| 关中-天水经济区土地利用变化模拟预测及景观格局动态变化 |
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| 引用本文： | 解修平,周杰,张海龙,张秋义,刘小强.关中-天水经济区土地利用变化模拟预测及景观格局动态变化[J].干旱区地理,2013,36(3):482-490. |
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| 作者姓名： | 解修平 周杰 张海龙 张秋义 刘小强 |
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| 作者单位： | （1 国家测绘地理信息局测绘标准化研究所， 陕西 西安 710074； 2 中国科学院水利部水土保持研究所黄土高原土壤侵蚀与旱地农业国家重点实验室， 陕西 杨凌 712100； 3 中国科学院遥感应用研究所， 北京 100101） |
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| 基金项目： | 黄土高原土壤侵蚀与旱地农业国家重点实验室开放基金，中国科学院百人计划项目，国家自然科学基金 |
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| 摘 要： | 利用2000年和2010年两期TM影像，应用遥感和GIS技术获取关中-天水经济区2000-2010年土地利用变化数据，对研究区土地利用时空状态进行分析，并借助CA-Markov模型对该地区土地利用变化趋势进行情景模拟，深入分析了10 a来和2020年研究区土地利用变化的数量和空间特征以及由此所引起的一系列生态环境效应，主要表现在：过去10 a来城镇建设用地面积增加迅速，耕地和草地面积则减少，城镇建设用地的扩展是通过占用大量城郊的农田来实现的，通过这10 a间的快速城市化进程看出，研究区的城市扩张和基本农田保护之间已经开始产生矛盾；研究区土地利用实际变迁面积约占全区总面积的24.39%，也就是说全区约1/4的土地在这10 a间都发生了变化，从而反映出人类活动之强烈；未来10 a耕地和草地面积将持续下降，耕地面积的减少速度变快，城镇建设用地面积仍然迅速增加，且主要有耕地和草地转化而来，未来10 a研究区土地利用实际变迁面积约占全区总面积的11.43%。景观指数的分析结果表明了研究区内的景观趋向破碎化、复杂化和均匀化发展，景观的稳定性和抗干扰性减小。
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| 关 键 词： | 土地利用 转移矩阵 CA-Markov 景观生态 关中-天水 |
| 收稿时间： | 2012-08-10 |
Land use change simulation and landscape pattern change of the Guanzhong-Tianshui Region |
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| XIE Xiu-ping,ZHOU Jie,ZHANG Hai-long,ZHANG Qiu-yi,LIU Xiao-qiang.Land use change simulation and landscape pattern change of the Guanzhong-Tianshui Region[J].Arid Land Geography,2013,36(3):482-490. |
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| Authors: | XIE Xiu-ping ZHOU Jie ZHANG Hai-long ZHANG Qiu-yi LIU Xiao-qiang |
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| Abstract: | Since 1998 development of western China，the economic development of western China has been developing very rapidly，the western region land use taking place the tremendous and unprecedented changes，and profoundly changing the local ecosystem structure. Based on two phases TM images acquired in 2000 and 2010 respectively，making use of the technology of Remote Sensing and GIS，also integrating with CA-Markov model， a quantitative analysis was made of the quantity and spatial feature changes of land use in Guanzhong-Tianshui region during the past ten years and the future ten years，with a hope for providing the supports for the sustainable land use，land management decision-making，regional land and ecological environment construction，and a series of eco-environmental after-effects. In this study，the BP neural network classification algorithm was used to classify the two period’s remote sensing images and analyse the land use change transfer matrix. In the past ten years，LUCC was expressed as follows: the build-up land increased sharply and enlarged about 291 210 hm2，whereas the arable land and grassland decreased apparently，arable land decreased about 60 028 hm2 and grassland decreased about 374 770 hm2. The build-up land has been increased in the way of invading the massive arable land，and the arable land reduction actually resulted in the reduction in per capita holding the average arable area，the grain question began to occur prominently; since this decade，about a quarter of the land has been changed in the study region， so human activities have developed strongly. And then the CA-Markov model was applied to carry on the simulation and prediction of 2020 land use，with the overall accuracy of simulating spatial location of 75.05%. In the coming ten years，LUCC will be listed as follows: Arable land and grassland will continue to be decreased and the reduction rate of cultivated land become greater in amount，build-up land area will still be in increasing rapidly and enlarged about 273 902 hm2，and most of them will be transformed from farmland and grassland，in the next ten years the actual changes in land use area will account for 11.43% of the region's total area. CA-Markov model with simulation time and spatial pattern change can reflect the changes in land use landscape patterns and their complexity and randomness with high precision and accuracy. More profound，intuitive study reveals the extent of environmental degradation. Land use and land cover change are a complex system，which is affected by many comprehensive factors，including both socio-economic and natural and environment ones. Using the CA-Markov model as a basic tool to predicate land use/land cover may not well indicate the real facts，it still needs other methods to consummate the model in order to make it more approach to the real fact. Finally，the landscape changes of the study area were analysed by calculating landscape indices. Comprehensive analysis of the landscape index shows the trends in landscape fragmentation，complexity and uniform development and overall landscape pattern’s increasing heterogeneity; agricultural land is the most important type of land，because of its area reduction，the importance of the effects of agricultural land on overall landscape also decreases. The reduced agricultural land was changed into the other type’s lands，and some ratios among the land use types’ were reduced with increasing land use types’ diversity and uniformity. The reduction in landscape dominance index means decrease in landscape stability，thereby the withstand capabilities of landscape decrease. |
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| Keywords: | land use change matrix CA-Markov landscape ecology Guanzhong-Tianshui region |
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