Dynamic and Cumulative Analyses of Desertification in the Sandy Area of Dalate County

Chen Yalin; Chang Xueli; Cui Buli

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Dynamic and Cumulative Analyses of Desertification in the Sandy Area of Dalate County

- Dynamic and Cumulative Analyses of Desertification in the Sandy Area of Dalate County
- Bulletin of Soiland Water Conservation Vol. 26, Issue 2, Pages: 112-118(2007)
- 作者机构：
  
  鲁东大学地理与资源管理学院,山东,烟台,264025
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2007
- 稿件说明：
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Chen Yalin, Chang Xueli, Cui Buli. Dynamic and Cumulative Analyses of Desertification in the Sandy Area of Dalate County[J]. Bulletin of Soiland Water Conservation, 2007, 26(2): 112-118.
DOI：

Chen Yalin, Chang Xueli, Cui Buli. Dynamic and Cumulative Analyses of Desertification in the Sandy Area of Dalate County[J]. Bulletin of Soiland Water Conservation, 2007, 26(2): 112-118. DOI：

摘要

以达拉特旗中部沙丘为研究区域

在3S技术支持下解译达拉特旗1987

1995

2000和2003年4期遥感影像

获得4个年份的沙漠化动态数据

运用滑动平均法探讨了沙漠化发展演变的动力机制。结果表明

该地区近20a来

沙漠化土地处于逆转-发展-逆转的过程中。1995-2000年间

是该地区沙漠化动态变化最大的时期

沙漠化驱动力的累加效应表明

人口数量与牲畜量对沙漠化的累加效应均很明显

且人口数量对沙漠化的累加效应要高于牲畜量;年均风速对沙漠化的累加效应在各个时间尺度均很显著

年均温在大于2a的时间尺度上对沙漠化的累加效应最明显。

Abstract

The study area is located in the center of Dalate County. Based on 3S techniques and combined with ground investigation

the Land-sat TM images of 1987

1995

2000 and 2003 were interpreted. The changes of sandy land were analy zed by using the database of desertification dynamics from 1987 to 2003. RS and GIS softwares

such as Erdas 8.6

ArcView 3.3 and ArcInfo 7.1 were used as an interpretation tool. The cumulative impact analysis was used to find the reasons of desertification. Results showed that in the past 20 years

the desert-if ied lands were in the status of the reverse-development-reverse. The degree of dynamic desertification was the highest from 1995 to 2000. The analyses of natural elements and human activities with sliding average indicated that the cumulat impacts of population and livestock on desertification were signif icant

and the effect of population was strong er than livestock. the cumulative impacts of annual mean wind were always significant in all temporal scales. The effect of annual mean temperature was significant (at 0.01 scale) over two years.

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