Evaluation of Remote Sensing Products for Wetland Mapping in the Irtysh River Basin

被引:1
|
作者
Luo, Kaiyue [1 ,2 ,3 ]
Samat, Alim [2 ,3 ,4 ]
Abuduwaili, Jilili [2 ,3 ,4 ]
Li, Wenbo [2 ,3 ,4 ]
机构
[1] Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi 830046, Peoples R China
[2] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Key Lab Ecol Safety & Sustainable Dev Arid Lands, Urumqi 830011, Peoples R China
[3] Chinese Acad Sci, Res Ctr Ecol & Environm Cent Asia, Urumqi 830011, Peoples R China
[4] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
关键词
wetland; remote sensing; spatial and temporal distribution; consistency analysis; Irtysh River Basin; LONG-TERM; CLASSIFICATION; ACCURACY; SYSTEM; TRENDS; AREA;
D O I
10.3390/geosciences14010014
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
As a transboundary river with rich and unique wetland types, the Irtysh River faces various challenges and threats from human activities and climate change, which affect area, type, and function of wetland. To accurately obtain information on the spatial and temporal distribution of wetlands in this basin, this study compares and evaluates the consistency and accuracy of a total of eleven remote sensing (RS) based land use/land cover (LULC), and wetland products. The information extraction effect of each RS product was examined through methods such as wetland area and type description, thematic map comparison, and similarity coefficient and Kappa coefficient calculations, which can reflect the wetland distribution characteristics and differences among the RS products in the Irtysh River Basin. The results show that although there is a consensus among the products in the major wetland distribution areas, there are still obvious deviations in detail depiction due to differences in factors such as data sources and methods. The products of Global 30 m Wetland Fine Classification Data (GWL_FCS30) and Global 30 m Land Cover Data (GLC_FCS30-2020) released by the Institute of Space and Astronautical Information Innovation (ISAI) of the Chinese Academy of Sciences (CAS) have a clear advantage in extracting spatial morphology features of wetlands due to the use of multi-source data, while the Esri Global 10 m Land Cover Data (ESRI_Global-LULC_10m) and products such as the global 10 m land cover data (FROM_GLC10_2017) from Tsinghua University have higher classification consistency. Moreover, data resolution, classification scheme design, and validation methods are key factors affecting the quality of wetland information extraction in the Irtysh River Basin. In practical terms, the findings of this study hold significant implications for informed decision-making in wetland conservation and management within the Irtysh River Basin. By advancing wetland monitoring technologies and addressing critical considerations in information extraction, this research effectively bridges the gap between remote sensing technology and practical applications, offering valuable insights for regional wetland protection efforts.
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页数:23
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