Mapping global forest canopy height through integration of GEDI and Landsat data
Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard...
Gespeichert in:
| Veröffentlicht in: | Remote sensing of environment Jg. 253; S. 112165 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Elsevier Inc
01.02.2021
Elsevier BV |
| Schlagworte: | |
| ISSN: | 0034-4257, 1879-0704 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R2 = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R2 = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives. |
|---|---|
| AbstractList | Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R² = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R² = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives. Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R2 = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R2 = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives. Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R2 = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R2 = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives. |
| ArticleNumber | 112165 |
| Author | Dubayah, Ralph Tyukavina, Alexandra Hofton, Michelle Hansen, Matthew C. Hernandez-Serna, Andres Tang, Hao Potapov, Peter Silva, Carlos Edibaldo Li, Xinyuan Armston, John Turubanova, Svetlana Blair, J. Bryan Kommareddy, Anil Pickens, Amy |
| Author_xml | – sequence: 1 givenname: Peter surname: Potapov fullname: Potapov, Peter email: potapov@umd.edu organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 2 givenname: Xinyuan surname: Li fullname: Li, Xinyuan organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 3 givenname: Andres surname: Hernandez-Serna fullname: Hernandez-Serna, Andres organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 4 givenname: Alexandra surname: Tyukavina fullname: Tyukavina, Alexandra organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 5 givenname: Matthew C. surname: Hansen fullname: Hansen, Matthew C. organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 6 givenname: Anil surname: Kommareddy fullname: Kommareddy, Anil organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 7 givenname: Amy surname: Pickens fullname: Pickens, Amy organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 8 givenname: Svetlana surname: Turubanova fullname: Turubanova, Svetlana organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 9 givenname: Hao surname: Tang fullname: Tang, Hao organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 10 givenname: Carlos Edibaldo surname: Silva fullname: Silva, Carlos Edibaldo organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 11 givenname: John surname: Armston fullname: Armston, John organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 12 givenname: Ralph surname: Dubayah fullname: Dubayah, Ralph organization: Department of Geographical Sciences, University of Maryland, United States – sequence: 13 givenname: J. Bryan surname: Blair fullname: Blair, J. Bryan organization: NASA Goddard Space Flight Center, United States – sequence: 14 givenname: Michelle surname: Hofton fullname: Hofton, Michelle organization: Department of Geographical Sciences, University of Maryland, United States |
| BookMark | eNp9kLFOwzAQhi0EEm3hAdgssbCk2I5Tx2JCpZRKRTDAbDnOJXUV7GC7SLw9KWXqwHKnk_7v9Osbo1PnHSB0RcmUEjq73U5DhCkjbLgpo7PiBI1oKWRGBOGnaERIzjPOCnGOxjFuCaFFKegIvT7rvreuxW3nK93hxgeICRvtfP-NN2DbTcJpE_yu3WDrErRBJ-sd9g1eLh5WWLsar4cRdcK1TvoCnTW6i3D5tyfo_XHxNn_K1i_L1fx-nRnOeMqgIKYqBC8p52Ut6hy0FHlFZpKyhrBaV5WUUnPCNQOagyylkZWsG9YIATnJJ-jm8LcP_nM3dFYfNhroOu3A76JiRUFlLqjcR6-Polu_C25opxgvS8YFp7MhRQ8pE3yMARrVB_uhw7eiRO0dq60aHKu9Y3VwPDDiiDE2_fpJQdvuX_LuQMLg6MtCUNFYcAZqG8AkVXv7D_0DtOKWsg |
| CitedBy_id | crossref_primary_10_1016_j_jag_2025_104614 crossref_primary_10_7717_peerj_15478 crossref_primary_10_1016_j_ecolind_2024_112895 crossref_primary_10_1016_j_rse_2023_113745 crossref_primary_10_3390_rs14092096 crossref_primary_10_3390_rs17101726 crossref_primary_10_1139_cjfr_2023_0118 crossref_primary_10_1016_j_jnc_2024_126771 crossref_primary_10_1038_s41467_023_37880_4 crossref_primary_10_1080_10095020_2023_2249037 crossref_primary_10_1016_j_fecs_2025_100372 crossref_primary_10_1088_1748_9326_ad5572 crossref_primary_10_1016_j_jag_2025_104850 crossref_primary_10_1029_2024WR038926 crossref_primary_10_1016_j_jhydrol_2025_134000 crossref_primary_10_1007_s13253_024_00600_6 crossref_primary_10_1016_j_cub_2025_05_016 crossref_primary_10_1016_j_foreco_2024_121879 crossref_primary_10_3390_f16030432 crossref_primary_10_1016_j_actatropica_2024_107286 crossref_primary_10_1016_j_scs_2025_106756 crossref_primary_10_1016_j_srs_2025_100195 crossref_primary_10_1080_10095020_2025_2555385 crossref_primary_10_1029_2025GH001451 crossref_primary_10_1093_ornithapp_duaf041 crossref_primary_10_1111_2041_210X_14401 crossref_primary_10_3390_rs17101733 crossref_primary_10_1007_s10712_024_09833_z crossref_primary_10_1016_j_rse_2025_115008 crossref_primary_10_3390_rs15081969 crossref_primary_10_1016_j_rse_2023_113985 crossref_primary_10_1109_JSTARS_2024_3425431 crossref_primary_10_1016_j_rse_2022_113103 crossref_primary_10_1109_TGRS_2023_3318084 crossref_primary_10_3390_rs12244042 crossref_primary_10_4236_gep_2025_135010 crossref_primary_10_3390_f13050689 crossref_primary_10_3390_rs14164112 crossref_primary_10_3390_s24041106 crossref_primary_10_3390_rs15102522 crossref_primary_10_1002_rse2_257 crossref_primary_10_1134_S1067413624602008 crossref_primary_10_21425_fob_18_145498 crossref_primary_10_1016_j_jag_2024_104348 crossref_primary_10_5194_essd_17_1835_2025 crossref_primary_10_1088_2752_664X_ad39f2 crossref_primary_10_5194_essd_16_5267_2024 crossref_primary_10_1007_s42965_023_00317_6 crossref_primary_10_1111_1365_2664_14858 crossref_primary_10_1016_j_uclim_2024_102114 crossref_primary_10_1111_oik_10554 crossref_primary_10_3390_rs14061364 crossref_primary_10_1088_1748_9326_ac358c crossref_primary_10_1016_j_jag_2022_102840 crossref_primary_10_1109_LGRS_2024_3390136 crossref_primary_10_3390_rs14174287 crossref_primary_10_3390_ani12141794 crossref_primary_10_59717_j_xinn_geo_2023_100015 crossref_primary_10_3390_f12091211 crossref_primary_10_3390_rs14143401 crossref_primary_10_1038_s41598_023_50838_2 crossref_primary_10_1016_j_ecoinf_2022_101665 crossref_primary_10_1080_07038992_2024_2351004 crossref_primary_10_1073_pnas_2504685122 crossref_primary_10_3389_fenvs_2025_1641301 crossref_primary_10_1073_pnas_2304988120 crossref_primary_10_1016_j_actaastro_2023_09_040 crossref_primary_10_1038_s41598_025_95207_3 crossref_primary_10_3390_rs15225352 crossref_primary_10_1007_s40725_024_00223_7 crossref_primary_10_1038_s43247_025_02609_2 crossref_primary_10_1111_avsc_70002 crossref_primary_10_1038_s43247_023_00896_1 crossref_primary_10_1111_gcb_16847 crossref_primary_10_5194_essd_14_3835_2022 crossref_primary_10_3390_rs14092079 crossref_primary_10_1080_17538947_2025_2556239 crossref_primary_10_1088_1748_9326_adb506 crossref_primary_10_1080_15481603_2025_2517922 crossref_primary_10_1016_j_rse_2023_113888 crossref_primary_10_1007_s41748_025_00713_z crossref_primary_10_1016_j_rse_2023_113648 crossref_primary_10_1038_s41598_023_30560_9 crossref_primary_10_1029_2020GL092149 crossref_primary_10_1088_2752_664X_adb850 crossref_primary_10_1109_JSTARS_2025_3567505 crossref_primary_10_3390_f16030457 crossref_primary_10_1038_s41597_025_04610_y crossref_primary_10_1038_s41597_023_02383_w crossref_primary_10_1016_j_crsus_2025_100343 crossref_primary_10_1016_j_scs_2025_106659 crossref_primary_10_1134_S0010952523700661 crossref_primary_10_1016_j_agrformet_2025_110784 crossref_primary_10_1029_2024GL111634 crossref_primary_10_1016_j_pecon_2024_04_002 crossref_primary_10_1021_acs_est_4c14275 crossref_primary_10_1038_s41558_025_02411_0 crossref_primary_10_1016_j_jag_2025_104700 crossref_primary_10_1016_j_jag_2025_104704 crossref_primary_10_5194_tc_18_575_2024 crossref_primary_10_1017_ext_2025_5 crossref_primary_10_1038_s41598_024_71133_8 crossref_primary_10_3390_rs15123107 crossref_primary_10_1038_s41598_025_06814_z crossref_primary_10_1016_j_jag_2024_104123 crossref_primary_10_3390_rs14153540 crossref_primary_10_1111_phor_12507 crossref_primary_10_3390_f12101374 crossref_primary_10_3390_rs16081389 crossref_primary_10_1109_TGRS_2025_3572524 crossref_primary_10_3390_f15071132 crossref_primary_10_1016_j_geomorph_2025_109962 crossref_primary_10_1111_1365_2664_14830 crossref_primary_10_1016_j_foreco_2022_120075 crossref_primary_10_1071_WF24224 crossref_primary_10_1109_JSTARS_2024_3461843 crossref_primary_10_3390_rs13122279 crossref_primary_10_1016_j_jenvman_2023_120005 crossref_primary_10_3390_rs13183777 crossref_primary_10_1080_10095020_2023_2286377 crossref_primary_10_1111_cobi_14135 crossref_primary_10_3390_rs15020375 crossref_primary_10_1038_s41597_024_04143_w crossref_primary_10_1080_00049158_2021_2004687 crossref_primary_10_3389_ffgc_2022_769917 crossref_primary_10_1016_j_uclim_2024_102201 crossref_primary_10_1080_01431161_2024_2343429 crossref_primary_10_3390_rs14174354 crossref_primary_10_1038_s41598_022_21412_z crossref_primary_10_1080_10106049_2022_2153930 crossref_primary_10_1016_j_biocon_2025_111114 crossref_primary_10_1109_TGRS_2025_3571000 crossref_primary_10_5194_pb_11_31_2024 crossref_primary_10_1080_21580103_2025_2481122 crossref_primary_10_1134_S0010952523700569 crossref_primary_10_1016_j_biocon_2023_110425 crossref_primary_10_1016_j_tfp_2024_100751 crossref_primary_10_1088_1748_9326_ac583f crossref_primary_10_1109_JSTARS_2024_3486737 crossref_primary_10_3390_rs14143330 crossref_primary_10_11626_KJEB_2024_42_2_193 crossref_primary_10_1016_j_jag_2025_104766 crossref_primary_10_1029_2023GL105588 crossref_primary_10_3390_su14137895 crossref_primary_10_3390_land11010028 crossref_primary_10_3390_rs13244961 crossref_primary_10_1016_j_isprsjprs_2024_12_018 crossref_primary_10_3390_f14061098 crossref_primary_10_1109_TGRS_2023_3333391 crossref_primary_10_1111_gcb_70166 crossref_primary_10_1016_j_oneear_2023_10_007 crossref_primary_10_1016_j_tfp_2024_100763 crossref_primary_10_3390_genes14030746 crossref_primary_10_1016_j_rse_2022_113392 crossref_primary_10_1088_1748_9326_ac4657 crossref_primary_10_1029_2023GB008016 crossref_primary_10_1088_1748_9326_ad661a crossref_primary_10_1016_j_rse_2022_113391 crossref_primary_10_1134_S0001433824700890 crossref_primary_10_1007_s10661_023_10942_2 crossref_primary_10_1016_j_agrformet_2025_110612 crossref_primary_10_3389_fmars_2023_1187702 crossref_primary_10_34248_bsengineering_1695801 crossref_primary_10_1029_2022EF002880 crossref_primary_10_3390_f12010008 crossref_primary_10_3390_rs17172945 crossref_primary_10_1016_j_fecs_2024_100196 crossref_primary_10_5194_essd_15_1465_2023 crossref_primary_10_3390_rs12213482 crossref_primary_10_1109_JSTARS_2023_3298991 crossref_primary_10_1016_j_jag_2025_104633 crossref_primary_10_1016_j_jag_2025_104753 crossref_primary_10_3390_f14101966 crossref_primary_10_1088_2752_664X_adaaf9 crossref_primary_10_3390_rs15204969 crossref_primary_10_1007_s10980_025_02145_6 crossref_primary_10_1109_TGRS_2023_3335364 crossref_primary_10_1186_s13595_025_01293_8 crossref_primary_10_1016_j_landurbplan_2025_105396 crossref_primary_10_1016_j_foreco_2024_121852 crossref_primary_10_1088_1748_9326_ada972 crossref_primary_10_1016_j_rse_2022_113367 crossref_primary_10_1016_j_rse_2022_113003 crossref_primary_10_1111_acv_12904 crossref_primary_10_1111_ddi_13644 crossref_primary_10_3390_f15122064 crossref_primary_10_3390_rs15020467 crossref_primary_10_1007_s12145_022_00915_3 crossref_primary_10_3390_rs15041028 crossref_primary_10_1109_TGRS_2025_3538216 crossref_primary_10_1016_j_envsoft_2024_106268 crossref_primary_10_1109_TGRS_2023_3297367 crossref_primary_10_3390_w13223173 crossref_primary_10_1109_TGRS_2025_3557196 crossref_primary_10_3390_rs15123029 crossref_primary_10_1007_s11629_024_9266_8 crossref_primary_10_1016_j_foreco_2024_121725 crossref_primary_10_3390_rs14122743 crossref_primary_10_1007_s00271_022_00798_8 crossref_primary_10_1016_j_enbuild_2025_115624 crossref_primary_10_1016_j_pce_2024_103819 crossref_primary_10_1111_2041_210X_14359 crossref_primary_10_1016_j_agrformet_2024_110217 crossref_primary_10_1016_j_oneear_2024_11_001 crossref_primary_10_1016_j_agrformet_2025_110756 crossref_primary_10_1016_j_rse_2023_113797 crossref_primary_10_3390_rs14205158 crossref_primary_10_1016_j_tree_2023_04_007 crossref_primary_10_1016_j_catena_2022_106211 crossref_primary_10_1111_2041_210X_14112 crossref_primary_10_1088_1748_9326_ad5858 crossref_primary_10_1186_s40462_025_00552_7 crossref_primary_10_1016_j_ecoinf_2024_102494 crossref_primary_10_1007_s10531_024_02961_3 crossref_primary_10_3390_rs14020404 crossref_primary_10_7717_peerj_18585 crossref_primary_10_1109_TGRS_2025_3600816 crossref_primary_10_7717_peerj_19673 crossref_primary_10_3390_rs14246251 crossref_primary_10_1088_2515_7620_ada420 crossref_primary_10_3390_f15010215 crossref_primary_10_3390_rs15030664 crossref_primary_10_1029_2025GL115437 crossref_primary_10_1111_mam_12279 crossref_primary_10_3390_ijerph182111416 crossref_primary_10_1029_2021JG006668 crossref_primary_10_1080_15481603_2024_2396807 crossref_primary_10_1109_JSTARS_2025_3584704 crossref_primary_10_1016_j_isprsjprs_2022_11_011 crossref_primary_10_1016_j_scs_2024_105669 crossref_primary_10_1016_j_ecoinf_2023_102082 crossref_primary_10_1038_s41559_022_01915_8 crossref_primary_10_1016_j_rse_2024_113999 crossref_primary_10_1038_s43247_024_01246_5 crossref_primary_10_3389_frsen_2025_1575100 crossref_primary_10_1080_01431161_2024_2354072 crossref_primary_10_1109_JSTARS_2023_3328403 crossref_primary_10_3390_rs14164088 crossref_primary_10_3390_rs15215162 crossref_primary_10_1016_j_foreco_2023_121648 crossref_primary_10_1007_s11356_024_34415_2 crossref_primary_10_1088_1748_9326_ad560a crossref_primary_10_3390_rs17050796 crossref_primary_10_1016_j_rse_2022_113074 crossref_primary_10_1016_j_rse_2022_113195 crossref_primary_10_1007_s40725_024_00242_4 crossref_primary_10_1016_j_srs_2024_100181 crossref_primary_10_3390_rs14030568 crossref_primary_10_1016_j_ecolind_2025_113610 crossref_primary_10_1016_j_rse_2023_113693 crossref_primary_10_1016_j_rse_2024_113993 crossref_primary_10_1016_j_rse_2023_113574 crossref_primary_10_1080_22797254_2024_2422323 crossref_primary_10_3390_land12081509 crossref_primary_10_3390_rs15082080 crossref_primary_10_1016_j_ecolind_2025_113889 crossref_primary_10_1016_j_jag_2025_104558 crossref_primary_10_1080_19376812_2023_2164865 crossref_primary_10_1016_j_envsoft_2025_106373 crossref_primary_10_1029_2023WR036948 crossref_primary_10_3389_fsufs_2025_1649756 crossref_primary_10_1016_j_jag_2025_104791 crossref_primary_10_1029_2021JG006519 crossref_primary_10_1080_13658816_2023_2224421 crossref_primary_10_3390_rs16111859 crossref_primary_10_1016_j_agrformet_2023_109360 crossref_primary_10_1016_j_scitotenv_2023_163128 crossref_primary_10_1016_j_segan_2023_101016 crossref_primary_10_3390_rs16132321 crossref_primary_10_1111_mam_12376 crossref_primary_10_3390_rs14194859 crossref_primary_10_1093_biolinnean_blaf008 crossref_primary_10_3390_rs12203351 crossref_primary_10_1080_01584197_2025_2508954 crossref_primary_10_1016_j_rse_2025_114774 crossref_primary_10_1111_fwb_14300 crossref_primary_10_1016_j_catena_2024_108488 crossref_primary_10_3390_rs15112862 crossref_primary_10_1109_JSTARS_2024_3443348 crossref_primary_10_3390_fire8040149 crossref_primary_10_3390_rs17142340 crossref_primary_10_1007_s12524_024_01836_y crossref_primary_10_3390_rs15143457 crossref_primary_10_1007_s42991_023_00393_0 crossref_primary_10_1016_j_jag_2024_104080 crossref_primary_10_3390_rs14246264 crossref_primary_10_1080_14693062_2024_2330373 crossref_primary_10_1029_2022JG007046 crossref_primary_10_3390_s24051651 crossref_primary_10_1088_2752_664X_ad7f5a crossref_primary_10_1016_j_buildenv_2023_110085 crossref_primary_10_1016_j_rse_2025_114644 crossref_primary_10_1016_j_foreco_2025_123040 crossref_primary_10_1088_2632_2153_ada47e crossref_primary_10_1080_10106049_2025_2453024 crossref_primary_10_1080_01431161_2025_2557583 crossref_primary_10_1109_JSTARS_2024_3388914 crossref_primary_10_1080_01431161_2025_2476776 crossref_primary_10_1016_j_uclim_2024_102045 crossref_primary_10_3390_rs14030649 crossref_primary_10_1038_s41467_024_55240_8 crossref_primary_10_5194_bg_20_3803_2023 crossref_primary_10_1016_j_jag_2025_104376 crossref_primary_10_1016_j_jag_2022_102754 crossref_primary_10_1016_j_rsase_2022_100817 crossref_primary_10_1007_s10661_025_13639_w crossref_primary_10_1088_1748_9326_acc8ea crossref_primary_10_1002_ajp_23625 crossref_primary_10_1111_mam_70002 crossref_primary_10_1007_s12524_023_01792_z crossref_primary_10_3389_fgene_2021_708871 crossref_primary_10_3390_rs13030442 crossref_primary_10_3390_rs17101777 crossref_primary_10_1007_s10344_025_01974_9 crossref_primary_10_1016_j_foreco_2022_120343 crossref_primary_10_1073_pnas_2401755122 crossref_primary_10_1016_j_landusepol_2023_106922 crossref_primary_10_1016_j_jhydrol_2025_132938 crossref_primary_10_1088_1748_9326_acde8f crossref_primary_10_1080_01431161_2024_2343134 crossref_primary_10_3389_ffgc_2023_1181049 crossref_primary_10_1016_j_cub_2024_11_051 crossref_primary_10_1016_j_rse_2021_112845 crossref_primary_10_1016_j_rse_2021_112844 crossref_primary_10_3390_rs15225391 crossref_primary_10_5194_essd_14_5695_2022 crossref_primary_10_1016_j_fecs_2024_100228 crossref_primary_10_1016_j_rse_2021_112849 crossref_primary_10_1007_s42690_021_00517_4 crossref_primary_10_1016_j_agrformet_2023_109586 crossref_primary_10_1111_1365_2656_13594 crossref_primary_10_3390_rs15082197 crossref_primary_10_1007_s12524_023_01693_1 crossref_primary_10_1016_j_agrformet_2023_109592 crossref_primary_10_1016_j_rse_2023_113491 crossref_primary_10_1134_S0010952523700715 crossref_primary_10_1093_nsr_nwae274 crossref_primary_10_1016_j_buildenv_2023_110383 crossref_primary_10_3390_rs15225274 crossref_primary_10_1111_gcb_70321 crossref_primary_10_3389_fpls_2024_1492560 crossref_primary_10_3390_rs15020515 crossref_primary_10_1007_s10113_024_02302_8 crossref_primary_10_1007_s10531_023_02606_x crossref_primary_10_1016_j_ecolind_2024_112157 crossref_primary_10_1109_TGRS_2022_3231926 crossref_primary_10_1002_pan3_10739 crossref_primary_10_1016_j_agrformet_2023_109676 crossref_primary_10_1088_1361_6501_addf66 crossref_primary_10_1016_j_jag_2025_104474 crossref_primary_10_1038_s41597_025_05739_6 crossref_primary_10_1088_2752_664X_acffcd crossref_primary_10_1007_s10980_024_01908_x crossref_primary_10_3390_fire5010005 crossref_primary_10_1080_15732479_2023_2177875 crossref_primary_10_1371_journal_pone_0308931 crossref_primary_10_3832_ifor4434_017 crossref_primary_10_1007_s40808_022_01648_4 crossref_primary_10_1016_j_rsase_2025_101691 crossref_primary_10_3390_rs16071281 crossref_primary_10_1016_j_rse_2024_114534 crossref_primary_10_3390_rs14215363 crossref_primary_10_1016_j_epsr_2022_107840 crossref_primary_10_3390_rs15133447 crossref_primary_10_1109_JSTARS_2025_3595673 crossref_primary_10_1016_j_jnc_2025_126849 crossref_primary_10_1038_s43247_023_00758_w crossref_primary_10_1111_nph_20127 crossref_primary_10_3390_f16010145 crossref_primary_10_1016_j_jnc_2025_126842 crossref_primary_10_1038_s41597_025_04655_z crossref_primary_10_3390_rs16071268 crossref_primary_10_1016_j_jag_2021_102326 crossref_primary_10_1109_IEEEDATA_2025_3576318 crossref_primary_10_11728_cjss2023_06_2023_0074 crossref_primary_10_3390_rs15030776 crossref_primary_10_1371_journal_pone_0289437 crossref_primary_10_1016_j_isprsjprs_2024_07_002 crossref_primary_10_1007_s10531_024_02920_y crossref_primary_10_1016_j_landurbplan_2022_104499 crossref_primary_10_1111_gcb_70222 crossref_primary_10_3390_rs14020364 crossref_primary_10_3390_rs16193650 crossref_primary_10_3389_fpls_2025_1547688 crossref_primary_10_3390_rs15174123 crossref_primary_10_1016_j_rse_2025_114719 crossref_primary_10_1016_j_rse_2025_114718 crossref_primary_10_1016_j_cell_2025_03_035 crossref_primary_10_1109_JSTARS_2025_3527631 crossref_primary_10_3390_rs16020425 crossref_primary_10_1016_j_rse_2025_114957 crossref_primary_10_1109_TGRS_2025_3542685 crossref_primary_10_3390_rs14102421 crossref_primary_10_3390_rs15153781 crossref_primary_10_1109_JSTARS_2024_3522688 crossref_primary_10_1002_ecs2_70026 crossref_primary_10_1016_j_isprsjprs_2024_01_014 crossref_primary_10_3390_forecast3030034 crossref_primary_10_1016_j_scs_2022_104051 crossref_primary_10_1038_s41559_025_02821_5 crossref_primary_10_1080_17538947_2025_2482101 crossref_primary_10_3390_rs13245105 crossref_primary_10_1002_ece3_11132 crossref_primary_10_3390_rs15030820 crossref_primary_10_1038_s41561_024_01423_3 crossref_primary_10_1016_j_acags_2025_100289 crossref_primary_10_1002_ecs2_4633 crossref_primary_10_1109_LGRS_2025_3602095 crossref_primary_10_3390_rs15040975 crossref_primary_10_1016_j_rse_2024_114557 crossref_primary_10_1016_j_scs_2024_105701 crossref_primary_10_1038_s41598_025_92231_1 crossref_primary_10_1016_j_isprsjprs_2021_11_015 crossref_primary_10_1016_j_rse_2021_112764 crossref_primary_10_3390_rs15174234 crossref_primary_10_1080_17538947_2025_2528657 crossref_primary_10_1029_2024EA003709 crossref_primary_10_1038_s41597_024_03668_4 crossref_primary_10_3390_f14071357 crossref_primary_10_1111_gcb_16017 crossref_primary_10_1038_s43247_024_01325_7 crossref_primary_10_1088_1748_9326_ac9c1d crossref_primary_10_1002_jwmg_22633 crossref_primary_10_1038_s41598_023_50308_9 crossref_primary_10_1080_01431161_2024_2391093 crossref_primary_10_3390_rs14133172 crossref_primary_10_1002_ece3_70116 crossref_primary_10_1016_j_fecs_2023_100122 crossref_primary_10_1038_s41559_023_02206_6 crossref_primary_10_1016_j_rsase_2024_101384 crossref_primary_10_1007_s00371_022_02526_x crossref_primary_10_1016_j_foreco_2022_120536 crossref_primary_10_1007_s42965_025_00392_x crossref_primary_10_3390_rs16162913 crossref_primary_10_1016_j_jenvman_2024_122101 crossref_primary_10_1080_13658816_2023_2183959 crossref_primary_10_1111_gcb_17224 crossref_primary_10_22201_fc_25942158e_2025_1_902 crossref_primary_10_1007_s10661_022_10657_w crossref_primary_10_1016_j_rse_2024_114322 crossref_primary_10_1016_j_jag_2024_103941 crossref_primary_10_1016_j_rse_2021_112510 crossref_primary_10_3390_rs14102320 crossref_primary_10_3390_rs15010074 crossref_primary_10_1080_15481603_2025_2483027 crossref_primary_10_1016_j_earscirev_2023_104501 crossref_primary_10_1016_j_agrformet_2023_109754 crossref_primary_10_3390_ijgi10060384 crossref_primary_10_1007_s10661_023_12066_z crossref_primary_10_1016_j_rse_2022_112919 crossref_primary_10_1016_j_jag_2025_104390 crossref_primary_10_1093_cz_zoae082 crossref_primary_10_1016_j_ecoinf_2023_102348 crossref_primary_10_1016_j_rse_2024_114572 crossref_primary_10_1029_2024GH001253 crossref_primary_10_7780_kjrs_2024_40_5_2_8 crossref_primary_10_3390_rs17050941 crossref_primary_10_1016_j_rse_2024_114578 crossref_primary_10_1111_geb_13773 crossref_primary_10_1016_j_rse_2025_114930 crossref_primary_10_5358_hsj_44_143 crossref_primary_10_1016_j_rse_2024_114333 crossref_primary_10_1016_j_agrformet_2023_109408 crossref_primary_10_1016_j_jag_2024_103711 crossref_primary_10_1111_geb_13406 crossref_primary_10_1051_e3sconf_202454204003 crossref_primary_10_1016_j_rse_2025_114802 crossref_primary_10_5194_essd_15_2957_2023 crossref_primary_10_59717_j_xinn_geo_2024_100095 crossref_primary_10_1002_eap_2526 crossref_primary_10_1002_ecs2_70258 crossref_primary_10_1038_s41467_024_44734_0 crossref_primary_10_3390_rs16203798 crossref_primary_10_1080_15481603_2023_2292374 crossref_primary_10_1007_s10661_024_13441_0 crossref_primary_10_3390_rs15030730 crossref_primary_10_3390_rs15245686 crossref_primary_10_1016_j_ecoinf_2023_102234 crossref_primary_10_1016_j_rse_2024_114226 crossref_primary_10_1016_j_rse_2020_112282 crossref_primary_10_1088_1748_9326_ac77a2 crossref_primary_10_3389_frsen_2025_1563430 crossref_primary_10_1038_s41467_024_54349_0 crossref_primary_10_1007_s10021_022_00777_2 crossref_primary_10_3390_rs15092285 crossref_primary_10_1038_s41597_025_05021_9 crossref_primary_10_1016_j_apgeog_2023_103024 crossref_primary_10_1088_1748_9326_ac46e9 crossref_primary_10_1016_j_rse_2025_114916 crossref_primary_10_1088_1748_9326_acad8d crossref_primary_10_1007_s10531_024_02835_8 crossref_primary_10_2139_ssrn_4609761 crossref_primary_10_3390_rs16122138 crossref_primary_10_3390_rs17091594 crossref_primary_10_3390_rs15122963 crossref_primary_10_1206_0003_0090_472_1_1 crossref_primary_10_1016_j_gloplacha_2024_104626 crossref_primary_10_1109_LGRS_2021_3131263 crossref_primary_10_3390_app15126824 crossref_primary_10_3832_ifor4632_017 crossref_primary_10_5194_hess_26_3177_2022 crossref_primary_10_3390_f16091481 crossref_primary_10_3390_rs17050886 crossref_primary_10_1016_j_asr_2025_09_013 crossref_primary_10_1016_j_rse_2021_112571 crossref_primary_10_1016_j_ecolind_2024_111921 crossref_primary_10_3390_f13010124 crossref_primary_10_3390_f14050876 crossref_primary_10_1016_j_cub_2023_04_019 crossref_primary_10_1080_01431161_2024_2326537 crossref_primary_10_5194_essd_15_4849_2023 crossref_primary_10_1016_j_jenvman_2023_119921 crossref_primary_10_3390_rs16224332 crossref_primary_10_3390_su16051735 crossref_primary_10_1029_2022WR034215 crossref_primary_10_1016_j_ecoinf_2024_102621 crossref_primary_10_3390_fire8020054 crossref_primary_10_1007_s44391_025_00021_z crossref_primary_10_1109_JSTARS_2023_3267118 crossref_primary_10_3389_feart_2021_752254 crossref_primary_10_1038_s41597_024_03930_9 crossref_primary_10_1088_1748_9326_ac46ec crossref_primary_10_1016_j_rse_2024_114005 crossref_primary_10_3897_BDJ_13_e153431 crossref_primary_10_1093_ornithapp_duac004 crossref_primary_10_1002_inc3_70011 crossref_primary_10_3390_rs16193550 crossref_primary_10_3390_rs17060993 crossref_primary_10_3390_s23104937 crossref_primary_10_1029_2024MS004300 crossref_primary_10_1080_17538947_2024_2330690 crossref_primary_10_1007_s41348_024_00861_w crossref_primary_10_1002_ece3_71341 crossref_primary_10_1002_hyp_14769 crossref_primary_10_1016_j_ecoinf_2024_102832 crossref_primary_10_1016_j_ecoinf_2024_102712 crossref_primary_10_1038_s41597_024_03428_4 crossref_primary_10_1109_JSTARS_2025_3545482 crossref_primary_10_3390_rs15122985 crossref_primary_10_1016_j_aiig_2025_100141 crossref_primary_10_3390_f16081249 crossref_primary_10_1111_2041_210X_13933 crossref_primary_10_3390_rs15061535 crossref_primary_10_26848_rbgf_v17_4_p3008_3021 crossref_primary_10_3390_rs17142407 crossref_primary_10_1016_j_jenvman_2023_118736 crossref_primary_10_3390_land13101644 crossref_primary_10_1080_2150704X_2022_2079017 crossref_primary_10_1038_s41597_024_04237_5 crossref_primary_10_3390_rs17121968 crossref_primary_10_1016_j_jhazmat_2021_126245 crossref_primary_10_1093_pnasnexus_pgad076 crossref_primary_10_1109_ACCESS_2024_3396414 crossref_primary_10_1016_j_oneear_2024_05_002 crossref_primary_10_1016_j_rse_2021_112428 crossref_primary_10_1080_21683565_2025_2524734 crossref_primary_10_1007_s10980_025_02195_w crossref_primary_10_1002_eap_2603 crossref_primary_10_3390_rs17010085 crossref_primary_10_1109_JSTARS_2024_3522330 crossref_primary_10_3390_su14020904 crossref_primary_10_3390_rs16162933 crossref_primary_10_1016_j_rse_2024_114384 crossref_primary_10_1080_10095020_2024_2429376 crossref_primary_10_3390_rs15061522 crossref_primary_10_1007_s40725_025_00248_6 crossref_primary_10_1038_s41597_025_04430_0 crossref_primary_10_3390_rs17173012 crossref_primary_10_1109_JSTARS_2021_3080711 crossref_primary_10_5194_hess_28_3567_2024 crossref_primary_10_1016_j_rse_2024_114026 crossref_primary_10_31413_nat_v13i3_19602 crossref_primary_10_1038_s41598_023_38935_8 crossref_primary_10_5194_essd_16_5449_2024 crossref_primary_10_1029_2021WR029716 crossref_primary_10_3390_fire6050215 crossref_primary_10_1002_evan_22032 crossref_primary_10_1016_j_scitotenv_2023_161757 crossref_primary_10_1016_j_ecoinf_2023_102404 crossref_primary_10_1016_j_rse_2024_114152 crossref_primary_10_5194_bg_22_4349_2025 crossref_primary_10_1016_j_rse_2024_114270 crossref_primary_10_3390_rs16213992 crossref_primary_10_1017_eds_2024_53 crossref_primary_10_1016_j_rse_2024_114276 crossref_primary_10_1029_2022JF006873 crossref_primary_10_3389_ffgc_2022_979528 crossref_primary_10_5194_essd_17_4397_2025 crossref_primary_10_1111_btp_13014 crossref_primary_10_3390_rs15235436 crossref_primary_10_7717_peerj_13202 crossref_primary_10_1371_journal_pone_0311816 crossref_primary_10_1002_rse2_416 crossref_primary_10_1016_j_foreco_2025_122964 crossref_primary_10_1080_01431161_2025_2549131 crossref_primary_10_3390_rs15010001 crossref_primary_10_1016_j_ocemod_2025_102536 crossref_primary_10_1016_j_envres_2024_119432 crossref_primary_10_1109_JSTARS_2021_3128022 crossref_primary_10_1007_s11707_025_1151_4 crossref_primary_10_3390_rs16010110 crossref_primary_10_1109_JSTARS_2022_3163208 crossref_primary_10_24057_2071_9388_2025_3735 crossref_primary_10_3389_fenvs_2025_1635707 crossref_primary_10_1109_JSTARS_2025_3599881 crossref_primary_10_1016_j_biocon_2025_111207 crossref_primary_10_1016_j_rse_2024_114168 crossref_primary_10_1016_j_rse_2022_112997 crossref_primary_10_1016_j_foreco_2025_122996 crossref_primary_10_1016_j_rsase_2024_101407 crossref_primary_10_1109_ACCESS_2024_3523415 crossref_primary_10_1038_s41598_024_52379_8 crossref_primary_10_1016_j_coesh_2021_100251 crossref_primary_10_1515_mammalia_2021_0113 crossref_primary_10_3390_rs13091650 crossref_primary_10_1016_j_foreco_2024_122317 crossref_primary_10_1038_s41467_025_59799_8 crossref_primary_10_1109_JSTARS_2024_3417302 crossref_primary_10_3389_ffgc_2023_1098901 crossref_primary_10_1016_j_scitotenv_2024_176393 crossref_primary_10_1016_j_rse_2024_114174 crossref_primary_10_1016_j_ufug_2025_129013 crossref_primary_10_1016_j_scs_2025_106493 crossref_primary_10_1016_j_scs_2025_106494 crossref_primary_10_1016_j_ecolind_2025_113085 crossref_primary_10_1029_2025AV001689 crossref_primary_10_1016_j_rse_2024_114293 crossref_primary_10_3390_resources13050062 crossref_primary_10_1080_15481603_2024_2427305 crossref_primary_10_5194_nhess_24_681_2024 crossref_primary_10_1038_s41597_025_04481_3 crossref_primary_10_1016_j_jag_2024_103798 crossref_primary_10_1016_j_scitotenv_2023_169692 crossref_primary_10_3390_land14040872 crossref_primary_10_1016_j_rse_2021_112587 crossref_primary_10_3390_f14030506 crossref_primary_10_1038_s41597_024_03896_8 crossref_primary_10_1093_pnasnexus_pgae360 crossref_primary_10_3390_rs17060966 crossref_primary_10_1038_s41597_024_04213_z crossref_primary_10_3390_su151310434 crossref_primary_10_1016_j_foreco_2025_122747 crossref_primary_10_1088_1748_9326_adbb03 crossref_primary_10_1016_j_fecs_2022_100006 crossref_primary_10_1111_1365_2745_13999 crossref_primary_10_1016_S2542_5196_25_00112_3 crossref_primary_10_1134_S0010952522700022 crossref_primary_10_1007_s12524_023_01740_x crossref_primary_10_1016_j_isprsjprs_2021_08_019 crossref_primary_10_1111_2041_210X_70041 crossref_primary_10_3389_frsen_2025_1532280 crossref_primary_10_3390_rs14153813 crossref_primary_10_1016_j_geomorph_2025_109689 crossref_primary_10_1088_2515_7620_acc56d crossref_primary_10_5194_essd_15_4927_2023 crossref_primary_10_1038_s41893_022_00904_w crossref_primary_10_1109_TGRS_2022_3222991 crossref_primary_10_1111_2041_210X_14040 crossref_primary_10_3390_s25113570 crossref_primary_10_1016_j_measurement_2023_113972 crossref_primary_10_1016_j_rse_2023_113823 crossref_primary_10_1016_j_jag_2025_104814 crossref_primary_10_1016_j_rse_2023_113703 crossref_primary_10_1016_j_rse_2023_113945 crossref_primary_10_1029_2021EF002560 crossref_primary_10_1002_ece3_11571 crossref_primary_10_1038_s44185_024_00044_8 crossref_primary_10_1080_15481603_2023_2260637 crossref_primary_10_1080_01431161_2023_2299278 crossref_primary_10_3389_fpls_2025_1561826 crossref_primary_10_3389_fpls_2024_1428268 crossref_primary_10_3390_f15071261 crossref_primary_10_3390_s22052015 crossref_primary_10_1016_j_agrformet_2025_110689 crossref_primary_10_3390_rs15153738 crossref_primary_10_3390_f16040570 crossref_primary_10_1016_j_jag_2022_103176 crossref_primary_10_1016_j_jag_2023_103435 crossref_primary_10_1016_j_jag_2022_103175 crossref_primary_10_1016_j_isprsjprs_2024_02_002 crossref_primary_10_3390_rs13040809 crossref_primary_10_1016_j_atech_2025_101338 crossref_primary_10_1029_2024JG008635 crossref_primary_10_1080_07038992_2024_2341762 crossref_primary_10_1038_s43016_021_00429_z crossref_primary_10_3390_f14061133 crossref_primary_10_1002_rse2_330 crossref_primary_10_1016_j_jag_2023_103431 crossref_primary_10_3390_rs14235968 crossref_primary_10_1016_j_wace_2022_100487 crossref_primary_10_1016_j_rse_2025_115030 crossref_primary_10_3390_rs15245627 crossref_primary_10_5194_essd_17_3219_2025 crossref_primary_10_3390_f14030454 crossref_primary_10_3390_s24113488 crossref_primary_10_3390_su151511525 crossref_primary_10_1016_j_scitotenv_2022_154729 crossref_primary_10_1016_j_csr_2023_104945 crossref_primary_10_3390_rs14184434 crossref_primary_10_1016_j_ecolind_2024_112744 crossref_primary_10_1029_2023EF003590 crossref_primary_10_1007_s10666_023_09897_y crossref_primary_10_1016_j_rse_2022_113402 crossref_primary_10_1371_journal_pone_0292386 crossref_primary_10_1016_j_pce_2025_104003 crossref_primary_10_1002_rse2_248 crossref_primary_10_1016_j_ecoinf_2025_103045 crossref_primary_10_3390_rs17091536 crossref_primary_10_1002_fee_2585 crossref_primary_10_3390_f15122115 crossref_primary_10_1109_ACCESS_2024_3442768 crossref_primary_10_1016_j_egyr_2023_10_073 crossref_primary_10_3390_rs17152617 crossref_primary_10_1007_s40808_024_02171_4 crossref_primary_10_1016_j_rse_2024_114099 crossref_primary_10_3390_rs13194012 crossref_primary_10_1016_j_rse_2024_114098 crossref_primary_10_1029_2024JG008519 crossref_primary_10_1088_1748_9326_adc752 crossref_primary_10_1002_esp_5461 crossref_primary_10_3390_f15071161 crossref_primary_10_1038_s41893_022_01020_5 crossref_primary_10_1016_j_ecolind_2024_111752 crossref_primary_10_1080_01431161_2024_2373344 crossref_primary_10_3390_rs13224516 crossref_primary_10_1088_1748_9326_ac4d4f crossref_primary_10_1186_s13717_022_00396_8 crossref_primary_10_1016_j_jag_2023_103570 crossref_primary_10_3390_f14061270 crossref_primary_10_1007_s10980_023_01597_y crossref_primary_10_1093_jofore_fvae020 crossref_primary_10_33494_nzjfs552025x446x crossref_primary_10_1016_j_jag_2023_103452 crossref_primary_10_1080_15481603_2024_2374150 crossref_primary_10_3390_f13101686 crossref_primary_10_1080_15481603_2025_2497603 crossref_primary_10_1109_TGRS_2024_3389821 crossref_primary_10_3390_rs14153615 crossref_primary_10_1007_s10745_025_00604_x crossref_primary_10_1016_j_rse_2025_115019 crossref_primary_10_3390_rs14153618 crossref_primary_10_3390_rs14153738 crossref_primary_10_1007_s11355_023_00539_9 crossref_primary_10_1016_j_jenvman_2025_127197 |
| Cites_doi | 10.1016/j.rse.2019.111347 10.1038/s41598-017-15050-z 10.3390/rs70505534 10.1016/j.rse.2019.111278 10.1016/j.isprsjprs.2014.11.007 10.1016/j.rse.2014.10.029 10.4155/cmt.11.18 10.1126/science.263.5144.185 10.1111/j.1755-263X.2009.00067.x 10.1080/07038992.2016.1207484 10.1016/j.rse.2017.12.020 10.1016/S0034-4257(02)00056-1 10.1088/1748-9326/3/4/045011 10.1007/s00442-011-2165-z 10.1016/0034-4257(85)90102-6 10.1016/j.rse.2016.07.016 10.1029/2010GL043622 10.3402/tellusb.v51i2.16288 10.1126/science.1073947 10.1117/1.2795724 10.1016/j.rse.2016.02.023 10.1038/nature10425 10.3390/rs5084045 10.1126/science.1201609 10.1016/j.rse.2018.02.019 10.1126/science.1244693 10.5589/m10-037 10.3390/rs12030426 10.1073/pnas.1710465114 10.1029/2011JG001708 10.1088/1748-9326/10/7/074002 10.3390/rs61212409 10.1016/j.srs.2020.100002 10.3390/rs6031762 10.5589/m03-026 10.1023/A:1018054314350 10.1073/pnas.1810512116 10.1139/x00-142 |
| ContentType | Journal Article |
| Copyright | 2020 Elsevier Inc. Copyright Elsevier BV Feb 2021 |
| Copyright_xml | – notice: 2020 Elsevier Inc. – notice: Copyright Elsevier BV Feb 2021 |
| DBID | AAYXX CITATION 7QF 7QO 7QQ 7SC 7SE 7SN 7SP 7SR 7TA 7TB 7TG 7U5 8BQ 8FD C1K F28 FR3 H8D H8G JG9 JQ2 KL. KR7 L7M L~C L~D P64 7S9 L.6 |
| DOI | 10.1016/j.rse.2020.112165 |
| DatabaseName | CrossRef Aluminium Industry Abstracts Biotechnology Research Abstracts Ceramic Abstracts Computer and Information Systems Abstracts Corrosion Abstracts Ecology Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts Materials Business File Mechanical & Transportation Engineering Abstracts Meteorological & Geoastrophysical Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database Environmental Sciences and Pollution Management ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database Copper Technical Reference Library Materials Research Database ProQuest Computer Science Collection Meteorological & Geoastrophysical Abstracts - Academic Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Biotechnology and BioEngineering Abstracts AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef Materials Research Database Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Materials Business File Environmental Sciences and Pollution Management Aerospace Database Copper Technical Reference Library Engineered Materials Abstracts Meteorological & Geoastrophysical Abstracts Biotechnology Research Abstracts Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Civil Engineering Abstracts Aluminium Industry Abstracts Electronics & Communications Abstracts Ceramic Abstracts Ecology Abstracts METADEX Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Professional Solid State and Superconductivity Abstracts Engineering Research Database Corrosion Abstracts Meteorological & Geoastrophysical Abstracts - Academic AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA Materials Research Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geography Geology Environmental Sciences |
| EISSN | 1879-0704 |
| ExternalDocumentID | 10_1016_j_rse_2020_112165 S0034425720305381 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 123 1B1 1RT 1~. 1~5 29P 4.4 41~ 457 4G. 53G 5VS 6TJ 7-5 71M 8P~ 9JM 9JN AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO ABEFU ABFNM ABFYP ABJNI ABLST ABMAC ABPPZ ABQEM ABQYD ABXDB ABYKQ ACDAQ ACGFS ACIWK ACLVX ACPRK ACRLP ACSBN ADBBV ADEZE ADMUD AEBSH AEKER AENEX AFFNX AFKWA AFRAH AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AHHHB AIEXJ AIKHN AITUG AJBFU AJOXV AKIFW ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG ATOGT AVWKF AXJTR AZFZN BKOJK BLECG BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FA8 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q G8K GBLVA HMA HMC HVGLF HZ~ H~9 IHE IMUCA J1W KCYFY KOM LY3 LY9 M41 MO0 N9A O-L O9- OAUVE OHT OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SDF SDG SDP SEN SEP SES SEW SPC SPCBC SSE SSJ SSZ T5K TN5 TWZ VOH WH7 WUQ XOL ZCA ZMT ~02 ~G- ~KM 9DU AAHBH AATTM AAXKI AAYWO AAYXX ABDPE ABUFD ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADVLN ADXHL AEGFY AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD 7QF 7QO 7QQ 7SC 7SE 7SN 7SP 7SR 7TA 7TB 7TG 7U5 8BQ 8FD AGCQF C1K F28 FR3 H8D H8G JG9 JQ2 KL. KR7 L7M L~C L~D P64 7S9 L.6 |
| ID | FETCH-LOGICAL-c424t-e50cb57481448d7d3ea973b06912f02dabb999a404a2e13e989c9b9df2f77e303 |
| ISICitedReferencesCount | 889 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000604325300005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0034-4257 |
| IngestDate | Sun Sep 28 01:17:03 EDT 2025 Wed Aug 13 09:17:28 EDT 2025 Sat Nov 29 07:26:52 EST 2025 Tue Nov 18 22:08:39 EST 2025 Fri Feb 23 02:48:16 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Lidar Time-series GEDI Forest height Forest monitoring Landsat |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c424t-e50cb57481448d7d3ea973b06912f02dabb999a404a2e13e989c9b9df2f77e303 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| PQID | 2488247416 |
| PQPubID | 2045405 |
| ParticipantIDs | proquest_miscellaneous_2551937190 proquest_journals_2488247416 crossref_primary_10_1016_j_rse_2020_112165 crossref_citationtrail_10_1016_j_rse_2020_112165 elsevier_sciencedirect_doi_10_1016_j_rse_2020_112165 |
| PublicationCentury | 2000 |
| PublicationDate | February 2021 2021-02-00 20210201 |
| PublicationDateYYYYMMDD | 2021-02-01 |
| PublicationDate_xml | – month: 02 year: 2021 text: February 2021 |
| PublicationDecade | 2020 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | Remote sensing of environment |
| PublicationYear | 2021 |
| Publisher | Elsevier Inc Elsevier BV |
| Publisher_xml | – name: Elsevier Inc – name: Elsevier BV |
| References | Balmford, Bruner, Cooper, Costanza, Farber, Green, Munro (bb0020) 2002; 297 Xu, Saatchi, Shapiro, Meyer, Ferraz, Yang, Bastin, Banks, Boeckx, Verbeeck, Lewis, Muanza, Bongwele, Kayembe, Mbenza, Kalau, Mukendi, Ilunga, Ebuta (bb0250) 2017; 7 Breiman (bb0030) 1996; 24 Pugh, Lindeskog, Smith, Poulter, Arneth, Haverd, Calle (bb0210) 2019; 116 Chi, Sun, Huang, Guo, Ni, Fu (bb0040) 2015; 7 Potapov, Tyukavina, Turubanova, Talero, Hernandez-Serna, Hansen, Saah, Tenneson, Poortinga, Aekakkararungroj, Chishtie (bb0200) 2019; 232 Matasci, Hermosilla, Wulder, White, Coops, Hobart, Zald (bb0165) 2018; 209 Beck, Armston, Hofton, Luthcke (bb0025) 2020 Lefsky, Cohen, Spies (bb0150) 2001; 31 Coulter, Stow, Tsai, Ibanez, Shih, Kerr, Benza, Weeks, Mensah (bb0050) 2016; 184 Pan, Birdsey, Fang, Houghton, Kauppi, Kurz, Ciais (bb0185) 2011; 333 Houghton (bb0120) 1999; 51 UNFCCC [United Nations Framework Convention on Climate Change] (bb0240) 2006 White, Coops, Wulder, Vastaranta, Hilker, Tompalski (bb0245) 2016; 42 Lovell, Jupp, Culvenor, Coops (bb0160) 2003; 29 Dubayah, Hofton, Blair, Armston, Tang, Luthcke (bb0070) 2020 Dubayah, Blair, Goetz, Fatoyinbo, Hansen, Healey, Hofton, Hurtt, Kellner, Luthcke (bb0065) 2020; 1 Dubayah, Tang, Armston, Luthcke, Hofton, Blair (bb0075) 2020 Tyukavina, Baccini, Hansen, Potapov, Stehman, Houghton, Krylov, Turubanova, Goetz (bb0235) 2015; 10 Simard, Pinto, Fisher, Baccini (bb0225) 2011; 116 Cook, Corp, Nelson, Middleton, Morton, McCorkel, Masek, Ranson, Ly, Montesano, Cook, Corp, Nelson, Middleton, Morton, McCorkel, Masek, Ranson, Ly, Montesano (bb0045) 2013; 5 Sasaki, Putz (bb0215) 2009; 2 Duncanson, Niemann, Wulder (bb0080) 2010; 36 UNFCCC Secretariat (bb0220) 2016 IUCN (bb0130) 2018 Lefsky (bb0145) 2010; 37 Hofton, Blair (bb0115) 2019 Florczyk, Corbane, Ehrlich, Freire, Kemper, Maffenini, Sabo (bb0085) 2019; 29788 Gibson, Lee, Koh, Brook, Gardner, Barlow, Sodhi (bb0090) 2011; 478 Jarvis, Reuter, Nelson, Guevara (bb0135) 2008 Lang, Schindler, Wegner (bb0140) 2019; 233 Goetz, Dubayah (bb0095) 2011; 2 Breiman, Friedman, Olshen, Stone (bb0035) 1984 Popescu, Zhou, Nelson, Neuenschwander, Sheridan, Narine, Walsh (bb0195) 2018; 208 Baccini, Laporte, Goetz, Sun, Dong (bb0015) 2008; 3 Crist (bb0055) 1985 Hudak, Lefsky, Cohen, Berterretche (bb0125) 2002; 82 Lefsky, Keller, Pang, De Camargo, Hunter (bb0155) 2007 TERN AusCover (bb0230) 2020 Hansen, Potapov, Moore, Hancher, Turubanova, Tyukavina, Thau, Stehman, Goetz, Loveland, Kommareddy (bb0105) 2013; 342 Dixon, Solomon, Brown, Houghton, Trexier, Wisniewski (bb0060) 1994; 263 Peterson, Nelson (bb0190) 2014; 6 Griscom, Adams, Ellis, Houghton, Lomax, Miteva, Woodbury (bb0100) 2017; 114 NYDF Assessment Partners (bb0180) 2019 Potapov, Hansen, Kommareddy, Kommareddy, Turubanova, Pickens, Adusei, Tyukavina, Ying (bb0205) 2020; 12 Neigh, Masek, Bourget, Cook, Huang, Rishmawi, Zhao, Neigh, Masek, Bourget, Cook, Huang, Rishmawi, Zhao (bb0175) 2014; 6 Ahmed, Franklin, Wulder, White (bb0005) 2015; 101 Asner, Mascaro, Muller-Landau, Vieilledent, Vaudry, Rasamoelina, Hall, Van Breugel (bb0010) 2012; 168 Montesano, Rosette, Sun, North, Nelson, Dubayah, Ranson, Kharuk (bb0170) 2015; 158 Hansen, Potapov, Goetz, Turubanova, Tyukavina, Krylov, Kommareddy, Egorov (bb0110) 2016; 185 TERN AusCover (10.1016/j.rse.2020.112165_bb0230) 2020 UNFCCC [United Nations Framework Convention on Climate Change] (10.1016/j.rse.2020.112165_bb0240) 2006 Lefsky (10.1016/j.rse.2020.112165_bb0145) 2010; 37 Potapov (10.1016/j.rse.2020.112165_bb0200) 2019; 232 Balmford (10.1016/j.rse.2020.112165_bb0020) 2002; 297 Dubayah (10.1016/j.rse.2020.112165_bb0070) 2020 Goetz (10.1016/j.rse.2020.112165_bb0095) 2011; 2 Breiman (10.1016/j.rse.2020.112165_bb0035) 1984 Peterson (10.1016/j.rse.2020.112165_bb0190) 2014; 6 Baccini (10.1016/j.rse.2020.112165_bb0015) 2008; 3 Hudak (10.1016/j.rse.2020.112165_bb0125) 2002; 82 Dubayah (10.1016/j.rse.2020.112165_bb0065) 2020; 1 Pan (10.1016/j.rse.2020.112165_bb0185) 2011; 333 Florczyk (10.1016/j.rse.2020.112165_bb0085) 2019; 29788 Simard (10.1016/j.rse.2020.112165_bb0225) 2011; 116 Beck (10.1016/j.rse.2020.112165_bb0025) 2020 Houghton (10.1016/j.rse.2020.112165_bb0120) 1999; 51 Gibson (10.1016/j.rse.2020.112165_bb0090) 2011; 478 Lefsky (10.1016/j.rse.2020.112165_bb0150) 2001; 31 Hansen (10.1016/j.rse.2020.112165_bb0105) 2013; 342 Jarvis (10.1016/j.rse.2020.112165_bb0135) Lang (10.1016/j.rse.2020.112165_bb0140) 2019; 233 Potapov (10.1016/j.rse.2020.112165_bb0205) 2020; 12 Neigh (10.1016/j.rse.2020.112165_bb0175) 2014; 6 Dubayah (10.1016/j.rse.2020.112165_bb0075) 2020 Duncanson (10.1016/j.rse.2020.112165_bb0080) 2010; 36 Cook (10.1016/j.rse.2020.112165_bb0045) 2013; 5 Ahmed (10.1016/j.rse.2020.112165_bb0005) 2015; 101 Montesano (10.1016/j.rse.2020.112165_bb0170) 2015; 158 Popescu (10.1016/j.rse.2020.112165_bb0195) 2018; 208 Dixon (10.1016/j.rse.2020.112165_bb0060) 1994; 263 IUCN (10.1016/j.rse.2020.112165_bb0130) 2018 Coulter (10.1016/j.rse.2020.112165_bb0050) 2016; 184 Griscom (10.1016/j.rse.2020.112165_bb0100) 2017; 114 Sasaki (10.1016/j.rse.2020.112165_bb0215) 2009; 2 Matasci (10.1016/j.rse.2020.112165_bb0165) 2018; 209 Tyukavina (10.1016/j.rse.2020.112165_bb0235) 2015; 10 Hansen (10.1016/j.rse.2020.112165_bb0110) 2016; 185 Hofton (10.1016/j.rse.2020.112165_bb0115) 2019 Xu (10.1016/j.rse.2020.112165_bb0250) 2017; 7 White (10.1016/j.rse.2020.112165_bb0245) 2016; 42 UNFCCC Secretariat (10.1016/j.rse.2020.112165_bb0220) 2016 Chi (10.1016/j.rse.2020.112165_bb0040) 2015; 7 NYDF Assessment Partners (10.1016/j.rse.2020.112165_bb0180) Lovell (10.1016/j.rse.2020.112165_bb0160) 2003; 29 Asner (10.1016/j.rse.2020.112165_bb0010) 2012; 168 Lefsky (10.1016/j.rse.2020.112165_bb0155) 2007; 1 Pugh (10.1016/j.rse.2020.112165_bb0210) 2019; 116 Crist (10.1016/j.rse.2020.112165_bb0055) 1985 Breiman (10.1016/j.rse.2020.112165_bb0030) 1996; 24 |
| References_xml | – year: 1984 ident: bb0035 article-title: Classification and Regression Trees – volume: 51 start-page: 298 year: 1999 end-page: 313 ident: bb0120 article-title: The annual net flux of carbon to the atmosphere from changes in land use 1850–1990 publication-title: Tellus B – volume: 168 start-page: 1147 year: 2012 end-page: 1160 ident: bb0010 article-title: A universal airborne LiDAR approach for tropical forest carbon mapping publication-title: Oecologia – volume: 233 start-page: 111347 year: 2019 ident: bb0140 article-title: Country-wide high-resolution vegetation height mapping with Sentinel-2 publication-title: Remote Sens. Environ. – volume: 208 start-page: 154 year: 2018 end-page: 170 ident: bb0195 article-title: Photon counting LiDAR: an adaptive ground and canopy height retrieval algorithm for ICESat-2 data publication-title: Remote Sens. Environ. – volume: 6 start-page: 12409 year: 2014 end-page: 12426 ident: bb0190 article-title: Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR publication-title: Remote Sens. – volume: 31 start-page: 78 year: 2001 end-page: 87 ident: bb0150 article-title: An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon publication-title: Can. J. For. Res. – volume: 6 start-page: 1762 year: 2014 end-page: 1782 ident: bb0175 article-title: Deciphering the precision of stereo IKONOS canopy height models for US forests with G-LiHT airborne LiDAR publication-title: Remote Sens. – year: 2016 ident: bb0220 article-title: Key Decisions Relevant for Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD+) – start-page: 301 year: 1985 end-page: 306 ident: bb0055 article-title: A TM tasseled cap equivalent transformation for reflectance factor data publication-title: Remote Sens. Environ. – start-page: 013537 year: 2007 ident: bb0155 article-title: Revised method for forest canopy height estimation from Geoscience Laser Altimeter System waveforms publication-title: J. Appl. Remote. Sens. – volume: 36 start-page: 129 year: 2010 end-page: 141 ident: bb0080 article-title: Integration of GLAS and Landsat TM data for aboveground biomass estimation publication-title: Can. J. Remote. Sens. – volume: 2 start-page: 231 year: 2011 end-page: 244 ident: bb0095 article-title: Advances in remote sensing technology and implications for measuring and monitoring forest carbon stocks and change publication-title: Carbon Management – volume: 37 year: 2010 ident: bb0145 article-title: A global forest canopy height map from the moderate resolution imaging Spectroradiometer and the geoscience laser altimeter system publication-title: Geophys. Res. Lett. – volume: 7 start-page: 15030 year: 2017 ident: bb0250 article-title: Spatial distribution of carbon stored in forests of the Democratic Republic of Congo publication-title: Sci. Rep. – volume: 101 start-page: 89 year: 2015 end-page: 101 ident: bb0005 article-title: Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the random Forest algorithm publication-title: ISPRS J. Photogramm. Remote Sens. – volume: 116 start-page: 4021 year: 2011 ident: bb0225 article-title: Mapping forest canopy height globally with spaceborne lidar publication-title: Geophys. Res. Lett. – volume: 185 start-page: 221 year: 2016 end-page: 232 ident: bb0110 article-title: Mapping tree height distributions in sub-Saharan Africa using Landsat 7 and 8 data publication-title: Remote Sens. Environ. – volume: 209 start-page: 90 year: 2018 end-page: 106 ident: bb0165 article-title: Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots publication-title: Remote Sens. Environ. – volume: 7 start-page: 5534 year: 2015 end-page: 5564 ident: bb0040 article-title: National forest aboveground biomass mapping from ICESat/GLAS data and MODIS imagery in China publication-title: Remote Sens. – volume: 5 start-page: 4045 year: 2013 end-page: 4066 ident: bb0045 article-title: NASA Goddard’s LiDAR, hyperspectral and thermal (G-LiHT) airborne imager publication-title: Remote Sens. – volume: 232 start-page: 111278 year: 2019 ident: bb0200 article-title: Annual continuous fields of woody vegetation structure in the lower Mekong region from 2000-2017 Landsat time-series publication-title: Remote Sens. Environ. – year: 2020 ident: bb0025 article-title: GLOBAL – volume: 333 start-page: 988 year: 2011 end-page: 993 ident: bb0185 article-title: A large and persistent carbon sink in the world’s forests publication-title: Science – volume: 116 start-page: 4382 year: 2019 end-page: 4387 ident: bb0210 article-title: Role of forest regrowth in global carbon sink dynamics publication-title: Proc. Natl. Acad. Sci. – year: 2008 ident: bb0135 article-title: Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture (CIAT), available from – year: 2019 ident: bb0180 article-title: Protecting and Restoring Forests: A Story of Large Commitments Yet Limited Progress. New York Declaration on Forests Five-Year Assessment Report. Accessible at – volume: 114 start-page: 11645 year: 2017 end-page: 11650 ident: bb0100 article-title: Natural climate solutions publication-title: Proceedings of the National Academy of Sciences – year: 2006 ident: bb0240 article-title: United Nations Office at Geneva, Switzerland – year: 2020 ident: bb0230 article-title: Airborne LiDAR - Riegl Q560, point, raster and full waveform, Australian field sites – year: 2019 ident: bb0115 article-title: Algorithm Theoretical Basis Document (ATBD) for GEDI Transmit and Receive Waveform Processing for L1. Goddard Space Flight Center, Greenbelt, MD. and L2 Products – volume: 184 start-page: 396 year: 2016 end-page: 409 ident: bb0050 article-title: Classification and assessment of land cover and land use change in southern Ghana using dense stacks of Landsat 7 ETM+ imagery publication-title: Remote Sens. Environ. – volume: 10 year: 2015 ident: bb0235 article-title: Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012 publication-title: Environ. Res. Lett. – year: 2020 ident: bb0075 article-title: GEDI L2B Canopy Cover and Vertical Profile Metrics Data Global Footprint Level V001 [Data set]. – year: 2018 ident: bb0130 article-title: Getting Started with the Bonn Challenge – volume: 297 start-page: 950 year: 2002 end-page: 953 ident: bb0020 article-title: Economic reasons for conserving wild nature publication-title: Science – volume: 29788 year: 2019 ident: bb0085 article-title: GHSL Data Package 2019 publication-title: Luxembourg. EUR – volume: 29 start-page: 607 year: 2003 end-page: 622 ident: bb0160 article-title: Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests publication-title: Can. J. Remote. Sens. – volume: 12 start-page: 426 year: 2020 ident: bb0205 article-title: Landsat analysis ready data for global land cover and land cover change mapping publication-title: Remote Sens. – year: 2020 ident: bb0070 article-title: GEDI L2A elevation and height metrics data global footprint level V001 [data set]. – volume: 1 start-page: 100002 year: 2020 ident: bb0065 article-title: The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography publication-title: Sci. Remote Sens. – volume: 263 start-page: 185 year: 1994 end-page: 190 ident: bb0060 article-title: Carbon pools and flux of global forest ecosystems publication-title: Science – volume: 158 start-page: 95 year: 2015 end-page: 109 ident: bb0170 article-title: The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient publication-title: Remote Sens. Environ. – volume: 82 start-page: 397 year: 2002 end-page: 416 ident: bb0125 article-title: Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height publication-title: Remote Sens. Environ. – volume: 24 start-page: 123 year: 1996 end-page: 140 ident: bb0030 article-title: Bagging predictors publication-title: Mach. Learn. – volume: 2 start-page: 226 year: 2009 end-page: 232 ident: bb0215 article-title: Critical need for new definitions of “forest” and “forest degradation” in global climate change agreements publication-title: Conserv. Lett. – volume: 42 start-page: 619 year: 2016 end-page: 641 ident: bb0245 article-title: Remote sensing technologies for enhancing forest inventories: a review publication-title: Can. J. Remote. Sens. – volume: 3 start-page: 045011 year: 2008 ident: bb0015 article-title: A first map of tropical Africa’s above-ground biomass derived from satellite imagery publication-title: Environ. Res. Lett. – volume: 342 start-page: 850 year: 2013 end-page: 853 ident: bb0105 article-title: High-resolution global maps of 21st-century forest cover change publication-title: Science – volume: 478 start-page: 378 year: 2011 end-page: 381 ident: bb0090 article-title: Primary forests are irreplaceable for sustaining tropical biodiversity publication-title: Nature – year: 2020 ident: 10.1016/j.rse.2020.112165_bb0230 – volume: 233 start-page: 111347 year: 2019 ident: 10.1016/j.rse.2020.112165_bb0140 article-title: Country-wide high-resolution vegetation height mapping with Sentinel-2 publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2019.111347 – year: 2006 ident: 10.1016/j.rse.2020.112165_bb0240 – volume: 7 start-page: 15030 year: 2017 ident: 10.1016/j.rse.2020.112165_bb0250 article-title: Spatial distribution of carbon stored in forests of the Democratic Republic of Congo publication-title: Sci. Rep. doi: 10.1038/s41598-017-15050-z – volume: 7 start-page: 5534 issue: 5 year: 2015 ident: 10.1016/j.rse.2020.112165_bb0040 article-title: National forest aboveground biomass mapping from ICESat/GLAS data and MODIS imagery in China publication-title: Remote Sens. doi: 10.3390/rs70505534 – volume: 232 start-page: 111278 year: 2019 ident: 10.1016/j.rse.2020.112165_bb0200 article-title: Annual continuous fields of woody vegetation structure in the lower Mekong region from 2000-2017 Landsat time-series publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2019.111278 – ident: 10.1016/j.rse.2020.112165_bb0135 – volume: 101 start-page: 89 year: 2015 ident: 10.1016/j.rse.2020.112165_bb0005 article-title: Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the random Forest algorithm publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2014.11.007 – volume: 29788 year: 2019 ident: 10.1016/j.rse.2020.112165_bb0085 article-title: GHSL Data Package 2019 publication-title: Luxembourg. EUR – volume: 158 start-page: 95 year: 2015 ident: 10.1016/j.rse.2020.112165_bb0170 article-title: The uncertainty of biomass estimates from modeled ICESat-2 returns across a boreal forest gradient publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.10.029 – volume: 2 start-page: 231 year: 2011 ident: 10.1016/j.rse.2020.112165_bb0095 article-title: Advances in remote sensing technology and implications for measuring and monitoring forest carbon stocks and change publication-title: Carbon Management doi: 10.4155/cmt.11.18 – volume: 263 start-page: 185 issue: 5144 year: 1994 ident: 10.1016/j.rse.2020.112165_bb0060 article-title: Carbon pools and flux of global forest ecosystems publication-title: Science doi: 10.1126/science.263.5144.185 – year: 2020 ident: 10.1016/j.rse.2020.112165_bb0075 – volume: 2 start-page: 226 issue: 5 year: 2009 ident: 10.1016/j.rse.2020.112165_bb0215 article-title: Critical need for new definitions of “forest” and “forest degradation” in global climate change agreements publication-title: Conserv. Lett. doi: 10.1111/j.1755-263X.2009.00067.x – volume: 42 start-page: 619 issue: 5 year: 2016 ident: 10.1016/j.rse.2020.112165_bb0245 article-title: Remote sensing technologies for enhancing forest inventories: a review publication-title: Can. J. Remote. Sens. doi: 10.1080/07038992.2016.1207484 – volume: 209 start-page: 90 year: 2018 ident: 10.1016/j.rse.2020.112165_bb0165 article-title: Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2017.12.020 – volume: 82 start-page: 397 issue: 2–3 year: 2002 ident: 10.1016/j.rse.2020.112165_bb0125 article-title: Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height publication-title: Remote Sens. Environ. doi: 10.1016/S0034-4257(02)00056-1 – volume: 3 start-page: 045011 issue: 4 year: 2008 ident: 10.1016/j.rse.2020.112165_bb0015 article-title: A first map of tropical Africa’s above-ground biomass derived from satellite imagery publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/3/4/045011 – year: 1984 ident: 10.1016/j.rse.2020.112165_bb0035 – volume: 168 start-page: 1147 year: 2012 ident: 10.1016/j.rse.2020.112165_bb0010 article-title: A universal airborne LiDAR approach for tropical forest carbon mapping publication-title: Oecologia doi: 10.1007/s00442-011-2165-z – start-page: 301 year: 1985 ident: 10.1016/j.rse.2020.112165_bb0055 article-title: A TM tasseled cap equivalent transformation for reflectance factor data publication-title: Remote Sens. Environ. doi: 10.1016/0034-4257(85)90102-6 – volume: 184 start-page: 396 year: 2016 ident: 10.1016/j.rse.2020.112165_bb0050 article-title: Classification and assessment of land cover and land use change in southern Ghana using dense stacks of Landsat 7 ETM+ imagery publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2016.07.016 – volume: 37 year: 2010 ident: 10.1016/j.rse.2020.112165_bb0145 article-title: A global forest canopy height map from the moderate resolution imaging Spectroradiometer and the geoscience laser altimeter system publication-title: Geophys. Res. Lett. doi: 10.1029/2010GL043622 – volume: 51 start-page: 298 issue: 2 year: 1999 ident: 10.1016/j.rse.2020.112165_bb0120 article-title: The annual net flux of carbon to the atmosphere from changes in land use 1850–1990 publication-title: Tellus B doi: 10.3402/tellusb.v51i2.16288 – year: 2018 ident: 10.1016/j.rse.2020.112165_bb0130 – volume: 297 start-page: 950 issue: 5583 year: 2002 ident: 10.1016/j.rse.2020.112165_bb0020 article-title: Economic reasons for conserving wild nature publication-title: Science doi: 10.1126/science.1073947 – volume: 1 start-page: 013537 issue: 1 year: 2007 ident: 10.1016/j.rse.2020.112165_bb0155 article-title: Revised method for forest canopy height estimation from Geoscience Laser Altimeter System waveforms publication-title: J. Appl. Remote. Sens. doi: 10.1117/1.2795724 – volume: 185 start-page: 221 year: 2016 ident: 10.1016/j.rse.2020.112165_bb0110 article-title: Mapping tree height distributions in sub-Saharan Africa using Landsat 7 and 8 data publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2016.02.023 – volume: 478 start-page: 378 issue: 7369 year: 2011 ident: 10.1016/j.rse.2020.112165_bb0090 article-title: Primary forests are irreplaceable for sustaining tropical biodiversity publication-title: Nature doi: 10.1038/nature10425 – volume: 5 start-page: 4045 issue: 8 year: 2013 ident: 10.1016/j.rse.2020.112165_bb0045 article-title: NASA Goddard’s LiDAR, hyperspectral and thermal (G-LiHT) airborne imager publication-title: Remote Sens. doi: 10.3390/rs5084045 – volume: 333 start-page: 988 issue: 6045 year: 2011 ident: 10.1016/j.rse.2020.112165_bb0185 article-title: A large and persistent carbon sink in the world’s forests publication-title: Science doi: 10.1126/science.1201609 – volume: 208 start-page: 154 year: 2018 ident: 10.1016/j.rse.2020.112165_bb0195 article-title: Photon counting LiDAR: an adaptive ground and canopy height retrieval algorithm for ICESat-2 data publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2018.02.019 – volume: 342 start-page: 850 issue: 6160 year: 2013 ident: 10.1016/j.rse.2020.112165_bb0105 article-title: High-resolution global maps of 21st-century forest cover change publication-title: Science doi: 10.1126/science.1244693 – year: 2020 ident: 10.1016/j.rse.2020.112165_bb0025 – volume: 36 start-page: 129 issue: 2 year: 2010 ident: 10.1016/j.rse.2020.112165_bb0080 article-title: Integration of GLAS and Landsat TM data for aboveground biomass estimation publication-title: Can. J. Remote. Sens. doi: 10.5589/m10-037 – volume: 12 start-page: 426 issue: 3 year: 2020 ident: 10.1016/j.rse.2020.112165_bb0205 article-title: Landsat analysis ready data for global land cover and land cover change mapping publication-title: Remote Sens. doi: 10.3390/rs12030426 – volume: 114 start-page: 11645 issue: 44 year: 2017 ident: 10.1016/j.rse.2020.112165_bb0100 article-title: Natural climate solutions publication-title: Proceedings of the National Academy of Sciences doi: 10.1073/pnas.1710465114 – year: 2016 ident: 10.1016/j.rse.2020.112165_bb0220 – year: 2020 ident: 10.1016/j.rse.2020.112165_bb0070 – volume: 116 start-page: 4021 year: 2011 ident: 10.1016/j.rse.2020.112165_bb0225 article-title: Mapping forest canopy height globally with spaceborne lidar publication-title: Geophys. Res. Lett. doi: 10.1029/2011JG001708 – volume: 10 issue: 7 year: 2015 ident: 10.1016/j.rse.2020.112165_bb0235 article-title: Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012 publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/10/7/074002 – volume: 6 start-page: 12409 issue: 12 year: 2014 ident: 10.1016/j.rse.2020.112165_bb0190 article-title: Mapping forest height in Alaska using GLAS, Landsat composites, and airborne LiDAR publication-title: Remote Sens. doi: 10.3390/rs61212409 – ident: 10.1016/j.rse.2020.112165_bb0180 – volume: 1 start-page: 100002 year: 2020 ident: 10.1016/j.rse.2020.112165_bb0065 article-title: The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography publication-title: Sci. Remote Sens. doi: 10.1016/j.srs.2020.100002 – volume: 6 start-page: 1762 year: 2014 ident: 10.1016/j.rse.2020.112165_bb0175 article-title: Deciphering the precision of stereo IKONOS canopy height models for US forests with G-LiHT airborne LiDAR publication-title: Remote Sens. doi: 10.3390/rs6031762 – volume: 29 start-page: 607 issue: 5 year: 2003 ident: 10.1016/j.rse.2020.112165_bb0160 article-title: Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests publication-title: Can. J. Remote. Sens. doi: 10.5589/m03-026 – volume: 24 start-page: 123 year: 1996 ident: 10.1016/j.rse.2020.112165_bb0030 article-title: Bagging predictors publication-title: Mach. Learn. doi: 10.1023/A:1018054314350 – volume: 116 start-page: 4382 issue: 10 year: 2019 ident: 10.1016/j.rse.2020.112165_bb0210 article-title: Role of forest regrowth in global carbon sink dynamics publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.1810512116 – volume: 31 start-page: 78 issue: 1 year: 2001 ident: 10.1016/j.rse.2020.112165_bb0150 article-title: An evaluation of alternate remote sensing products for forest inventory, monitoring, and mapping of Douglas-fir forests in western Oregon publication-title: Can. J. For. Res. doi: 10.1139/x00-142 – year: 2019 ident: 10.1016/j.rse.2020.112165_bb0115 |
| SSID | ssj0015871 |
| Score | 2.739836 |
| Snippet | Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 112165 |
| SubjectTerms | Canopies canopy height carbon Carbon emissions climate Ecosystem dynamics ecosystems Emissions environment Environmental restoration Forest canopy Forest degradation Forest ecosystems Forest height Forest monitoring forest restoration Forests GEDI Global climate Imagery Integration International Space Station Landsat Landsat satellites Lidar Monitoring Remote sensing Space stations Spatial discrimination Spatial resolution Sustainable development time series analysis Time-series Vegetation |
| Title | Mapping global forest canopy height through integration of GEDI and Landsat data |
| URI | https://dx.doi.org/10.1016/j.rse.2020.112165 https://www.proquest.com/docview/2488247416 https://www.proquest.com/docview/2551937190 |
| Volume | 253 |
| WOSCitedRecordID | wos000604325300005&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-0704 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0015871 issn: 0034-4257 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLbKBoIXBIWJwkBGQjwwBSWOU9uPE3TdUCkTdKhvlpM6UrcpCb1p_SH8X45jOy2bmOCBl6iKnbTy-fr5HJ8bQm8SFSuSChHkkcgCGmXdgMcqC3gK27syO3rXNptgwyEfj8Vpq_XT58KsLllR8KsrUf1XUcM9ELZJnf0HcTcvhRvwGYQOVxA7XP9K8J9VVedAuVIfoJQC8ZvgrrJag15ojPGmO48vFuG0xn7v40ntTRiYBGC1OHCZa436-lWDZPXB3ES922jprUS5hmXLharK1Y3o30EdODCeFuvlBpLH_hw7-KZdflodY9mo-qP18kKtpm7IpuPM1PZhBYl8fLM_QWuyaL5vk3JMA0MddkuyPMyZya2ynYk9UZMk3qJaUBQj22bixi5gDyTO38_mphAqqfOk3NzfK24Pv8ijs8FAjnrj0dvqR2CakRmnvevMcgftEpYIIMvdw5Pe-FPjnko4s60Y3S_37vI6cPDat_5J4bm29df6zOgReugMEXxoAfQYtXTRRnu9jThh0BH_vI3u97Wrbd5G9_p1N-j1E3TqsIYt1rDFGrZYwxZr2GENb2ENlzk2WMMgS-ywhg3WnqKzo97ow3HgWnQEGSV0EegkzNKEUQ52OZ-wSayVYHEadkVE8pBMVAo8IBQNqSI6irXgIhOpmOQkZ0yD-rSHdoqy0M8QZnFXCwIGBKdgolPjPqdpSHIwkBVXSdZBoV9Hmbn69aaNyqX0gYrnEpZemqWXduk76F3zSGWLt9w2mXrhSKd9Wq1SAqxue2zfC1I6FphLAtsiocbY6aDXzTAQt_HGqUKXS5iTGOOJgUL-_PZXvEAPNn-lfbSzmC31S3Q3Wy2m89krB81fJQu3eQ |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Mapping+global+forest+canopy+height+through+integration+of+GEDI+and+Landsat+data&rft.jtitle=Remote+sensing+of+environment&rft.au=Potapov%2C+Peter&rft.au=Li%2C+Xinyuan&rft.au=Hernandez-Serna%2C+Andres&rft.au=Tyukavina%2C+Alexandra&rft.date=2021-02-01&rft.pub=Elsevier+BV&rft.issn=0034-4257&rft.eissn=1879-0704&rft.volume=253&rft.spage=112165&rft_id=info:doi/10.1016%2Fj.rse.2020.112165&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0034-4257&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0034-4257&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0034-4257&client=summon |