Basics of Remote Sensing Techniques Applicable in Wetlands Ecosystems

Chakraborty, Susanta Kumar; Sanyal, Poulomi; Ray, Ratnadeep

doi:10.1007/978-3-031-09253-4_6

Cited by 2 publications

(2 citation statements)

References 130 publications

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“…In recent years, RS for wetland research has become a focal point, with numerous scholars and institutions worldwide conducting studies across various regions and scales [17][18][19]. These investigations, to varying degrees, reflect the diversity and complexity of wetlands.…”

Section: Introductionmentioning

confidence: 99%

“…Nonetheless, the wetlands are still in a degraded state, which is the result of complex interactions between climate change and human activities [22]. Exploring the transformation of natural and artificial wetlands at the Yangtze River estuary, a vital hub for biodiversity and ecosystem services, Chen et al, [17] detected substantial changes. Over the period from 1960 to 2015, they noted a remarkable reduction of natural wetland area of 574.3 km 2 , counterbalanced by a corresponding expansion of artificial wetland area by 553.6 km 2 .…”

Section: Introductionmentioning

confidence: 99%

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

Luo,

Samat,

Abuduwaili

et al. 2023

Geosciences

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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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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%