Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region
Abstract Global forests are increasingly threatened by disturbance events such as wildfire. Spaceborne Synthetic Aperture Radar (SAR) missions at L‐ (or P‐) band, such as the upcoming NASA ISRO SAR (NISAR), have great potential to advance global mapping of above‐ground biomass (AGB). AGB mapping wit...
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ftdoajarticles:oai:doaj.org/article:421348a508cc489d9edc8451f9b313fe 2023-05-15T16:23:06+02:00 Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region S. Kraatz L. Bourgeau‐Chavez M. Battaglia A. Poley P. Siqueira 2022-12-01T00:00:00Z https://doi.org/10.1029/2022EA002431 https://doaj.org/article/421348a508cc489d9edc8451f9b313fe EN eng American Geophysical Union (AGU) https://doi.org/10.1029/2022EA002431 https://doaj.org/toc/2333-5084 2333-5084 doi:10.1029/2022EA002431 https://doaj.org/article/421348a508cc489d9edc8451f9b313fe Earth and Space Science, Vol 9, Iss 12, Pp n/a-n/a (2022) above NISAR biomass Astronomy QB1-991 Geology QE1-996.5 article 2022 ftdoajarticles https://doi.org/10.1029/2022EA002431 2022-12-30T19:26:28Z Abstract Global forests are increasingly threatened by disturbance events such as wildfire. Spaceborne Synthetic Aperture Radar (SAR) missions at L‐ (or P‐) band, such as the upcoming NASA ISRO SAR (NISAR), have great potential to advance global mapping of above‐ground biomass (AGB). AGB mapping with SAR is challenging due to lack of available L‐ or P‐ band data, and because SAR data are sensitive to confounding factors such as hydrology and terrain. This study uses recently collected AGB validation site data (AGBV) to produce a 1 ha biomass map about the Great Slave Lake in Canada using SAR data, and reports on NISAR's anticipated performance. This study addresses errors inherent to the representativeness of AGBVs with coarser grid/landscape scale processes by evaluating model performance as data are aggregated over increasingly larger areas (AOAs). Air and spaceborne SAR data were found to be interoperable after processing them according to analysis ready data specifications, improving data availability. Owing to poor model performance at two AGBVs, root‐mean‐square errors (RMSEs) were ∼60 Mg/ha, irrespective of AOA. When instead using NISAR's more lenient assessment criteria, RMSEs decreased to 32, 15, and 21 Mg/ha for the small (∼0.1 ha), medium (∼3.5 ha), and large (∼14 ha) AOA. Thus, AGB mapping in this region appears to benefit significantly from coarser data aggregations than to be used by NISAR's. This approach is practical for identifying a suitable scale of correspondence between the AGBV and SAR data and the landscape‐scale processes and can substantially improve AGB mapping accuracy. Article in Journal/Newspaper Great Slave Lake Directory of Open Access Journals: DOAJ Articles Canada Great Slave Lake ENVELOPE(-114.001,-114.001,61.500,61.500) Earth and Space Science 9 12 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
above NISAR biomass Astronomy QB1-991 Geology QE1-996.5 |
spellingShingle |
above NISAR biomass Astronomy QB1-991 Geology QE1-996.5 S. Kraatz L. Bourgeau‐Chavez M. Battaglia A. Poley P. Siqueira Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
topic_facet |
above NISAR biomass Astronomy QB1-991 Geology QE1-996.5 |
description |
Abstract Global forests are increasingly threatened by disturbance events such as wildfire. Spaceborne Synthetic Aperture Radar (SAR) missions at L‐ (or P‐) band, such as the upcoming NASA ISRO SAR (NISAR), have great potential to advance global mapping of above‐ground biomass (AGB). AGB mapping with SAR is challenging due to lack of available L‐ or P‐ band data, and because SAR data are sensitive to confounding factors such as hydrology and terrain. This study uses recently collected AGB validation site data (AGBV) to produce a 1 ha biomass map about the Great Slave Lake in Canada using SAR data, and reports on NISAR's anticipated performance. This study addresses errors inherent to the representativeness of AGBVs with coarser grid/landscape scale processes by evaluating model performance as data are aggregated over increasingly larger areas (AOAs). Air and spaceborne SAR data were found to be interoperable after processing them according to analysis ready data specifications, improving data availability. Owing to poor model performance at two AGBVs, root‐mean‐square errors (RMSEs) were ∼60 Mg/ha, irrespective of AOA. When instead using NISAR's more lenient assessment criteria, RMSEs decreased to 32, 15, and 21 Mg/ha for the small (∼0.1 ha), medium (∼3.5 ha), and large (∼14 ha) AOA. Thus, AGB mapping in this region appears to benefit significantly from coarser data aggregations than to be used by NISAR's. This approach is practical for identifying a suitable scale of correspondence between the AGBV and SAR data and the landscape‐scale processes and can substantially improve AGB mapping accuracy. |
format |
Article in Journal/Newspaper |
author |
S. Kraatz L. Bourgeau‐Chavez M. Battaglia A. Poley P. Siqueira |
author_facet |
S. Kraatz L. Bourgeau‐Chavez M. Battaglia A. Poley P. Siqueira |
author_sort |
S. Kraatz |
title |
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
title_short |
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
title_full |
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
title_fullStr |
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
title_full_unstemmed |
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region |
title_sort |
mapping and scaling of in situ above ground biomass to regional extent with sar in the great slave region |
publisher |
American Geophysical Union (AGU) |
publishDate |
2022 |
url |
https://doi.org/10.1029/2022EA002431 https://doaj.org/article/421348a508cc489d9edc8451f9b313fe |
long_lat |
ENVELOPE(-114.001,-114.001,61.500,61.500) |
geographic |
Canada Great Slave Lake |
geographic_facet |
Canada Great Slave Lake |
genre |
Great Slave Lake |
genre_facet |
Great Slave Lake |
op_source |
Earth and Space Science, Vol 9, Iss 12, Pp n/a-n/a (2022) |
op_relation |
https://doi.org/10.1029/2022EA002431 https://doaj.org/toc/2333-5084 2333-5084 doi:10.1029/2022EA002431 https://doaj.org/article/421348a508cc489d9edc8451f9b313fe |
op_doi |
https://doi.org/10.1029/2022EA002431 |
container_title |
Earth and Space Science |
container_volume |
9 |
container_issue |
12 |
_version_ |
1766011288544083968 |