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  • 标题:Mapping wetlands in Indonesia using Landsat and PALSAR data-sets and derived topographical indices
  • 本地全文:下载
  • 作者:Belinda A. Margono ; Jean-Robert B. Bwangoy ; Peter V. Potapov
  • 期刊名称:Geo-spatial Information Science
  • 印刷版ISSN:1009-5020
  • 电子版ISSN:1993-5153
  • 出版年度:2014
  • 卷号:17
  • 期号:1
  • 页码:60-71
  • DOI:10.1080/10095020.2014.898560
  • 出版社:Taylor and Francis Ltd
  • 摘要:Wetlands play an important role in the provision of ecosystem services, ranging from the regulation of hydrological systems to carbon sequestration and biodiversity habitat. This paper reports the mapping of Indonesia’s wetland cover as a single thematic class, including peatlands, freshwater wetlands, and mangroves. Expert-interpreted training data were used to identify wetland formations including areas of likely past wetland extent that have been converted to other land uses. Topographical indices (Shuttle Radar Topography Mission-derived) and optical (Landsat) and radar (PALSAR) image inputs were used to build a bagged classification tree model based on training data in order to generate a national-scale map of wetland extent at a 60 m spatial resolution. The resulting wetland map covers 21.0% (39.6 Mha) of Indonesia’s land, including 25.2% of Sumatra (11.9 Mha), 22.9% of Kalimantan (12.2 Mha), and 28.9% of Papua (11.8 Mha). Results agree with existing image-interpreted products from Indonesia’s Ministries of Forestry and Agriculture and Wetlands International (89% overall agreement), and with the Ministry of Forestry forest inventory data for Sumatra and Kalimantan (91% overall agreement). An internally consistent algorithm-derived national wetland extent map can be used to quantify changing rates of land conversion inside and outside of wetlands. Additionally, wetlands extent can be used to efficiently allocate field resources in national assessments of wetland sub-types such as peatlands, which are a current focus of policies aiming to reduce carbon emissions from land use change.
  • 关键词:wetlands; Indonesia; remote sensing; Landsat; digital elevation model \(DEM\); PALSAR; Shuttle Radar Topography Mission \(SRTM\)
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