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约束性条件下的喀什市土地利用空间格局分析
引用本文:吕金霄,张永福. 约束性条件下的喀什市土地利用空间格局分析[J]. 水土保持研究, 2017, 0(3): 325-330
作者姓名:吕金霄  张永福
作者单位:新疆大学资源与环境科学学院,乌鲁木齐830046;新疆大学绿洲生态重点实验室,乌鲁木齐830046
基金项目:阿克苏市基本农田划定项目(211-62180)
摘    要:基于高分辨率遥感影像解译得到新疆喀什市2002年与2013年两期土地利用历史数据,通过对两期影像进行处理、分类、精度验证以及对CLUE-S模型和Markov模型进行精度验证,利用CLUE-S模型和Markov模型相结合的方法对研究区喀什市未来土地利用变化进行两种不同情景的模拟预测,系统分析了两种不同情景下土地利用变化的时空特征。结果表明:CLUE-S模型和Markov模型的相互结合使用成功克服了单一模型的不足,能够对喀什市未来土地利用情况进行良好的模拟。因此,在设计的两种情景模拟预案下,喀什市未来的建设用地均将持续增加,并以消耗大量的耕地资源为代价,并且约束情景模型Ⅱ城镇规划节约集约用地和基本农田保护预案是喀什市未来土地利用变化的推荐预案。

关 键 词:土地利用  约束性条件  情景模拟  喀什市

Analysis on Land Use Spatial Pattern of Kashi City Under the Constraint Condition
LYU Jinxiao,ZHANG Yongfu. Analysis on Land Use Spatial Pattern of Kashi City Under the Constraint Condition[J]. Research of Soil and Water Conservation, 2017, 0(3): 325-330
Authors:LYU Jinxiao  ZHANG Yongfu
Abstract:Based on high-resolution satellite image interpretation obtained in Kashi Prefecture of Xinjiang Uygur Autonomous Region,Kashi City,in 2002 and 2013.The CLUE-S model and Markov model were used to predict city under the condition of the binding decades of land use change in the future.Two phases of images were processed and classified,accuracy was verified.The accuracy of CLUE-S model and Markov model was verified.Two different scenarios were predicted,and two different system changes in spatial characteristics in land use scenarios were analyzed.The results showed that combinin CLUE-S model and the Markov model could successfully overcome the lack of mutual use of a single model,it is possible for the future land use of the city of Kashi to be well simulated in two design plans,Kashi City,the future of construction land will continue to increase,and to consume a lot of resources at the expense of arable land,comprehensive comparison of results show that the constraint scenario model Ⅲ town planning conservation and intensive land and basic farmland protection plan is the future land use change in Kashi City recommended plan.
Keywords:land use  binding conditions  scenarios simulation  Kashi City
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