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Review
. 2017 Apr 5;17(4):777.
doi: 10.3390/s17040777.

A Review of Wetland Remote Sensing

Meng Guo  1 , Jing Li  2 , Chunlei Sheng  3 , Jiawei Xu  4 , Li Wu  5
Affiliations
Review

A Review of Wetland Remote Sensing

Meng Guo et al. Sensors (Basel). .

Abstract

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.

Keywords: LiDAR; optical sensor; radar; remote sensing; wetland.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Number of wetland remote sensing publications and the ratio of wetland remote sensing to wetland research from 1964 to 2015.
Figure 2
Figure 2
Zhalong Nature Reserve images (a) Landsat2 MSS on 1977183, RGB = 321; (b) Landsat5 TM on 1985194, RGB = 432; (c) Landsat 7 ETM+ on 2002185, RGB = 432 and (d) Landsat 8 OLI on 2016200, RGB = 543.
Figure 2
Figure 2
Zhalong Nature Reserve images (a) Landsat2 MSS on 1977183, RGB = 321; (b) Landsat5 TM on 1985194, RGB = 432; (c) Landsat 7 ETM+ on 2002185, RGB = 432 and (d) Landsat 8 OLI on 2016200, RGB = 543.
See this image and copyright information in PMC

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