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...

Full description

Bibliographic Details
Main Authors: Martyna A. Stelmaszczuk-Górska, Mikhail Urbazaev, Christiane Schmullius, Christian Thiel
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Remote Sensing
Subjects:
SAR
Online Access:http://www.mdpi.com/2072-4292/10/10/1550
id doaj-602eb25b36d14f48b5ee9f87ac4fa412
record_format Article
spelling 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
work_keys_str_mv AT martynaastelmaszczukgorska estimationofabovegroundbiomassoverborealforestsonsiberiausingupdatedinsitualos2palsar2andradarsat2data
AT mikhailurbazaev estimationofabovegroundbiomassoverborealforestsonsiberiausingupdatedinsitualos2palsar2andradarsat2data
AT christianeschmullius estimationofabovegroundbiomassoverborealforestsonsiberiausingupdatedinsitualos2palsar2andradarsat2data
AT christianthiel estimationofabovegroundbiomassoverborealforestsonsiberiausingupdatedinsitualos2palsar2andradarsat2data
_version_ 1726015395104555008