A Review of Wetland Remote Sensing
Обзор дистанционного зондирования водно-болотных угодий
2017-04-05
SCID: 54.1/4bf2fac8
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LiDAR datahyperspectral imagerywater qualitywetland classificationwetland remote sensing
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Abstract (AI)
Wetlands are some of the most important ecosystems on Earth. They play a key role in alleviating floods and filtering polluted water and also provide habitats for many plants and animals. Wetlands also interact with climate change. Over the past 50 years, wetlands have been polluted and declined dramatically as land cover has changed in some regions. Remote sensing has been the most useful tool to acquire spatial and temporal information about wetlands. In this paper, seven types of sensors were reviewed: aerial photos coarse-resolution, medium-resolution, high-resolution, hyperspectral imagery, radar, and Light Detection and Ranging (LiDAR) data. This study also discusses the advantage of each sensor for wetland research. Wetland research themes reviewed in this paper include wetland classification, habitat or biodiversity, biomass estimation, plant leaf chemistry, water quality, mangrove forest, and sea level rise. This study also gives an overview of the methods used in wetland research such as supervised and unsupervised classification and decision tree and object-based classification. Finally, this paper provides some advice on future wetland remote sensing. To our knowledge, this paper is the most comprehensive and detailed review of wetland remote sensing and it will be a good reference for wetland researchers.
Key Findings
1
Remote sensing is identified as the most useful tool for obtaining spatial and temporal information about wetlands.
2
The review covers seven sensor categories, including aerial photography, multiple spatial resolutions, hyperspectral imagery, radar, and LiDAR, and discusses their respective advantages.
3
The review synthesizes commonly used analytical methods, including supervised and unsupervised classification, decision trees, and object-based classification, while offering guidance for future research.
4
Wetland remote-sensing applications span classification, habitat and biodiversity assessment, biomass estimation, plant leaf chemistry, water quality, mangrove forests, and sea-level rise.
5
Wetlands provide critical flood mitigation, water purification, biodiversity habitat, and climate-related ecosystem functions, but have declined dramatically in some regions over the past 50 years.
Research Object
wetlands
Research Subject
remote-sensing-based spatial and temporal information acquisition and characterization of wetlands, including classification, habitat and biodiversity, biomass, plant leaf chemistry, water quality, mangrove forests, and sea-level-rise impacts
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2017-04-05
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