Construction of Spectral Prediction Model of Karst Rocky Desertification Under Different Conditions and Analysis of Its Spatial Distribution

ZHOU Zhong-fa; YAN Li-hui; YU Qin

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Construction of Spectral Prediction Model of Karst Rocky Desertification Under Different Conditions and Analysis of Its Spatial Distribution

- Construction of Spectral Prediction Model of Karst Rocky Desertification Under Different Conditions and Analysis of Its Spatial Distribution
- Bulletin of Soiland Water Conservation Vol. 27, Issue 6, Pages: 95-97(2008)
- 作者机构：
  
  1. 武汉理工大学资源与环境工程学院,湖北,武汉,430070
  2. 贵州师范大学中国南方喀斯特研究院,贵州,贵阳,550001
- 作者简介：
- 基金信息：
- DOI：
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- Published：2008
- 稿件说明：
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ZHOU Zhong-fa, YAN Li-hui, YU Qin. Construction of Spectral Prediction Model of Karst Rocky Desertification Under Different Conditions and Analysis of Its Spatial Distribution[J]. Bulletin of Soiland Water Conservation, 2008, 27(6): 95-97.
DOI：

ZHOU Zhong-fa, YAN Li-hui, YU Qin. Construction of Spectral Prediction Model of Karst Rocky Desertification Under Different Conditions and Analysis of Its Spatial Distribution[J]. Bulletin of Soiland Water Conservation, 2008, 27(6): 95-97. DOI：

摘要

在喀斯特地区不同背景条件下

采用光谱特征与数学分解模型相结合的方法对石漠化信息进行分类

可提高对石漠化智能分类的准确性和时效性。以贵州省毕节市鸭池示范区为例

利用不同平台和波段遥感数据

在3S技术支持下进行处理、分类、解译和分析喀斯特石漠化的空间分布状况与特征

对石漠化光谱特征进行定量研究

掌握不同条件和不同影响因子下石漠化光谱特征的变化规律

得出了该区石漠化的空间分布与状况特征

可为其它地区石漠化遥感智能解译提供参考。

Abstract

This article attempts to get the information on rocky desertification under different background conditions in the karst area using spectral features and mathematical method

so as to improve the accuracy and timeliness of desertification intelligent classification.The Yachi demonstration area is taken as a study area and different platforms and different bands of remote sensing data are used.Based on the 3S technologies

the spatial distribution and characteristics of the karst area are summarized through processing

analysis

and classification.A quantitative research is carried out to understand the spectral characteristics in different conditions and diversities.Results from the study provide some references for other areas to develop the interpretation of remote sensing intelligent desertification.

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Soil Organic Carbon and Total Nitrogen of Soil Physical Fraction in the Process of Karst Rocky Desertification

Impact of Precipitation Factor on Rocky Desertification in Karst Areas

Correlation of Karst Rock Desertification and Land Use Patterns in Different Geomorphologic Environment

Design of Monitoring and Pre-warning System of Karst Rocky Desertification in Guizhou Plateau

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