首页> 外文会议>Proceedings of the 22nd Asian Conference on Remote Sensing >THE USE OF A KNOWLEDGE-BASED DECISION RULE COMPUTER PROGRAM IN THE INTER-ANNUAL LAND COVER AND LAND USE CHANGE ANALYSIS OF THE UPPER MAGAT WATERSHED
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THE USE OF A KNOWLEDGE-BASED DECISION RULE COMPUTER PROGRAM IN THE INTER-ANNUAL LAND COVER AND LAND USE CHANGE ANALYSIS OF THE UPPER MAGAT WATERSHED

机译:基于知识的决策规则计算机程序在年际土地覆被中的应用以及上马加特流域的土地利用变化分析

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Radiometric correction was difficult to perform on imageries of mountainous areas where atmospheric and climatic data were difficult to obtain, because of the absence of weather stations. It was a general knowledge that the classification of the non-radiometrically corrected imagery resulted to misclassifications, low accuracy and inconsistencies. From these problems, the objectives of this study were drawn, namely: to utilize a knowledge-based decision rule program to improve the accuracy and assist in the pre-analysis of non-radiometrically corrected land cover and land use data. The study site was the Upper Magat Watershed, Province of Nueva Vizcaya, Philippines. Eight sets of Landsat TM data taken from 1988 to 1998 were used as inputs to the project. The raw imageries were geometrically rectified, and classified image mosaics were produced. A Turbo Pascal Program was created with a set of knowledge-based decision rule criteria. The classified imageries were used as input to the program and the result was a new set of classified imageries. Cross-tabulation of the classified imageries and those refined by the computer assisted program was performed. Confusion matrices of the 1998 classified imageries were generated. Results of the cross-tabulation showed that the classified imageries refined by the computer program had no incidence of invalid change results unlike the classified imageries produced without the assistance of the knowledge-based computer program. Also, its classification accuracy was higher than that of the imageries produced without the assistance of the computer program. We therefore conclude that the use of knowledge-based decision rule computer programs to assist the standard classification procedures improved the accuracy of the land cover and land use data and the consistency of the land cover and land use change results.
机译:由于缺乏气象站,很难在难以获得大气和气候数据的山区图像上进行辐射校正。众所周知,未经放射线校正的图像的分类会导致分类错误,准确性低和不一致。从这些问题出发,得出了本研究的目标,即:利用基于知识的决策规则程序来提高准确性,并协助对非辐射校正的土地覆盖和土地利用数据进行预分析。研究地点是菲律宾新埃斯比亚省的上马加特流域。从1988年至1998年获取的八套Landsat TM数据被用作该项目的输入。对原始图像进行几何校正,并生成分类的图像镶嵌图。使用一组基于知识的决策规则标准创建了Turbo Pascal程序。分类的图像用作程序的输入,结果是一组新的分类图像。对分类图像和由计算机辅助程序提炼的图像进行交叉制表。生成了1998年分类图像的混淆矩阵。交叉列表的结果表明,与没有借助基于知识的计算机程序的帮助下生成的分类图像不同,由计算机程序提炼的分类图像不会出现无效更改结果。而且,其分类精度高于没有计算机程序协助的情况下产生的图像的分类精度。因此,我们得出结论,使用基于知识的决策规则计算机程序来辅助标准分类程序,可以提高土地覆盖率和土地利用数据的准确性以及土地覆盖率和土地利用变化结果的一致性。

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