基于CLUE-S模型和GIS的微山县土地利用变化动态模拟与情景分析
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摘要
土地利用反映了人类与自然界相互影响与交互作用最直接和最密切的关系,人类在利用土地促进社会经济发展的同时,也引起了土地覆被的变化,并对生态环境产生了巨大的影响。LUCC是国际地圈-生物圈计划(IGBP)和全球环境变化的人文因素计划(IHDP)的核心计划,LUCC计划的根本目标是促进土地利用/覆盖变化的区域理解,尤其是用模型清楚地表达出来。
这一领域目前主要关注的问题是:①土地利用/覆盖变化模拟的驱动力;②土地利用/覆盖变化驱动力模拟的尺度依赖性;③预测土地利用/覆盖的位置变化和数量变化;④土地利用/覆盖变化生物物理反馈的结合。
对一些局部和区域的实例研究,可提供确定和说明原因与覆被相互关系的主要变异所需的空间和时间分辨率。当把重点集中到单个区域和地区,或者缩小时间范围时,就会大大增进我们对原因与覆被关系的详细了解。为解释土地利用/土地覆被的全球变化,必须进行广泛的区域个性个例研究。
本文以微山县土地利用格局为研究对象,利用遥感图像提取了土地利用现状图,并结合易于栅格化并对土地利用变化有主要影响的驱动因子的分析,采用逻辑斯蒂回归得出的相关系数,目标年土地利用需求数据一起导入CLUE-S模型分别预测了2004年和2014年的土地利用格局,并对模拟结果进行多重验证和评价。本论文开展的研究工作和得出的结论如下:
1、对研究区的生态承载力评价表明,微山县2005年人均生态足迹为3.2341hm~2/人,而实际可利用人均生态承载力仅为0.2978hm~2/人,生态赤字高达2.9363hm~2/人。由于缺乏2003,2004年的能源消费状况,所以建筑用地和化石燃料用地生态足迹难以计算,2003、2004年总的生态足迹无法得出。但是从其余四种土地类型的生态足迹来看,其生态足迹之和已经远远超过土地的生态承载力。
由此可见,区域的承载能力已经难以满足生物生产性土地面积的需求,区域生态系统十分脆弱,人地矛盾非常突出,其生态环境已经承受越来越大的压力,生态环境的自我调节能力越来越差。因此,在运用模型模拟未来土地利用变化时,需要设定生态保护情景,依据合理的土地需求进行模拟,才能有效缓解区域发展的矛盾,实现可持续发展。
2、分别以1995年300m、500m栅格模拟2004年土地利用格局,与2004年实际土地利用现状作比较。在300×300m栅格情况下,得到的模拟正确栅格数是16257个,占总栅格数18000的90.32%,所以Po=0.9032。由此计算出Kappa指数为0.8838。在500×500m栅格情况下,得到的模拟正确栅格数是5676个,占总栅格数6475的87.66%,所以Po=0.8766。由此计算出Kappa指数为0.8519。以上两种模拟结果均比较理想,说明CLUE-S模型可以很好的模拟微山县的土地利用/土地覆被变化。同时,栅格尺度增大在一定程度上降低了模拟精度。
3、以2004年为初始数据模拟2014年四种需求情境下的土地利用格局,水域、耕地、建设用地、林地、园地、未利用地的ROC指数分别为0.966,0.891,0.985,0.866,0.922,0.989,其中由于未利用地变化较小,所以模拟精度最大。
结果表明,四种模拟情景下的土地格局在空间上存在较大差异,具体数量上的主要变化如下:前三种水域面积略有减少,自然增长情景和经济发展情景表现为耕地减少,建设用地增加,其中后者的建设用地得到集中建设。土地优化情景的建设用地通过集中建设面积减少,用以增加耕地面积,园地林地为实现结构优化也略有增加。生态保护情景:水域和林地面积明显增加,耕地和建设用地均减少,因此表现为耕地和建设用地转为水域和林地,未利用地和园地变化较小。
Land Use reflects the most direct and close relationship between human and nature in interaction, human boost social and economic development using land, simultaneously, also cause changes in land cover, which have produced a huge impact on the ecological environment. LUCC is the core programs of International Geosphere - Biosphere Programme ( IGBP ) and the Global Environmental Change Human Dimensions Programme (IHDP),The fundamental objective of LUCC project is to promote regional understanding in land use / cover change , particularly expressed by model clearly . At present, The main concern of this area are:①The driving forces of simulation in Land Use /
Cover Change;②The scale dependence of drive simulation in Land Use / Cover Change;③Forecasting the changes in the location and number for Land Use / Cover Change;④The combination of biophysical feedback in Land Use / Cover Change. The case studies of local and regional area can provide the spatial and temporal resolution required by the main variation which could explain the relationship between reason and cover . When focusing on the individual regions and districts, or narrowing the time frame, it will greatly improve our understanding of the relationship between cause and cover. Extensive case studies of regional character must be conducted to explain the land use / land cover changes in the world.
This article study the land use pattern of Weishan through getting land use maps which are extracted using remote sensing images, and analyzing driving factors rasterized which have major impact on land use change .The paper predict respectively the land use pattern in 2004 and 2014,and execute multiple verification and evaluation for the results of simulation through using the Correlation coefficient obtained by logistic regression analysis and importing the demand data for land use of the target year into CLUE-S model.
The main content and conclusion of this research are as follows:
1 The evaluation of ecological carrying capacity in Weishan shows that the ecological footprint is 3.2341hm~2/p in 2005, ecological carrying capacity is 0.2978hm~2/p, ecological deficit per capita is 2.9363hm~2/p. Due to lack of energy consumption data in 2003 and 2004, the ecological footprint of building site and fossil fuel land are difficult to calculate, so the total ecological footprint can not be obtained. But the ecological footprint of the rest four land types and has far exceeded the land's ecological capacity.
Thus, the region's carrying capacity has been difficult to meet the biological productive land area's requirements, the regional ecosystem is very fragile. Human-Land conflict keeps intensifying. Ecological environment has been under increasing pressure, the self-adjustment ability of ecological environment is getting worse. Therefore, before using model simulations of future land use change, the study must set up ecological protection scenarios, basis the reasonable land demand to simulation, then can effectively alleviate the contradiction in regional development and achieve sustainable development.
2 Adopting the 300m, 500m grid date in 1995 to simulation of land use pattern in 2004, and compared to the actual land use in 2004.In the case of 300×300m grid, get the correct simulation of the grid number is 15679, the total number is 18,000,the ratio is 80%, so Po = 0.8710. Kappa index was calculated to 0.8452. In the case of 500×500m grid, get the correct simulation of the grid number is 5438, the total number is 6475,the ratio is 83.98%, so Po = 0.8710. Kappa index was calculated to 0.8078. Above two results are both satisfactory, indicating that CLUE-S model can simulated Weishan land use / land cover change. Meanwhile, the grid size increases reduce the simulation accuracy in certain extent.
3 Take 2004 as the initial data to simulate the land use pattern under four demand scenarios in 2014, the ROC index of Water, land, construction land, forest land, garden plot and unused land are 0.966,0.891,0.985,0.866,0.922,0.989, among these, the unused land simulation accuracy largest because of it change least.
The results show that under the four scenarios of land patterns are quite different in space, the specific number of the major changes are as follows: The water area of the first three decreased slightly, The natural growth scenarios and the performance of economic development scenarios show the reduction of arable land, and the increase of construction land, the latter of which are focused on building construction sites. Optimization scenarios of land construction land area decreased by focusing on the construction to increase the cultivated area, of which forest land and garden land also have a slight increase to achieve structural optimization. Ecological protection scenario: significant increase in water and forest land, farmland and construction sites are both reduced, so the performance shows the arable land and construction land are converted into the water and forest land, of which unused land and the garden land changed have a small change.
这一领域目前主要关注的问题是:①土地利用/覆盖变化模拟的驱动力;②土地利用/覆盖变化驱动力模拟的尺度依赖性;③预测土地利用/覆盖的位置变化和数量变化;④土地利用/覆盖变化生物物理反馈的结合。
对一些局部和区域的实例研究,可提供确定和说明原因与覆被相互关系的主要变异所需的空间和时间分辨率。当把重点集中到单个区域和地区,或者缩小时间范围时,就会大大增进我们对原因与覆被关系的详细了解。为解释土地利用/土地覆被的全球变化,必须进行广泛的区域个性个例研究。
本文以微山县土地利用格局为研究对象,利用遥感图像提取了土地利用现状图,并结合易于栅格化并对土地利用变化有主要影响的驱动因子的分析,采用逻辑斯蒂回归得出的相关系数,目标年土地利用需求数据一起导入CLUE-S模型分别预测了2004年和2014年的土地利用格局,并对模拟结果进行多重验证和评价。本论文开展的研究工作和得出的结论如下:
1、对研究区的生态承载力评价表明,微山县2005年人均生态足迹为3.2341hm~2/人,而实际可利用人均生态承载力仅为0.2978hm~2/人,生态赤字高达2.9363hm~2/人。由于缺乏2003,2004年的能源消费状况,所以建筑用地和化石燃料用地生态足迹难以计算,2003、2004年总的生态足迹无法得出。但是从其余四种土地类型的生态足迹来看,其生态足迹之和已经远远超过土地的生态承载力。
由此可见,区域的承载能力已经难以满足生物生产性土地面积的需求,区域生态系统十分脆弱,人地矛盾非常突出,其生态环境已经承受越来越大的压力,生态环境的自我调节能力越来越差。因此,在运用模型模拟未来土地利用变化时,需要设定生态保护情景,依据合理的土地需求进行模拟,才能有效缓解区域发展的矛盾,实现可持续发展。
2、分别以1995年300m、500m栅格模拟2004年土地利用格局,与2004年实际土地利用现状作比较。在300×300m栅格情况下,得到的模拟正确栅格数是16257个,占总栅格数18000的90.32%,所以Po=0.9032。由此计算出Kappa指数为0.8838。在500×500m栅格情况下,得到的模拟正确栅格数是5676个,占总栅格数6475的87.66%,所以Po=0.8766。由此计算出Kappa指数为0.8519。以上两种模拟结果均比较理想,说明CLUE-S模型可以很好的模拟微山县的土地利用/土地覆被变化。同时,栅格尺度增大在一定程度上降低了模拟精度。
3、以2004年为初始数据模拟2014年四种需求情境下的土地利用格局,水域、耕地、建设用地、林地、园地、未利用地的ROC指数分别为0.966,0.891,0.985,0.866,0.922,0.989,其中由于未利用地变化较小,所以模拟精度最大。
结果表明,四种模拟情景下的土地格局在空间上存在较大差异,具体数量上的主要变化如下:前三种水域面积略有减少,自然增长情景和经济发展情景表现为耕地减少,建设用地增加,其中后者的建设用地得到集中建设。土地优化情景的建设用地通过集中建设面积减少,用以增加耕地面积,园地林地为实现结构优化也略有增加。生态保护情景:水域和林地面积明显增加,耕地和建设用地均减少,因此表现为耕地和建设用地转为水域和林地,未利用地和园地变化较小。
Land Use reflects the most direct and close relationship between human and nature in interaction, human boost social and economic development using land, simultaneously, also cause changes in land cover, which have produced a huge impact on the ecological environment. LUCC is the core programs of International Geosphere - Biosphere Programme ( IGBP ) and the Global Environmental Change Human Dimensions Programme (IHDP),The fundamental objective of LUCC project is to promote regional understanding in land use / cover change , particularly expressed by model clearly . At present, The main concern of this area are:①The driving forces of simulation in Land Use /
Cover Change;②The scale dependence of drive simulation in Land Use / Cover Change;③Forecasting the changes in the location and number for Land Use / Cover Change;④The combination of biophysical feedback in Land Use / Cover Change. The case studies of local and regional area can provide the spatial and temporal resolution required by the main variation which could explain the relationship between reason and cover . When focusing on the individual regions and districts, or narrowing the time frame, it will greatly improve our understanding of the relationship between cause and cover. Extensive case studies of regional character must be conducted to explain the land use / land cover changes in the world.
This article study the land use pattern of Weishan through getting land use maps which are extracted using remote sensing images, and analyzing driving factors rasterized which have major impact on land use change .The paper predict respectively the land use pattern in 2004 and 2014,and execute multiple verification and evaluation for the results of simulation through using the Correlation coefficient obtained by logistic regression analysis and importing the demand data for land use of the target year into CLUE-S model.
The main content and conclusion of this research are as follows:
1 The evaluation of ecological carrying capacity in Weishan shows that the ecological footprint is 3.2341hm~2/p in 2005, ecological carrying capacity is 0.2978hm~2/p, ecological deficit per capita is 2.9363hm~2/p. Due to lack of energy consumption data in 2003 and 2004, the ecological footprint of building site and fossil fuel land are difficult to calculate, so the total ecological footprint can not be obtained. But the ecological footprint of the rest four land types and has far exceeded the land's ecological capacity.
Thus, the region's carrying capacity has been difficult to meet the biological productive land area's requirements, the regional ecosystem is very fragile. Human-Land conflict keeps intensifying. Ecological environment has been under increasing pressure, the self-adjustment ability of ecological environment is getting worse. Therefore, before using model simulations of future land use change, the study must set up ecological protection scenarios, basis the reasonable land demand to simulation, then can effectively alleviate the contradiction in regional development and achieve sustainable development.
2 Adopting the 300m, 500m grid date in 1995 to simulation of land use pattern in 2004, and compared to the actual land use in 2004.In the case of 300×300m grid, get the correct simulation of the grid number is 15679, the total number is 18,000,the ratio is 80%, so Po = 0.8710. Kappa index was calculated to 0.8452. In the case of 500×500m grid, get the correct simulation of the grid number is 5438, the total number is 6475,the ratio is 83.98%, so Po = 0.8710. Kappa index was calculated to 0.8078. Above two results are both satisfactory, indicating that CLUE-S model can simulated Weishan land use / land cover change. Meanwhile, the grid size increases reduce the simulation accuracy in certain extent.
3 Take 2004 as the initial data to simulate the land use pattern under four demand scenarios in 2014, the ROC index of Water, land, construction land, forest land, garden plot and unused land are 0.966,0.891,0.985,0.866,0.922,0.989, among these, the unused land simulation accuracy largest because of it change least.
The results show that under the four scenarios of land patterns are quite different in space, the specific number of the major changes are as follows: The water area of the first three decreased slightly, The natural growth scenarios and the performance of economic development scenarios show the reduction of arable land, and the increase of construction land, the latter of which are focused on building construction sites. Optimization scenarios of land construction land area decreased by focusing on the construction to increase the cultivated area, of which forest land and garden land also have a slight increase to achieve structural optimization. Ecological protection scenario: significant increase in water and forest land, farmland and construction sites are both reduced, so the performance shows the arable land and construction land are converted into the water and forest land, of which unused land and the garden land changed have a small change.
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