Position: Home > Articles > On Saline Soil's Brightness Changes of TM Images in Northern Part of Tarim Basin——A Case Study of Ugan and Kucha Rivers Delta
Soils
2008,40
(4)
667-671
基于TM图像的塔里木盆地北缘盐渍地亮度值分析——以渭干河-库车河三角洲绿洲为例
作 者:
吐尔逊·艾山;塔西甫拉提·特依拜;丁建丽
单 位:
新疆大学资源与环境科学学院
关键词:
渭干河-库车河三角洲;盐渍地;TM图像;亮度值
摘 要:
渭干河-库车河三角洲绿洲地处世界第二大沙漠塔克拉玛干沙漠的北缘。随着经济的快速发展,土地资源开发强度开始加大,土壤盐渍化成为渭干河-库车河三角洲可持续发展面临的主要环境问题之一。因此,准确提取土壤盐渍化信息对研究区土壤盐渍化监测和研究盐渍化动态变化具有重要意义。本文以TM卫星图像数据及野外实测的数据为数据源,选择研究区具有代表性的植被、水体、重度盐渍地、中轻度盐渍地、岩石和旱地等主要地物,利用PCI软件分析了这些主要地物在TM影像不同波段上的亮度值变化规律。其中,研究区内不同程度盐渍地的信息提取是本研究的重点。本文结合研究区本底资料,在对遥感数据光谱知识充分分析,挖掘谱间结构的基础上,揭示了研究区内不同程度盐渍地在TM影像中的亮度值变化特征及分离规则。实验表明,盐渍地总提取精度达到88.6%。其中,重度及中轻度盐渍地面积的提取精度分别达到90.8%和86.7%。本研究表明,通过利用此方法,可将盐渍地信息较为精确地提取出来。
译 名:
On Saline Soil's Brightness Changes of TM Images in Northern Part of Tarim Basin——A Case Study of Ugan and Kucha Rivers Delta
作 者:
TRUSUN.Hasan1,2, TASHPOLAT.Tiyip1,2, DING Jian-li1,2,3 (1 College of Resource and Environment Sciences, Xinjiang University, Urumqi 830046, China; 2 Key Laboratory of Oasis Ecology, Ministry of Education, Urumqi 830046, China; 3 Post Doctoral Laboratory of Theoretical Economics, Xinjiang University, Urumqi 830046, China )
关键词:
Ugan and Kucha River Delta, Saline soil, TM image, Brightness value
摘 要:
Soil salinization in Ugan and Kuch river delta, located in the north part of the world's second largest desert of Taklimakan, has become one of the main environmental problems for regional sustainable development with the rapid development of the economy and the continual utilization of soil resources. How to get the precise information on soil salinization is very important and useful to monitor soil salinization and its dynamic changes. This paper, by combining the regional background-information and based on the full analyses of spectral features of RS data, revealed the brightness changes of TM images and its separation regulation with PCI software for soils under different salinizated-extents in Ugan and Kucha river delta. The results showed that the total extracting accuracy of salinizated soil was 88.6%, and those of severe-and middle-light salinizated soils were 90.8% and 86.7%, respectively. In conclusion, the method used in this paper could extract accurately the information on salinizated soil.
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