Characterization of Coastal Wetland Systems using Multiple Remote Sensing Data Types and Analytical Techniques

被引：6

作者：

Civco, Daniel ^{[1
]}

Hurd, James ^{[1
]}

Prisloe, Sandy ^{[1
]}

Gilmore, Matha ^{[2
]}

机构：

[1] Univ Connecticut, Ctr Land Use Educ & Res, Storrs, CT 06269 USA

[2] Wesleyan Univ, Earth & Environm Sci, Middletown, CT 06459 USA

来源：

2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年

基金：

美国国家航空航天局;

关键词：

Connecticut; Long Island Sound; salt marsh; vegetation; classification; Landsat; LIDAR; ADS-40;

D O I：

10.1109/IGARSS.2006.883

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

A multistage process for classifying coastal marshes using a rule-based object-oriented procedure applied to Landsat ETM data is discussed. The method, which uses both spectral and spatial criteria, produces classifications more useful than those based on per-pixel, spectral data-alone techniques. Analysis of co-registered high resolution LIDAR-derived elevation and ADS40 CIR imagery has demonstrated it is possible to discriminate among areas dominated by Phragmites australis, Typha spp. and Spartina patens.

引用

页码：3442 / +

页数：2

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