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中国沙漠 ›› 2003, Vol. 23 ›› Issue (2): 132-135.

• 研究论文 • 上一篇    下一篇

宁夏沙地遥感宏观动态研究

颜长珍, 王一谋, 冯毓荪, 王建华   

  1. 中国科学院 寒区旱区环境与工程研究所, 甘肃 兰州 730000
  • 收稿日期:2001-04-17 修回日期:2001-06-29 出版日期:2003-04-20 发布日期:2003-04-20
  • 作者简介:颜长珍(1967-),男(汉族),甘肃岷县人,助研,博士。主要从事遥感应用与地理信息系统研究工作。
  • 基金资助:
    中国科学院"九五"特别支持项目"中国资源环境遥感信息系统与农情速报"(KZ95T)成果

Macro-scale Survey and Dynamic Studies of Sandy Land in Ningxia by Remote Sensing

YAN Chang-zhen, WANG Yi-mou, FENG Yu-sun, WANG Jian-hua   

  1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
  • Received:2001-04-17 Revised:2001-06-29 Online:2003-04-20 Published:2003-04-20

摘要: 以宁夏1996年和2000年的TM影像为信息源,在全数字方式下运用遥感技术与地理信息系统技术结合建立了两期宁夏沙地数据库。通过分析得出:2000年宁夏有沙地面积313 498 hm2,与1996年相比新增加4 894 hm2、减少2 9705 hm2、净减少2 4811 hm2,净减少了7.333%。沙地占全区总土地面积的比例由1996年的6.533%减少到2000年的6.054%,平均每年净减少0.120%。同时,分析了全区沙地变化的驱动因子。沙地增加的主要因素是草地沙漠化和耕地沙化,两者分别占沙地总增加量的78.463%和13.302%;沙地减少的相互主要因素是沙地开垦为耕地和沙地恢复草被变为草地,两者分别占沙地总减少量的50.025%和46.666%。

关键词: 遥感, 地理信息系统, 陕甘宁青沙地, 宏观研究

Abstract: By using digital method of remote sensing and geographical information system techniques,TM images of 1996 and 2000 have been interpreted to establish the database of sandy land of the two periods in Ningxia Region.In the study,the definition of the sandy land is the land that is covered by sand and the vegetation coverage is lower than 5%,and it includes sand desert.There are as much as 313 498 km2 sandy lands in Ningxia Region in 2000 and 24 811 km2 less than that in 1996,the sandy land deceased by 7.334%.The percentage of sandy land area to the whole area decreased from 6.533% in 1996 to 6.054% in 2000,and decreased 0.120% each year.Further,the factors causing sandy land change were analyzed.The factors causing sandy land increasing are grassland desertification and cultivated land desertification,and they occupied 78.463% and 13.302%,respectively.The factors causing sandy land decreasing are that sandy lands were cultivated and planted grass,and they occupied 50.025% and 46.666% in order.

Key words: remote sensing technique, GIS, sandy land in Ningxia region, macro-scale study

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