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金衢盆地土地退化遥感研究──以兰溪市上华试验区为例
引用本文:卢金发,崔书红,林利,黄秀华.金衢盆地土地退化遥感研究──以兰溪市上华试验区为例[J].遥感学报,1996(3).
作者姓名:卢金发  崔书红  林利  黄秀华
作者单位:中国科学院地理研究所,中国科学院遥感应用研究所
摘    要:在土地退化评价指标建立的基础上,利用两期航空象片和GIS,编制完成了浙江省兰溪市上华试验区50年代和80年代土地退化图。分析表明,全区64%以上土地已开垦利用,流水侵蚀引起的各级退化土地面积约占全区土地总面积的36%。其中,剧烈和严重退化土地约占5.11%,较严重和中度退化土地约占7.38%,轻度和微度退化土地约占23.43%。退化土地的空间分布具有明显的坡位分异性。目前本区以裸露的侵蚀劣地为主要特征的严重和剧烈退化土地,并非人们以往所认为的是近几十年间形成的。近几十年来,土地退化的发展主要表现为微度退化土地的急剧减少及轻度和中度退化土地的明显增加。

关 键 词:金衢盆地,土地退化,遥感和地理信息系统

Research on Land Degradation in Jinhua-Quzhou Basin by Remote Sensing: A Case Study
Lu Jinf,Cui Shuhong,Lin Li.Research on Land Degradation in Jinhua-Quzhou Basin by Remote Sensing: A Case Study[J].Journal of Remote Sensing,1996(3).
Authors:Lu Jinf  Cui Shuhong  Lin Li
Abstract:Based on the criteria for assessment of land degradation two synthetic maps of land degradation in different periods (1950's and 1980's) are prepared by using aerial photos and with the help of GIS. It has been shown that due to the long history of economic development more than 64% of land were cultivated or used in the studied area. Various grades of degraded land caused by water erosion occupied only 36% of the total land: some 5. 11% of this are severely and very severely degraded, 7. 38% moderately and more severely degraded and the other 23. 43% slightly degraded and non-degraded. Since downslope zonation of soil, vegetation and erosional features is obvious from top to foot of hill, same situation happens to spatial variation of degraded land. It has been proved that severely and very severely degraded land characteristic of bared badlands were not formed in recent decades due to deforestation as it was commonly thought, but its history could been traced back to at least Ming and Qing Dynasties (350-650 years B. P.), even Tang, Song, Yuan and Jin Dynasties (650-1300 years B. P). During the last few decades the development of land degradation manifests itself as drastic reduction. of non-degraded land and parallel increase of slightly and moderately degraded land.
Keywords:Land degradation  Jinhua-Quzhou basin  Remote sensing and GIS
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