Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model
The semi-empirical Interferometric Water Cloud Model, IWCM, is used to estimate above ground forest biomass, AGB, in northern Sweden, Krycklan (64 degrees N 20 degrees E). The results are based on separate analysis of 14 TanDEM-X ac-quisitions from 2011 to 2014 and a Lidar digital terrain model (DTM...
| Published in: | Remote Sensing of Environment |
|---|---|
| Main Authors: | , , |
| Language: | unknown |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://doi.org/10.1016/j.rse.2017.05.010 https://research.chalmers.se/en/publication/250752 |
| _version_ | 1835018844078342144 |
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| author | Askne, Jan Soja, Maciej Ulander, Lars |
| author_facet | Askne, Jan Soja, Maciej Ulander, Lars |
| author_sort | Askne, Jan |
| collection | Unknown |
| container_start_page | 265 |
| container_title | Remote Sensing of Environment |
| container_volume | 196 |
| description | The semi-empirical Interferometric Water Cloud Model, IWCM, is used to estimate above ground forest biomass, AGB, in northern Sweden, Krycklan (64 degrees N 20 degrees E). The results are based on separate analysis of 14 TanDEM-X ac-quisitions from 2011 to 2014 and a Lidar digital terrain model (DTM). 29 stands covering 272 ha and with AGB 1 ha covering 3166 ha and with AGB |
| genre | Northern Sweden |
| genre_facet | Northern Sweden |
| id | ftchalmersuniv:oai:research.chalmers.se:250752 |
| institution | Open Polar |
| language | unknown |
| op_collection_id | ftchalmersuniv |
| op_container_end_page | 278 |
| op_doi | https://doi.org/10.1016/j.rse.2017.05.010 |
| op_relation | http://dx.doi.org/10.1016/j.rse.2017.05.010 https://research.chalmers.se/en/publication/250752 |
| publishDate | 2017 |
| record_format | openpolar |
| spelling | ftchalmersuniv:oai:research.chalmers.se:250752 2025-06-15T14:44:25+00:00 Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model Askne, Jan Soja, Maciej Ulander, Lars 2017 text https://doi.org/10.1016/j.rse.2017.05.010 https://research.chalmers.se/en/publication/250752 unknown http://dx.doi.org/10.1016/j.rse.2017.05.010 https://research.chalmers.se/en/publication/250752 Remote Sensing Biomass Forest height InSAR Boreal forest TanDEM-X 2017 ftchalmersuniv https://doi.org/10.1016/j.rse.2017.05.010 2025-05-19T04:26:16Z The semi-empirical Interferometric Water Cloud Model, IWCM, is used to estimate above ground forest biomass, AGB, in northern Sweden, Krycklan (64 degrees N 20 degrees E). The results are based on separate analysis of 14 TanDEM-X ac-quisitions from 2011 to 2014 and a Lidar digital terrain model (DTM). 29 stands covering 272 ha and with AGB 1 ha covering 3166 ha and with AGB Other/Unknown Material Northern Sweden Unknown Remote Sensing of Environment 196 265 278 |
| spellingShingle | Remote Sensing Biomass Forest height InSAR Boreal forest TanDEM-X Askne, Jan Soja, Maciej Ulander, Lars Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title | Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title_full | Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title_fullStr | Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title_full_unstemmed | Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title_short | Biomass estimation in a boreal forest from TanDEM-X data, lidar DTM, and the interferometric water cloud model |
| title_sort | biomass estimation in a boreal forest from tandem-x data, lidar dtm, and the interferometric water cloud model |
| topic | Remote Sensing Biomass Forest height InSAR Boreal forest TanDEM-X |
| topic_facet | Remote Sensing Biomass Forest height InSAR Boreal forest TanDEM-X |
| url | https://doi.org/10.1016/j.rse.2017.05.010 https://research.chalmers.se/en/publication/250752 |