Capability of C-band SAR for operational wetland monitoring at high latitudes
Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. F...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Molecular Diversity Preservation International (MDPI)
2012
|
Subjects: | |
Online Access: | https://pure.iiasa.ac.at/id/eprint/9985/ https://pure.iiasa.ac.at/id/eprint/9985/1/remotesensing-04-02923.pdf https://doi.org/10.3390/rs4102923 |
id |
ftiiasalaxenburg:oai:pure.iiasa.ac.at:9985 |
---|---|
record_format |
openpolar |
spelling |
ftiiasalaxenburg:oai:pure.iiasa.ac.at:9985 2024-02-04T10:03:51+01:00 Capability of C-band SAR for operational wetland monitoring at high latitudes Reschke, J. Bartsch, A. Schlaffer, S. Schepaschenko, D. 2012-10 text https://pure.iiasa.ac.at/id/eprint/9985/ https://pure.iiasa.ac.at/id/eprint/9985/1/remotesensing-04-02923.pdf https://doi.org/10.3390/rs4102923 en eng Molecular Diversity Preservation International (MDPI) https://pure.iiasa.ac.at/id/eprint/9985/1/remotesensing-04-02923.pdf Reschke, J., Bartsch, A., Schlaffer, S., & Schepaschenko, D. <https://pure.iiasa.ac.at/view/iiasa/279.html> orcid:0000-0002-7814-4990 (2012). Capability of C-band SAR for operational wetland monitoring at high latitudes. Remote Sensing 4 (10) 2923-2943. 10.3390/rs4102923 <https://doi.org/10.3390/rs4102923>. doi:10.3390/rs4102923 cc_by Article PeerReviewed 2012 ftiiasalaxenburg https://doi.org/10.3390/rs4102923 2024-01-08T00:34:56Z Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENVISAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007 and 2008. The area identified with this method amounts to approximately 300,000 km2 in northern Siberia in 2007. It overlaps with zones of high carbon storage. Comparison with a range of related datasets (static and dynamic) showed that hSW represents not only peatlands but also temporary wetlands associated with post-forest fire conditions in permafrost regions. Annual long-term monitoring of change in boreal and tundra environments is possible with the presented approach. Sentinel-1, the successor of ENVISAT ASAR, will provide data that may allow continuous monitoring of these wetland dynamics in the future complementing global observations of wetland fraction. Article in Journal/Newspaper permafrost Tundra Siberia IIASA PURE (International Institute of Applied Systems Analysis: PUblications REpository) Asar ENVELOPE(134.033,134.033,68.667,68.667) Remote Sensing 4 10 2923 2943 |
institution |
Open Polar |
collection |
IIASA PURE (International Institute of Applied Systems Analysis: PUblications REpository) |
op_collection_id |
ftiiasalaxenburg |
language |
English |
description |
Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENVISAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007 and 2008. The area identified with this method amounts to approximately 300,000 km2 in northern Siberia in 2007. It overlaps with zones of high carbon storage. Comparison with a range of related datasets (static and dynamic) showed that hSW represents not only peatlands but also temporary wetlands associated with post-forest fire conditions in permafrost regions. Annual long-term monitoring of change in boreal and tundra environments is possible with the presented approach. Sentinel-1, the successor of ENVISAT ASAR, will provide data that may allow continuous monitoring of these wetland dynamics in the future complementing global observations of wetland fraction. |
format |
Article in Journal/Newspaper |
author |
Reschke, J. Bartsch, A. Schlaffer, S. Schepaschenko, D. |
spellingShingle |
Reschke, J. Bartsch, A. Schlaffer, S. Schepaschenko, D. Capability of C-band SAR for operational wetland monitoring at high latitudes |
author_facet |
Reschke, J. Bartsch, A. Schlaffer, S. Schepaschenko, D. |
author_sort |
Reschke, J. |
title |
Capability of C-band SAR for operational wetland monitoring at high latitudes |
title_short |
Capability of C-band SAR for operational wetland monitoring at high latitudes |
title_full |
Capability of C-band SAR for operational wetland monitoring at high latitudes |
title_fullStr |
Capability of C-band SAR for operational wetland monitoring at high latitudes |
title_full_unstemmed |
Capability of C-band SAR for operational wetland monitoring at high latitudes |
title_sort |
capability of c-band sar for operational wetland monitoring at high latitudes |
publisher |
Molecular Diversity Preservation International (MDPI) |
publishDate |
2012 |
url |
https://pure.iiasa.ac.at/id/eprint/9985/ https://pure.iiasa.ac.at/id/eprint/9985/1/remotesensing-04-02923.pdf https://doi.org/10.3390/rs4102923 |
long_lat |
ENVELOPE(134.033,134.033,68.667,68.667) |
geographic |
Asar |
geographic_facet |
Asar |
genre |
permafrost Tundra Siberia |
genre_facet |
permafrost Tundra Siberia |
op_relation |
https://pure.iiasa.ac.at/id/eprint/9985/1/remotesensing-04-02923.pdf Reschke, J., Bartsch, A., Schlaffer, S., & Schepaschenko, D. <https://pure.iiasa.ac.at/view/iiasa/279.html> orcid:0000-0002-7814-4990 (2012). Capability of C-band SAR for operational wetland monitoring at high latitudes. Remote Sensing 4 (10) 2923-2943. 10.3390/rs4102923 <https://doi.org/10.3390/rs4102923>. doi:10.3390/rs4102923 |
op_rights |
cc_by |
op_doi |
https://doi.org/10.3390/rs4102923 |
container_title |
Remote Sensing |
container_volume |
4 |
container_issue |
10 |
container_start_page |
2923 |
op_container_end_page |
2943 |
_version_ |
1789971641342623744 |