Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data
The estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. In particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This...
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doaj-602eb25b36d14f48b5ee9f87ac4fa4122020-11-24T21:16:50ZengMDPI AGRemote Sensing2072-42922018-09-011010155010.3390/rs10101550rs10101550Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 DataMartyna A. Stelmaszczuk-Górska0Mikhail Urbazaev1Christiane Schmullius2Christian Thiel3Department for Earth Observation, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, GermanyDepartment for Earth Observation, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, GermanyDepartment for Earth Observation, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, GermanyDepartment for Earth Observation, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, GermanyThe estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. In particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This study explores the combination of multi-frequency, multi-polarization, and multi-temporal radar data as one key approach to provide an accurate estimate of forest biomass. The data from L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-Band Synthetic Aperture Radar 2 (PALSAR-2), together with C-band RADARSAT-2 data, were applied for AGB estimation. Backscatter coefficients from L- and C-band radar were used independently and in combination with a non-parametric model to retrieve AGB data for a boreal forest in Siberia (Krasnoyarskiy Kray). AGB estimation was performed using the random forests machine learning algorithm. The results demonstrated that high estimation accuracies can be achieved at a spatial resolution of 0.25 ha. When the L-band data alone were used for the retrieval, a corrected root-mean-square error (RMSEcor) of 29.4 t ha−1 was calculated. A marginal decrease in RMSEcor was observed when only the filtered L-band backscatter data, without ratio and texture, were used (29.1 t ha−1). The inclusion of the C-band data reduced the over and underestimation; the bias was reduced from 5.5 t ha−1 to 4.7 t ha−1; and a RMSEcor of 30.2 t ha−1 was calculated.http://www.mdpi.com/2072-4292/10/10/1550SARboreal forestabove-ground biomassbackscatterALOS-2 PALSAR-2RADARSAT-2 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Martyna A. Stelmaszczuk-Górska Mikhail Urbazaev Christiane Schmullius Christian Thiel |
spellingShingle |
Martyna A. Stelmaszczuk-Górska Mikhail Urbazaev Christiane Schmullius Christian Thiel Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data Remote Sensing SAR boreal forest above-ground biomass backscatter ALOS-2 PALSAR-2 RADARSAT-2 |
author_facet |
Martyna A. Stelmaszczuk-Górska Mikhail Urbazaev Christiane Schmullius Christian Thiel |
author_sort |
Martyna A. Stelmaszczuk-Górska |
title |
Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
title_short |
Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
title_full |
Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
title_fullStr |
Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
title_full_unstemmed |
Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data |
title_sort |
estimation of above-ground biomass over boreal forests on siberia using updated in situ, alos-2 palsar-2, and radarsat-2 data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-09-01 |
description |
The estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. In particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This study explores the combination of multi-frequency, multi-polarization, and multi-temporal radar data as one key approach to provide an accurate estimate of forest biomass. The data from L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-Band Synthetic Aperture Radar 2 (PALSAR-2), together with C-band RADARSAT-2 data, were applied for AGB estimation. Backscatter coefficients from L- and C-band radar were used independently and in combination with a non-parametric model to retrieve AGB data for a boreal forest in Siberia (Krasnoyarskiy Kray). AGB estimation was performed using the random forests machine learning algorithm. The results demonstrated that high estimation accuracies can be achieved at a spatial resolution of 0.25 ha. When the L-band data alone were used for the retrieval, a corrected root-mean-square error (RMSEcor) of 29.4 t ha−1 was calculated. A marginal decrease in RMSEcor was observed when only the filtered L-band backscatter data, without ratio and texture, were used (29.1 t ha−1). The inclusion of the C-band data reduced the over and underestimation; the bias was reduced from 5.5 t ha−1 to 4.7 t ha−1; and a RMSEcor of 30.2 t ha−1 was calculated. |
topic |
SAR boreal forest above-ground biomass backscatter ALOS-2 PALSAR-2 RADARSAT-2 |
url |
http://www.mdpi.com/2072-4292/10/10/1550 |
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