ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING
The forest biomass is one of the most important parameters for the global carbon stock. Information on the forest volume, coverage and biomass are important to develop the global perspective on the CO<sub>2</sub> concentration changes. Objective of this research is to estimate forest bio...
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5-W3/7/2019/isprs-archives-XLII-5-W3-7-2019.pdf |
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doaj-a0a9ba20cef64b30ae6de7a39674f7ad2020-11-25T01:13:56ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-12-01XLII-5-W371210.5194/isprs-archives-XLII-5-W3-7-2019ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSINGT. Altanchimeg0T. Altanchimeg1T. Renchin2P. De Maeyer3E. Natsagdorj4B. Tseveen5B. Norov6NUM-ITC-UNESCO Laboratory for Space Science and Remote Sensing, National University of Mongolia, Ulaanbaatar, MongoliaDepartment of Environmental and Forest Engineering, National University of Mongolia, Ulaanbaatar, MongoliaNUM-ITC-UNESCO Laboratory for Space Science and Remote Sensing, National University of Mongolia, Ulaanbaatar, MongoliaDepartment of Geography, Faculty of Sciences, Ghent University, BelgiumNUM-ITC-UNESCO Laboratory for Space Science and Remote Sensing, National University of Mongolia, Ulaanbaatar, MongoliaDepartment of Environmental and Forest Engineering, National University of Mongolia, Ulaanbaatar, MongoliaLaboratory for Geo mineralization, Mongolian National University (MNU), MongoliaThe forest biomass is one of the most important parameters for the global carbon stock. Information on the forest volume, coverage and biomass are important to develop the global perspective on the CO<sub>2</sub> concentration changes. Objective of this research is to estimate forest biomass in the study area. The study area is Hangal sum, Bulgan province, Mongolia. Backscatter coefficients for vertical transmit and vertical receive (VV), for vertical transmit and horizontal receive (VH) from Sentinel data and Leaf Area Index (LAI) from Landsat data were used in the study area. We developed biomass estimation approach using ground truth data which is DBH, height and soil moisture. The coefficient α, β, δ, γ were found from the approach. The output map from the approach was compared with VV and VH, LAI data. The relationship between output map and VH data shows a positive result R<sup>2</sup> = 0.61. This study suggests that the biomass estimation using Remote sensing data can be applied in forest region in the North.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5-W3/7/2019/isprs-archives-XLII-5-W3-7-2019.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
T. Altanchimeg T. Altanchimeg T. Renchin P. De Maeyer E. Natsagdorj B. Tseveen B. Norov |
spellingShingle |
T. Altanchimeg T. Altanchimeg T. Renchin P. De Maeyer E. Natsagdorj B. Tseveen B. Norov ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
T. Altanchimeg T. Altanchimeg T. Renchin P. De Maeyer E. Natsagdorj B. Tseveen B. Norov |
author_sort |
T. Altanchimeg |
title |
ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING |
title_short |
ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING |
title_full |
ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING |
title_fullStr |
ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING |
title_full_unstemmed |
ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING |
title_sort |
estimation methodology for forest biomass in mongolia using remote sensing |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2019-12-01 |
description |
The forest biomass is one of the most important parameters for the global carbon stock. Information on the forest volume, coverage and biomass are important to develop the global perspective on the CO<sub>2</sub> concentration changes. Objective of this research is to estimate forest biomass in the study area. The study area is Hangal sum, Bulgan province, Mongolia. Backscatter coefficients for vertical transmit and vertical receive (VV), for vertical transmit and horizontal receive (VH) from Sentinel data and Leaf Area Index (LAI) from Landsat data were used in the study area. We developed biomass estimation approach using ground truth data which is DBH, height and soil moisture. The coefficient α, β, δ, γ were found from the approach. The output map from the approach was compared with VV and VH, LAI data. The relationship between output map and VH data shows a positive result R<sup>2</sup> = 0.61. This study suggests that the biomass estimation using Remote sensing data can be applied in forest region in the North. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-5-W3/7/2019/isprs-archives-XLII-5-W3-7-2019.pdf |
work_keys_str_mv |
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