{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T07:29:20Z","timestamp":1761290960126,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2012,10,1]],"date-time":"2012-10-01T00:00:00Z","timestamp":1349049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 ENIVSAT 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.<\/jats:p>","DOI":"10.3390\/rs4102923","type":"journal-article","created":{"date-parts":[[2012,10,2]],"date-time":"2012-10-02T02:39:08Z","timestamp":1349145548000},"page":"2923-2943","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes"],"prefix":"10.3390","volume":"4","author":[{"given":"Julia","family":"Reschke","sequence":"first","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Gusshausstrasse 27-29, Vienna 1040, Austria"}]},{"given":"Annett","family":"Bartsch","sequence":"additional","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Gusshausstrasse 27-29, Vienna 1040, Austria"}]},{"given":"Stefan","family":"Schlaffer","sequence":"additional","affiliation":[{"name":"Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Gusshausstrasse 27-29, Vienna 1040, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7814-4990","authenticated-orcid":false,"given":"Dmitry","family":"Schepaschenko","sequence":"additional","affiliation":[{"name":"Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg 2361, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2012,10,1]]},"reference":[{"key":"ref_1","first-page":"1733","article-title":"Barriers to predicting changes in global terrestrial methane fluxes: Analyses using CLM 4 Me, a methane biogeochemistry model integrated in CESM","volume":"8","author":"Riley","year":"2011","journal-title":"Biogeosci. 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