How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass?
The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Varvia, P. [verfasserIn] Korhonen, L. [verfasserIn] Bruguière, A. [verfasserIn] Toivonen, J. [verfasserIn] Packalen, P. [verfasserIn] Maltamo, M. [verfasserIn] Saarela, S. [verfasserIn] Popescu, S.C. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Remote sensing of environment - Amsterdam [u.a.] : Elsevier Science, 1969, 280 |
|---|---|
| Übergeordnetes Werk: |
volume:280 |
| DOI / URN: |
10.1016/j.rse.2022.113174 |
|---|
| Katalog-ID: |
ELV008460523 |
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| 245 | 1 | 0 | |a How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? |
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| 520 | |a The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. | ||
| 650 | 4 | |a ICESat-2 | |
| 650 | 4 | |a Above-ground biomass | |
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| 700 | 1 | |a Bruguière, A. |e verfasserin |4 aut | |
| 700 | 1 | |a Toivonen, J. |e verfasserin |0 (orcid)0000-0003-1319-3035 |4 aut | |
| 700 | 1 | |a Packalen, P. |e verfasserin |4 aut | |
| 700 | 1 | |a Maltamo, M. |e verfasserin |4 aut | |
| 700 | 1 | |a Saarela, S. |e verfasserin |0 (orcid)0000-0002-9044-7249 |4 aut | |
| 700 | 1 | |a Popescu, S.C. |e verfasserin |0 (orcid)0000-0002-8155-8801 |4 aut | |
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10.1016/j.rse.2022.113174 doi (DE-627)ELV008460523 (ELSEVIER)S0034-4257(22)00287-5 DE-627 ger DE-627 rda eng 050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl Varvia, P. verfasserin (orcid)0000-0001-5323-9128 aut How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar Korhonen, L. verfasserin aut Bruguière, A. verfasserin aut Toivonen, J. verfasserin (orcid)0000-0003-1319-3035 aut Packalen, P. verfasserin aut Maltamo, M. verfasserin aut Saarela, S. verfasserin (orcid)0000-0002-9044-7249 aut Popescu, S.C. verfasserin (orcid)0000-0002-8155-8801 aut Enthalten in Remote sensing of environment Amsterdam [u.a.] : Elsevier Science, 1969 280 Online-Ressource (DE-627)306591324 (DE-600)1498713-2 (DE-576)098330268 1879-0704 nnns volume:280 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.03 Methoden und Techniken der Geowissenschaften 43.03 Methoden der Umweltforschung und des Umweltschutzes 74.41 Luftaufnahmen Photogrammetrie AR 280 |
| spelling |
10.1016/j.rse.2022.113174 doi (DE-627)ELV008460523 (ELSEVIER)S0034-4257(22)00287-5 DE-627 ger DE-627 rda eng 050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl Varvia, P. verfasserin (orcid)0000-0001-5323-9128 aut How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar Korhonen, L. verfasserin aut Bruguière, A. verfasserin aut Toivonen, J. verfasserin (orcid)0000-0003-1319-3035 aut Packalen, P. verfasserin aut Maltamo, M. verfasserin aut Saarela, S. verfasserin (orcid)0000-0002-9044-7249 aut Popescu, S.C. verfasserin (orcid)0000-0002-8155-8801 aut Enthalten in Remote sensing of environment Amsterdam [u.a.] : Elsevier Science, 1969 280 Online-Ressource (DE-627)306591324 (DE-600)1498713-2 (DE-576)098330268 1879-0704 nnns volume:280 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.03 Methoden und Techniken der Geowissenschaften 43.03 Methoden der Umweltforschung und des Umweltschutzes 74.41 Luftaufnahmen Photogrammetrie AR 280 |
| allfields_unstemmed |
10.1016/j.rse.2022.113174 doi (DE-627)ELV008460523 (ELSEVIER)S0034-4257(22)00287-5 DE-627 ger DE-627 rda eng 050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl Varvia, P. verfasserin (orcid)0000-0001-5323-9128 aut How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar Korhonen, L. verfasserin aut Bruguière, A. verfasserin aut Toivonen, J. verfasserin (orcid)0000-0003-1319-3035 aut Packalen, P. verfasserin aut Maltamo, M. verfasserin aut Saarela, S. verfasserin (orcid)0000-0002-9044-7249 aut Popescu, S.C. verfasserin (orcid)0000-0002-8155-8801 aut Enthalten in Remote sensing of environment Amsterdam [u.a.] : Elsevier Science, 1969 280 Online-Ressource (DE-627)306591324 (DE-600)1498713-2 (DE-576)098330268 1879-0704 nnns volume:280 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.03 Methoden und Techniken der Geowissenschaften 43.03 Methoden der Umweltforschung und des Umweltschutzes 74.41 Luftaufnahmen Photogrammetrie AR 280 |
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10.1016/j.rse.2022.113174 doi (DE-627)ELV008460523 (ELSEVIER)S0034-4257(22)00287-5 DE-627 ger DE-627 rda eng 050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl Varvia, P. verfasserin (orcid)0000-0001-5323-9128 aut How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar Korhonen, L. verfasserin aut Bruguière, A. verfasserin aut Toivonen, J. verfasserin (orcid)0000-0003-1319-3035 aut Packalen, P. verfasserin aut Maltamo, M. verfasserin aut Saarela, S. verfasserin (orcid)0000-0002-9044-7249 aut Popescu, S.C. verfasserin (orcid)0000-0002-8155-8801 aut Enthalten in Remote sensing of environment Amsterdam [u.a.] : Elsevier Science, 1969 280 Online-Ressource (DE-627)306591324 (DE-600)1498713-2 (DE-576)098330268 1879-0704 nnns volume:280 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.03 Methoden und Techniken der Geowissenschaften 43.03 Methoden der Umweltforschung und des Umweltschutzes 74.41 Luftaufnahmen Photogrammetrie AR 280 |
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10.1016/j.rse.2022.113174 doi (DE-627)ELV008460523 (ELSEVIER)S0034-4257(22)00287-5 DE-627 ger DE-627 rda eng 050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl Varvia, P. verfasserin (orcid)0000-0001-5323-9128 aut How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar Korhonen, L. verfasserin aut Bruguière, A. verfasserin aut Toivonen, J. verfasserin (orcid)0000-0003-1319-3035 aut Packalen, P. verfasserin aut Maltamo, M. verfasserin aut Saarela, S. verfasserin (orcid)0000-0002-9044-7249 aut Popescu, S.C. verfasserin (orcid)0000-0002-8155-8801 aut Enthalten in Remote sensing of environment Amsterdam [u.a.] : Elsevier Science, 1969 280 Online-Ressource (DE-627)306591324 (DE-600)1498713-2 (DE-576)098330268 1879-0704 nnns volume:280 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 38.03 Methoden und Techniken der Geowissenschaften 43.03 Methoden der Umweltforschung und des Umweltschutzes 74.41 Luftaufnahmen Photogrammetrie AR 280 |
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050 550 DE-600 38.03 bkl 43.03 bkl 74.41 bkl How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? ICESat-2 Above-ground biomass Boreal forest Mixed-effect models Lidar |
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How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? |
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How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? |
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Varvia, P. Korhonen, L. Bruguière, A. Toivonen, J. Packalen, P. Maltamo, M. Saarela, S. Popescu, S.C. |
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how to consider the effects of time of day, beam strength, and snow cover in icesat-2 based estimation of boreal forest biomass? |
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How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? |
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The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. |
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The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. |
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The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions. |
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