Study on Remote Sensing Classification Method of Classifing High, Medium and Low Yield Croplands and Their Forming Factors in the Loess Plateau  --Taking Dingxiang County of Shanxi Province as an Example

QIAO Yu  liang

doi:10.11834/jrs.20020113

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Study on Remote Sensing Classification Method of Classifing High, Medium and Low Yield Croplands and Their Forming Factors in the Loess Plateau --Taking Dingxiang County of Shanxi Province as an Example
Issue 1, Pages: 70-74(2002)
Published：2002
DOI： 10.11834/jrs.20020113
稿件说明：

移动端阅览

[1]乔玉良.黄土地区高中低产农田成因及遥感分类方法研究——以山西省定襄县为例[J].遥感学报,2002(01):70-74. DOI： 10.11834/jrs.20020113.

QIAO Yu liang. Study on Remote Sensing Classification Method of Classifing High, Medium and Low Yield Croplands and Their Forming Factors in the Loess Plateau --Taking Dingxiang County of Shanxi Province as an Example[J]. Journal of Remote Sensing, 2002, (1): 70-74. DOI： 10.11834/jrs.20020113.

摘要

利用空间遥感信息在地理信息系统支持下

以山西省定襄县为试验区

进行黄土地区高中低产农田监测时

选用与高中低产农田成因有直接关系的盐碱程度、灌溉等级和地形坡度等专题信息与TM数据进行信息复合

采用先分区后分类最后合并的复合分层分类方法

改进了常规的遥感分类方法

大大提高了分类精度。

Abstract

In loess plateau of China

the yield varies from cropland to cropland. It is very important for the agriculture of China that monitoring the changes of cropland in different years with RS information. The paper selects some themes that directly affect the yeild of cropland. Based on the comprehensive thematic information

a large region is divided into several small regions and the cropland from some different region in the remote sensing TM image are classified. The development of the method of divisional compound hierarchical classification has improved the accuracy of remote sensing classification greatly.