Visual interpretation of FCC image for land use and land cover mapping: an expert system approach

Rajkishore Prasad, A. K. Sinha, K. R. Ranjan
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引用次数: 1

Abstract

Emphasizes importance of visual image interpretation of satellite based standard false color composite (FCC) images for small areas and describes development of a rule based expert system for application in visual image interpretation of IRS-1B based FCC images, for land use and land cover mapping. The main objective is to develop computer based support for a human photo-interpreter and beginners in the area of FCC photo interpretation. The proposed expert system has been developed using a logic programming approach in the Borland's Turbo-Prolog 2.0 environment. The knowledge base of the system is based on the multilevel classification scheme of United States Geological Surveys (USGS) for land use/cover with due variation for Indian context. This system can make classification at the first level of the above scheme, using the standard FCC (images with band combination 2:3:4:B:G:R) of IRS-1B. The knowledge base of the system has been developed in accordance with syntax of Turbo-Prolog. This system can be used to help photo interpreter and to learn the visual image interpretation skill of FCC. The system has been used to identify land cover on FCC images of an area of Vaishali district of Bihar, India. The result has been found to be satisfactory at the coarse level.
用于土地利用和土地覆盖制图的FCC图像的可视化解释:一个专家系统方法
强调了小区域基于卫星的标准假彩色合成(FCC)图像的视觉图像解译的重要性,并描述了一个基于规则的专家系统的开发,该系统用于IRS-1B基于FCC图像的视觉图像解译,用于土地利用和土地覆盖制图。主要目标是为人类照片口译员和FCC照片口译领域的初学者开发基于计算机的支持。所提出的专家系统是在Borland的Turbo-Prolog 2.0环境中使用逻辑编程方法开发的。该系统的知识库基于美国地质调查局(USGS)关于土地利用/覆盖的多级分类方案,并根据印度的情况进行适当的变化。本系统采用IRS-1B标准FCC(图像带组合2:3:4:B:G:R),可在上述方案的第一级进行分类。系统的知识库按照Turbo-Prolog的语法进行了开发。该系统可用于辅助图片解译,学习FCC的视觉图像解译技巧。该系统已被用于识别印度比哈尔邦Vaishali地区的FCC图像上的土地覆盖。结果在粗水平上是令人满意的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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