ARTIFICIAL NEURAL NETWORKS FOR LAND-COVER CLASSIFICATION AND MAPPING

被引：259

作者：

CIVCO, DL

机构：

[1] Laboratory for Earth Resources Information Systems, U-87, Natural Resource Management and Engineering, The University of Connecticut, Storrs, CT

来源：

INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SYSTEMS | 1993年 / 7卷 / 02期

关键词：

D O I：

10.1080/02693799308901949

中图分类号：

P9 [自然地理学]; K9 [地理];

学科分类号：

0705 ; 070501 ;

摘要：

Artificial intelligence approaches toward image processing and pattern recognition are perceived as an alternative to, and an improvement over, traditional statistically-based procedures. Of particular interest to the satellite remote sensing community are artificial neural networks. This article describes the application of such an approach to the problem of deriving land-cover information from Landsat satellite Thematic Mapper (TM) digital imagery. The techniques being developed are ones that will provide more accurate and useful data for use with geographical information systems.

引用

页码：173 / 186

页数：14

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