Satellite remote sensing of wetlands

被引：836

作者：

Ozesmi S.L. ^{[1
,2
]}

Bauer M.E. ^{[1
]}

机构：

[1] Department of Forest Resources, University of Minnesota, St Paul

[2] Environmental Engineering Department, Environmental Science Branch, Erciyes Univ. School of Engineering

来源：

Wetlands Ecology and Management | 2002年 / 10卷 / 5期

关键词：

Classification techniques; Comparison of methods; Remote sensing; Satellite imagery; Wetland classification; Wetland identification; Wetlands; Wetlands inventory;

D O I：

10.1023/A:1020908432489

中图分类号：

学科分类号：

摘要：

To conserve and manage wetland resources, it is important to inventory and monitor wetlands and their adjacent uplands. Satellite remote sensing has several advantages for monitoring wetland resources, especially for large geographic areas: This review summarizes the literature on satellite remote sensing of wetlands, including what classification techniques were most successful in identifying wetlands and separating them from other land cover types. All types of wetlands have been studied with satellite remote sensing. Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have been used to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radar systems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imagery used visual interpretation for classification. The most commonly used computer classification method to map wetlands is unsupervised classification or clustering. Maximum likelihood is the most common supervised classification method. Wetland classification is difficult because of spectral confusion with other landcover classes and among different types of wetlands. However, multi-temporal data usually improves the classification of wetlands, as does ancillary data such as soil data, elevation or topography data. Classified satellite imagery and maps derived from aerial photography have been compared with the conclusion that they offer different bur complimentary information. Change detection studies have taken advantage of the repeat coverage and archival data available with satellite remote sensing. Detailed wetland maps can be updated using satellite imagery. Given the spatial resolution of satellite remote sensing systems, fuzzy classification, subpixel classification, spectral mixture analysis, and mixtures estimation may provide more detailed information on wetlands. A layered, hybrid or rule-based approach may give better results than more traditional methods. The combination of radar and optical data provide the most promise for improving wetland classification.

引用

页码：381 / 402

页数：21

共 106 条

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