. Lett.
  doi: 10.1111/ele.13568
– volume: 30
  start-page: 609
  year: 2007
  ident: B30
  article-title: Methods to account for spatial autocorrelation in the analysis of species distributional data: a review.
  publication-title: Ecography
  doi: 10.1111/j.2007.0906-7590.05171.x
– volume: 12
  start-page: 339
  year: 2014
  ident: B52
  article-title: Bringing an ecological view of change to Landsat-based remote sensing.
  publication-title: Front. Ecol. Environ.
  doi: 10.1890/130066
– volume: 27
  start-page: 692
  year: 2012
  ident: B13
  article-title: Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM.
  publication-title: Scand. J. For. Res.
  doi: 10.1080/02827581.2012.686625
– volume: 19
  start-page: 1217
  year: 2013
  ident: B37
  article-title: Species distribution models in conservation biogeography: developments and challenges.
  publication-title: Divers. Distrib.
  doi: 10.1111/ddi.12125
– volume: 225
  start-page: 378
  year: 2006
  ident: B43
  article-title: Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2006.01.014
– volume: 7
  start-page: e01424
  year: 2016
  ident: B16
  article-title: The demography of tree species response to climate: Seedling recruitment and survival.
  publication-title: Ecosphere
  doi: 10.1002/ecs2.1424
– volume: 137
  start-page: 29
  year: 2018
  ident: B97
  article-title: Harmonic regression of Landsat time series for modeling attributes from national forest inventory data.
  publication-title: ISPRS J. Photogramm. Remote Sens.
  doi: 10.1016/j.isprsjprs.2018.01.006
– volume: 349
  start-page: 823
  year: 2015
  ident: B65
  article-title: Temperate forest health in an era of emerging megadisturbance.
  publication-title: Science
  doi: 10.1126/science.aaa9933
– volume: 371
  start-page: 20150178
  year: 2016
  ident: B92
  article-title: Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring.
  publication-title: Philos. Trans. R. Soc. B: Biol. Sci.
  doi: 10.1098/rstb.2015.0178
– volume: 112
  start-page: 1982
  year: 2008
  ident: B88
  article-title: Combining national forest inventory field plots and remote sensing data for forest databases.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2007.03.032
– volume: 44
  start-page: 1057
  year: 2007
  ident: B102
  article-title: Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah.
  publication-title: J. Appl. Ecol.
  doi: 10.1111/j.1365-2664.2007.01348.x
– volume: 22
  start-page: 2279
  year: 2001
  ident: B24
  article-title: Modelling forest cover attributes as continuous variables in a regional context with Thematic Mapper data.
  publication-title: Int. J. Remote Sens.
  doi: 10.1080/01431160121472
– volume: 92
  start-page: 18
  year: 2018
  ident: B28
  article-title: Expanding our understanding of forest structural restoration needs in the pacific northwest.
  publication-title: Northwest Sci.
  doi: 10.3955/046.092.0104
– volume: 12
  start-page: 610
  year: 2020
  ident: B1
  article-title: Mapping forest composition with landsat time series: An evaluation of seasonal composites and harmonic regression.
  publication-title: Remote Sensing
  doi: 10.3390/rs12040610
– volume: 26
  start-page: 163
  year: 2006
  ident: B83
  article-title: Risk analysis for biological hazards: What we need to know about invasive species.
  publication-title: Risk Anal.
  doi: 10.1111/j.1539-6924.2006.00707.x
– volume: 3
  start-page: 292
  year: 2012
  ident: B96
  article-title: Temperature as a potent driver of regional forest drought stress and tree mortality.
  publication-title: Nat. Clim. Change
  doi: 10.1038/nclimate1693
– volume: 10
  start-page: e02838
  year: 2019
  ident: B46
  article-title: Vegetation mapping to support greater sage-grouse habitat monitoring and management: multi- or univariate approach?
  publication-title: Ecosphere
  doi: 10.1002/ecs2.2838
– volume: 12
  start-page: 4038
  year: 2019
  ident: B82
  article-title: Derivation of Tasseled Cap Transformation Coefficients for Sentinel-2 MSI At-Sensor Reflectance Data.
  publication-title: IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.
  doi: 10.1109/JSTARS.2019.2938388
– year: 2020
  ident: B77
  publication-title: R: A language and environment for statistical computing
– volume: 41
  start-page: 1
  year: 1992
  ident: B23
  article-title: Estimating structural attributes of Douglas-fir/western hemlock forest stands from landsat and SPOT imagery.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/0034-4257(92)90056-P
– volume: 114
  start-page: 1053
  year: 2010
  ident: B74
  article-title: Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2009.12.018
– volume: 271
  start-page: 182
  year: 2012
  ident: B98
  article-title: A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2012.02.002
– volume: 42
  start-page: 619
  year: 2016
  ident: B94
  article-title: Remote sensing technologies for enhancing forest inventories: A review.
  publication-title: Canad. J. Remote Sens.
  doi: 10.1080/07038992.2016.1207484
– volume: 54
  start-page: 535
  year: 2004
  ident: B22
  article-title: Landsat’s role in ecological applications of remote sensing.
  publication-title: BioScience
  doi: 10.1641/0006-3568(2004)054[0535:LRIEAO]2.0.CO;2
– volume: 8
  start-page: 1
  year: 2013
  ident: B99
  article-title: Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage.
  publication-title: Carbon Balance Manag.
  doi: 10.1186/1750-0680-8-1
– volume: 409
  start-page: 317
  year: 2018
  ident: B2
  article-title: Interactions of predominant insects and diseases with climate change in Douglas-fir forests of western Oregon and Washington, U.S.A.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2017.11.004
– volume: 110
  start-page: 412
  year: 2007
  ident: B63
  article-title: Remote sensing support for national forest inventories.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2006.09.034
– volume: 17
  start-page: 18
  year: 2007
  ident: B70
  article-title: Influence of environment, disturbance, and ownership on forest vegetation of coastal Oregon.
  publication-title: Ecol. Appl.
  doi: 10.1890/1051-0761(2007)017[0018:IOEDAO]2.0.CO;2
– start-page: 85
  year: 2005
  ident: B11
  publication-title: The enhanced forest inventory and analysis program — national sampling design and estimation procedures. general tehcnical report SRS-GTR-80.
– volume: 347
  start-page: 107
  year: 2015
  ident: B31
  article-title: An imputed forest composition map for New England screened by species range boundaries.
  publication-title: For. Ecol. Manag.
  doi: 10.1016/j.foreco.2015.03.016
– start-page: 112
  year: 2015
  ident: B27
  publication-title: Northwest Forest Plan–the first 20 years (1994-2013): status and trends of late-successional and old-growth forests. General Technical Report PNW-GTR-911.
  doi: 10.2737/PNW-GTR-911
– volume: 29
  start-page: 129
  year: 2006
  ident: B32
  article-title: Novel methods improve prediction of species’ distributions from occurrence data.
  publication-title: Ecography
  doi: 10.1111/j.2006.0906-7590.04596.x
– volume: 13
  start-page: 41001
  year: 2018
  ident: B53
  article-title: An empirical, integrated forest biomass monitoring system.
  publication-title: Environ. Res. Lett.
  doi: 10.1088/1748-9326/aa9d9e
– volume: 11
  start-page: e0156720
  year: 2016
  ident: B90
  article-title: Locally downscaled and spatially customizable climate data for historical and future periods for North America.
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0156720
– year: 2016
  ident: B62
  publication-title: FUSION / LDV : Software for LIDAR Data Analysis and Visualization, FUSION
– volume: 1
  start-page: 4
  year: 2015
  ident: B45
  article-title: Will remote sensing shape the next generation of species distribution models?
  publication-title: Remote Sens. Ecol. Conserv.
  doi: 10.1002/rse2.7
– volume: 5
  start-page: 397
  year: 2014
  ident: B73
  article-title: Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM).
  publication-title: Methods Ecol. Evol.
  doi: 10.1111/2041-210X.12180
– volume: 114
  start-page: 4582
  year: 2017
  ident: B81
  article-title: Adapt to more wildfire in western North American forests as climate changes.
  publication-title: Proc. Natl Acad. Sci. U. S. A.
  doi: 10.1073/pnas.1617464114
– volume: 202
  start-page: 18
  year: 2017
  ident: B41
  article-title: Google Earth Engine: Planetary-scale geospatial analysis for everyone.
  publication-title: Remote Sens. Environ.
  doi: 10.1016/j.rse.2017.06.031
– volume: 68
  start-page: 5
  year: 2002
  ident: B39
  article-title: The national elevation dataset.
  publication-title: Photogramm. Eng. Remote Sens.
– year: 2020
  ident: B91
  publication-title: Forest health assessment and treatment framework (RCW 76.06.200).
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Snippet Maps of species composition are important for assessing a wide range of ecosystem functions in forested landscapes, including processes shaping community...
SourceID doaj
proquest
crossref
SourceType Open Website
Aggregation Database
Index Database
StartPage 962816
SubjectTerms Abundance
Accuracy
Aerial photography
Climate change
Community composition
Community structure
Composition
Coniferous forests
Coniferous trees
digital aerial photogrammetry (DAP)
Ecological function
Environmental factors
Environmental gradient
Forest management
forest mapping
Forests
Landsat satellites
Mapping
nearest neighbor imputation
Photogrammetry
Plant species
Relative abundance
Remote sensing
Satellite imagery
Satellite photography
Sentinel-2
Species composition
Temperate forests
Topography
tree community
Vegetation mapping
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Title Mapping with height and spectral remote sensing implies that environment and forest structure jointly constrain tree community composition in temperate coniferous forests of eastern Washington, United States
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Volume 5
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