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密云水库流域土地利用时空变化及景观恢复保护区划
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摘要
目前密云水库是北京惟一地表饮用水水源地,北京城镇地表水供水量50%以上来自密云水库。为了保护密云水库水质、水量及周边的生态环境,多年来国家和北京、河北两地政府在密云水库流域节水灌溉、治污、水源涵养、水土保持等方面做了大量工作,流域内的植被恢复和重建工作取得了很大的成绩,也导致了流域土地利用/覆被及景观格局发生了大幅度的变化。为此,在广泛收集密云水库流域现有资料的基础上,以TM和MSS遥感卫星影像为基础,采用遥感技术和地理信息系统技术建立了密云水库流域的1978、1988、1998年和2008年四期土地利用空间信息数据库,进行流域的土地利用/覆盖变化研究。建立基于CA、Markov的复合模型来模拟和预测流域土地利用的变化,进一步探索土地利用变化背后的驱动机制以及预测未来土地利用格局。将定性分析和定量计算相结合,采用模拟结果和现实状况相比较、DCCA模型等方法研究了政策因素对土地利用变化驱动作用,揭示人类社会影响下区域土地利用变化的过程、机理等,以期帮助土地管理者分析不同宏观政策驱动下的土地利用变化趋势,为合理利用土地规划和决策提供支持。同时,为了研究该区森林景观的结构与功能,诊断森林景观健康状况,平衡区域发展,保护脆弱生态环境,并使得生态补偿标准更加科学化和合理化,本文对密云水库流域土地利用现状进行了基于生计改善的森林景观恢复优先区以及基于生态效益的森林景观保护区进行了划分,以期为调整社会经济发展策略及该流域森林景观恢复和改善提供科学依据。
     本研究的主要成果如下:
     1、1978-2008年以来,耕地、草地、水域及未利用土地面积减少,而林地和城乡、工矿、居民用地面积增加。流域土地利用方式以耕地、林地和草地为主,但其所占比例有所变化。1978-2008年有林地面积共增加4 891.75km2,草地资源的大面积退化也是密云水库流域土地利用空间变化的显著特征之一,可能由于高覆盖度草地的大量退化,中、低覆盖草地在某些相应时段内呈增加趋势,总体看来,草地面积在大量缩减,同时草地质量在下降;耕地在1978-2008年间共减少1 350.04km2。
     2、从密云水库流域土地利用类型空间转移情况看,主要表现为旱地、有林地、灌木林地、疏林地以及高、中、低覆盖度草地的变化。1978-2008年间,旱地的减少面积为1 858.67km2,主要去向为有林地、灌木林地和高覆盖度草地;旱地的增加面积为521.04km2,主要来源是高覆盖度草地。有林地增加面积为4 893.55km2,主要来源于旱地、疏林地。灌木林地的减少面积为752.65km2,主要去向为有林地、高覆盖度草地、中覆盖度草地;灌木林地增加面积为1 689.21km2,主要来源于旱地、疏林地、高覆盖度草地。疏林地的减少面积为3 816.31km2,主要去向为有林地、灌木林地;疏林地增加的面积为383.81km2,主要来源于旱地、灌木林地、高覆盖度草地。高覆盖度草地的减少面积为1 394.31km2,主要去向为有林地、灌木林地;高覆盖度草地的增加面积为769.82km2,主要来源于旱地、低覆盖度草地。中覆盖度草地的减少面积为274.41km2,主要去向为旱地、有林地、高覆盖度草地;中覆盖度草地增加的面积为540.45km2,主要来源于旱地、高覆盖度草地。低覆盖度草地的减少面积为613.28km2,主要去向为有林地、高覆盖度草地。
     3、1978年到2008年间,水田、滩地、有林地的破碎化程度降低,疏林地、河渠的斑块边界总长度逐渐减少,表明其形状逐渐趋于规则、简单,受人类活动的干扰较强。从景观格局整体变化趋势看,斑块数、斑块密度和斑块平均面积的变化趋势说明密云水库流域北京部分的景观趋于完整化,而河北部分的景观趋于破碎化。也说明了1988年后由于河北部分景观破碎化程度的增加导致了整个密云水库流域的景观破碎化程度在增加。北京部分和河北部分的景观多样性指数和景观均匀度指数都呈逐渐降低的趋势,北京降低的速度快于河北部分。
     4、密云水库流域河北部分1988-1998年旱地、疏林地和高覆盖度草地减少的速度大于1978-1988年,而有林地、灌木林地和中覆盖度草地增加的速率大于1978-1988年;1998-2008年有林地、疏林地、中覆盖度草地增加的速度小于1988-1998年,而旱地、灌木林地、高覆盖度草地减少的速度小于1988-1998年。密云水库流域北京部分1988-1998年疏林地、高覆盖度草地减少的速度大于1978-1988年,而有林地、灌木林地增加的速度大于1978-1988年,2008年的模拟结果主要表现为疏林地的模拟结果比现实结果要大,而旱地、灌木林地的面积的模拟结果都比现实结果要小。这也说明政策的干扰加剧了1988-1998年间林地的增加以及耕地、草地的减少,而1998-2008年政策的干扰强度较前十年有所降低。DCCA排序结果显示国家生态建设政策引导和调控下的人类活动是导致密云水库流域土地利用变化的最主要原因,是林地面积大幅度增加的直接驱动力。
     5、2020年预测结果与2008年现状相比较显示,耕地、草地仍呈减少的趋势,林地、水域和建设用地较2008年有所增加,总体看来2020年土地利用的变化趋势和1978-2008这30年间每10年一个时间段的变化趋势大体相同,但变化幅度远远减小。
     6、基于生计改善的森林景观恢复优先区以及基于生态效益的森林景观保护区划分结果显示:密云水库社会经济发展潜力一级分区主要分布在赤城县、丰宁县和密云县,二级分区主要分布在密云县、延庆县、滦平县和丰宁县,三级分区主要分布在赤城县、丰宁县、怀柔县、延庆县、滦平县和兴隆县,四级分区主要分布在赤城县和丰宁县;属于森林景观恢复一级优先区的村数有7个,多分布在赤城县,属于二级优先区的有377个村,多分布在赤城、丰宁和沽源县,属于复三级优先区的有606个村,多分布在赤城、密云和丰宁县,属于四级优先区的有116个村,多分布在怀柔区、密云县和延庆县;密云水库流域森林碳汇功能第一和第二分区所占面积最大,分别为441 928.95 hm2和318 505.95hm2,占总面积的46.40%和33.44%,第五分区最小,仅占总面积的3.17%;森林生态系统水源涵养功能分区中第二分区和第三分区所占的比例较大,分别为55.45%和28.28%,第五分区所占的比例最小,仅2.34%;生态系统服务功能第二分区和第三分区的面积最大,分别为542 812.69hm2和256 413.25hm2,分别占总面积的56.99%和26.92%,第五分区面积最小,仅占0.30%。
Fresh water resource scarcity is a global problem, Beijing as one of the world's serious water shortage cities, the per capita water resource is less than 300m, which is 4% of the world average value, and this makes Beijing a serious wat er deficient area. Miyun Reservoir is currently the only surface water source in Beijing, supplying more than 50% of Beijing urban surface water resource. In order to protect the water quality, quantity, and surrounding environment of Miyun Reservoir, national and Beijing, Hebei governments did a lot of work about water saving irrigation, pollution control, water and soil conservation in Miyun Reservoir watershed during the last few years, which made great achievements in vegetation restoration and reconstruction, but also led to a significant change of land use / cover and landscape pattern. For this reason, on the basis of available information of Miyun Reservoir watershed, based on the TM and MSS remote sensing satellite images, using remote sensing and GIS technology, we established 4 spatial information database of land use in the Miyun Reservoir watershed in 1978, 1988, 1998 and 2008 to analysis land use/cover change. We established CA, Markov composite model to simulate and predict land use changes to further more explore the driving mechanism and to forecast future land use pattern. We combined the qualitative analysis and quantitative calculation: compare the simulation results and the actual situation, apply DCCA model to analysis the impact of policy factors to land use change, reveal the land use change process and mechanism under the human activities effect, which can help land managers analysis land use trend under different macro-policy, to support rational land use planning and decision-making support. At the same time, in order to study the forest landscape structure and function, diagnosis the health status of forest landscape, balance regional development, protect the fragile ecological environment, and make scientific and reasonable ecological compensation standards, in this paper we zoned different priority areas of forest landscape restoration based on the livelihood improvement and different priority areas of forest protection based on ecological benefits, in order to provide scientific basis for adjusting social and economic development strategies and forest landscape restoration and improvement.
     The main results of this study are as follows:
     1. The farmland, grassland, water area and unused land have decreased, while the forest land, urban and rural, mining, residential areas have increased during 1978-2008. The farmland, forest land, and grassland were the main land use types in this watershed, but their proportion changed from 1978 to 2008. The forest land increased 4 891.75km2 from 1978 to 2008, and grassland degradation is also one of remarkable characteristics of spatial change of land use in Miyun Reservoir watershed, may be due to the mass degenerative high coverage grassland, medium and low coverage grassland tended to increase in some time period, in general the area of grassland greatly reduced, while quality of the grassland declined too; there was 1 350.04km2 farmland reduced during 1978-2008.
     2. As to the transfer situation of land use types in Miyun reservoir watershed, it mainly shown as the change among nonirrigated farmland, forest land, shrub land, high coverage grassland, moderate coverage grassland and low coverage grassland. The nonirrigated farmland reduced 1 858.67km2 during 1978-2008, and mainly changed to forest land, shrub land and high coverage grassland, the increased area of nonirrigated farmland is 521.04km2, which mainly from high coverage grassland. The increased area of forest land is 4 893.55km2, which mainly from nonirrigated farmland and open forest land. The shrub land reduced 752.65km2 during 1978-2008, and mainly changed to forest land, high coverage grassland and moderate coverage grassland, the increased area of shrub land is 1 689.21km2, which mainly from nonirrigated farmland, open forest land and high coverage grassland. The open forest land reduced 3 816.31km2 during 1978-2008, and mainly changed to forest land and shrub land, the increased area of open forest land is 383.81km2, which mainly from nonirrigated farmland, shrub land and high coverage grassland. The high coverage grassland reduced 1 394.31km2 during 1978-2008, and mainly changed to forest land and shrub land, the increased area of high coverage grassland is 769.82km2, which mainly from nonirrigated farmland and low coverage grassland. The moderate coverage grassland reduced 274.41km2 during 1978-2008, and mainly changed to nonirrigated farmland, forest land and high coverage grassland, the increased area of moderate coverage grassland is 540.45km2, which mainly from nonirrigated farmland and high coverage grassland. The low coverage grassland reduced 613.28km2 during 1978-2008, and mainly changed to forest land and high coverage grassland.
     3. The fragmentation degree of irrigated farmland, beach land and forest land reduced from 1978 to 2008, the total edge of open forest land and river trench gradually decreased, which indicating that their shape becoming more and more regular and simple, strong disturbed by human activities. From the whole developing trend of landscape pattern we can see that the trend of patch number, patch density and mean patch area shows the landscape of Beijing part tend to be integrated, while the Hebei part tend to fragmentation, and the increase in the landscape fragmentation degree of Hebei part after 1988 has led to the increasing of landscape fragmentation of Miyun Reservoir watershed. Both the landscape diversity index and landscape evenness index of Beijing and Hebei part gradually decreased, and the decreasing speed in Beijing part was faster than Hebei.
     ?4. The decreasing speed of nonirrigated farmland, open forest land and high coverage grassland in Hebei part during 1988-1998 is higher than 1978-1988, while the increasing speed of forest land, shrub land and moderate coverage grassland is higher than 1978-1988. The increasing speed of forest land, open forest land and moderate coverage grassland in Hebei part during 1998-2008 is higher than 1988-1998, while the decreasing speed of nonirrigated farmland, shrub land and high coverage grassland is higher than 1988-1998. The decreasing speed of open forest land and high coverage grassland in Beijing part during 1988-1998 is higher than 1978-1988, while the increasing speed of forest land and shrub land is higher than 1978-1988. The simulation results of land use situation in 2008 in Beijing part mainly show that the simulation result of open forest land is larger than actual result, while the nonirrigated farmland and shrub land are smaller than actual result. This implied the policy disturbance exacerbated the increase of forest land and the decrease of farmland and grassland in 1988-1998, but the policy disturbance intensity decreased during 1998-2008. The results of DCCA analysis show that human activities guided and regulated by national ecological construction projects is the main driving force of land use change in Miyun Reservoir watershed, it is also the direct driving force of large increased area of forest.
     5. Compared the simulated result in 2020 to the actual situation in 2008 we can see that farmland and grassland continued to show a decreasing trend, forest land, water area and construction area has increased compared with 2008. Overall, the land use change trend during 2008-2020 is similar to the trend of the last 3 time period, but the change speed reduced significantly.
     6. The zoning of different priority areas of forest landscape restoration based on the livelihood improvement and different priority areas of forest protection based on ecological benefits showed that: the 1st area of socio-economic development potential areas is mainly distributed in Chicheng County, Fengning County and Miyun County, the 2nd area is mainly distributed in Miyun County, Yanqing County and Luanping County, the 3rd area is mainly distributed in Chicheng County, Fengning County, Huairou County, Yanqing County, Luanping County and Xinglong County, the 4th area is mainly distributed in Chicheng County and Fengning County; there are 7 villages belong to the 1st area of forest landscape restoration, and most of them located in Chicheng County, there are 377 villages belong to the 2nd area of forest landscape restoration, and most of them located in Chicheng, Fengning and Guyuan counties, there are 606 villages belong to the 3rd area of forest landscape restoration, and most of them located in Chicheng and Miyun counties, there are 116 villages belong to the 4th area of forest landscape restoration, and most of them located in Huairou, Miyun and Yanqing counties; there are large areas of the 1st and the 2nd areas of forest system carbon sequestration function area, which are 441 928.95 hm2 and 318 505.95hm2 respectively, about 46.40% and 33.44% of the total area, and the 5th area has the smallest area, which is about 3.17% of the total area; there are large areas of the 2nd and the 3rd areas of forest system water conservation function area, which are 55.45% and 28.28% of the total area respectively, and the 5th area has the smallest area, which is about 2.34% of the total area; also there are large areas of the 2nd and the 3rd areas of forest ecosystem function area, which are 542 812.69hm2 and 256 413.25hm2 respectively, about 55.45% and 28.28% of the total area, and the 5th area has the smallest area, which is about 0.30% of the total area.
引文
Alejandro F S, Miguel M R, Omar R M. Assessing implications of land-use and land-cover change dynamics for conservation of a highly diverse tropical rain forest. Biological Conservation, 2007, 138(1-2): 131-145.
    Arai T, Akiyama T. Empirical analysis for estimating land use transition potential functions case in the Tokyo metropolitan region. Computers, environment and urban systems, 2004, 28: 65-84.
    Aspinall R. Modelling land use change with generalized linear models-a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana. Journal of Environmental Management, 2004, 72, 91-103.
    Barredo J I, Kasanko M, McCormick N, et al. Modelling dynamic spatial processes: simulation of urban future scenarios through cellular automata. Landscape and Urban Planning, 2003, 64(3): 145-160.
    Barreteau O, Bousquet F. SHADOC: a multi-agent model to tackle viability of irrigated systems. Annals of Operations Research, 2000, 94: 139-162.
    Batty M, XieY. From cells to cities. Environment and Planning B, 1994, 21: 31-48.
    Batty M, Couclelis H, Eichen M. Urban systems as cellular automata. Environment and Planning B: Planning and Design, 1997, 24: 159-164.
    Batty M, Xie Y, Sun Z. Modeling urban dynamics through GIS-based cellular automata. Computers, Environment and Urban Systems, 1999, 23: 205-233.
    Berger T. Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, Resource use changes and policy analysis. Agricultural Economics, 2001, 25: 245-260.
    Bessusi E, Cecchini A, Rinaldi E. The diffused city of the Italian northeast: Identification of urban dynamics using cellular automata urban models. Computer, Environment and Urban Systems, 1998, 22(5): 497-523.
    Boerner R E J, DeMers M N, Simpson J W, et al. Markov models of inertia and dynamic on two contiguous Ohio landscapes. Geographical Analysis, 1996, 28: 56-66.
    Bousquet F, Bakam I, Proton H, et al. Cormas: common-pool resources and multi agent systems. Lecture Notes in Artificial Intelligence, 1998, 1416: 826-837.
    Brath A, Montanari A, Moretti G. Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). Journal of Hydrology, 2006, 324(1): 141-153.
    Bray D B, Ellis E A, Armijo-Canto N, et al. The institutional drivers of sustainable landscapes: a case study of the Mayan Zone in Quintana Roo, Mexico. Land Use Policy, 2004, 21: 333-346.
    Cecchini A. Approaching generalized automata with help on line (AUGH). In: Besussi E, Cecchini A (eds), 1996. Artificial worlds and urban studies, DAEST, 1996, 231-248.
    Chapin F S, Weiss S F. A probabilistic Model of Residential Growth. Transportation Research, 1968, 2: 375-390.
    Clarke K C, Gaydos L, Hoppen S. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B, 1997, 24: 247-261.
    Clarke K C, Gazulis N, Dietzel C K, et al. A decade of SLEUTHing: lessons learned from applications of a cellular automaton land use change model. In: Fisher P (ed), Classics from IJGIS. Twenty years of the International Journal of Geographical Information Systems and Science. Boca Raton, FL: CRC Press, 2007.
    Couclelis H. Cellular worlds: A framework for modeling micro macro dynamics. Environment and Planning A, 1985, 17: 585-596.
    Couclelis H. Macrostructure and micro behavior in a metropolitan area. Environment and Planning B, 1989, 16: 151-154.
    Couclelis H. From cellular automata to urban models: new principles for model development and implementation. Environment and Planning B, 1997, 24: 165-174.
    Deadman P J, Brown R D, Gimblett H R. Modeling rural residential settlement patterns with cellular automata. Journal of Environmental Management, 1993, 37: 147-160.
    Deal B M, Sun Z. A spatially explicit urban simulation model: the land-use evolution and impact assessment model (LEAM). in: Ruth M (eds). Regional development, infrastructure, and adaptation to climate variability and change. New York: Springer, 2005.
    Dietzel C, Clarke K C. Toward optimal calibration of the SLEUTH land use change model, Transactions in GIS, 2007, 11(1): 29-45.
    Eastman J R, Solorzano L A, Van Fossen M E. Transition potential modeling for land-cover change. In: Maguire D J, Batty M, Goodchild M F (eds.), GIS, spatial analysis, and modeling. California, ESRI Press, 2005, pp 357-385.
    Engelen G, White R, Inge Ulgee, et al. Using cellular automata for integrated modeling of socio-environmental systems. Environmental Monitoring and Assessment, 1995, 34: 203-214.
    Evans T P, Kelley H. Multi-scale analysis of a household level agent-based model of land cover change. Journal of Environmental Management, 2004, 72(1-2): 57-72.
    Fang S, Gertner G Z, Sun Z, et al. The impact of interactions in spatial simulation of the dynamics of urban sprawl. Landscape and Urban Planning, 2005, 73(4): 294-306.
    Flamm R O, Turner M G. Alternative model formulation for a stochastic simulation of landscape change. Landscape Ecology, 1994, 9 (1): 37-46.
    Forman, R T T, Godron M. Landscape ecology. New York, John Wiley, 1986.
    García-Frapolli E, Ayala-Orozco B, Bonilla-Mohenob M, et al. Biodiversity conservation, traditional agriculture and ecotourism: Land cover/land use change projections for a natural protected area in the northeastern Yucatan Peninsula, Mexico. Landscape and Urban Planning, 2007, 83(2-3): 137-153.
    Geymen A, Baz I. Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area. Environmental Monitoring and Assessment, 2008, 136(1-3): 449-459.
    Goetz S J, Smith A J, Jantz C, et al. Monitoring and predicting urban land use change: applications of multi-resolution multi-temporal satellite data. In: Proceedings of the IEEE International Geoscience and Remote Sensing Symposium. Toulouse, France, 2003, pp. 1567-1569.
    Gustafson E J, Parker G R. Relationships between land cover proportion and indices of landscape spatial pattern. Landscape Ecology, 1992, 7(2): 101-110.
    Haines-Young R, Chopping M. Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Progress in Physical Geography, 1996, 20(4): 418-445.
    Howard D M, Howard P J A, Howard D C. A markov model projection of soil organic carbon stores following land use changes. Journal of Environmental Management, 1995, 45:287-302.
    Huang Y F, Chen X, Humlg G H, et a1. GIS-based distributed model for simulating run of and sediment load in the Malian River Basin. Hydrobiologia, 2003, 494: 127-134.
    Hulst R. On the dynamics of vegetation: Markov chains as models of succession. Plant Ecology, 1979, 40(1): 3-14.
    Itami R M. Simulation spatial dynamics: cellular automata theory. Landscape and Urban Planning, 1994, 30: 27-47.
    Kalnay E, Cai M. Impact of urbanization and land use change on climate. Nature, 2003, 423: 528-531.
    Kamusoko C, Aniya M, Adi B, et al. Rural sustainability under threat in Zimbabwe-Simulation of future land use cover changes in the Bindura district based on the Markov-cellular automata model. Applied Geography, 2009, 29(3): 435-447.
    Kasetkasem T, Arora M K, Varshney P K. Super-resolution land cover mapping using a Markov random field based approach. Remote Sensing of Environment, 2005, 96: 302-314.
    Lambin E F. Modelling and monitoring land-cover change processes in tropical regions. Progress in Physical Geography, 1997, 21(5):375-393.
    Lambin E F, Rounsevell M, Geist H. Are current agricultural land use models able to predict change in land use intensity? Agriculture, Ecosystem and Environment, 2000, 82:321-331.
    Li H, Reynolds J F. Modeling effects of spatial pattern, drought, and grazing on rates of rangeland degradation: a combined Markov and cellular automaton approach. In: Quattrochi D A, Goodchild M F (eds.), Scale in Remote Sensing and GIS. Boca Raton, Florida: Lewis Publishers, 1997, pp 211-230.
    Li X, Yeh A G O. Modeling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science, 2000, 14(2): 131-152.
    Li X. Constrained CA-Model for the simulation and planning of sustainable urban forms by Using GIS. Environment and Planning B.2001, 28: 733-753.
    Liu X H, Andersson C. Assessing the impact of temporal dynamics on land use change modeling. Computer, Environment and Urban Systems, 2004, 28: 107-124.
    Liu Y, Phinn S R. Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers, Environment and Urban Systems, 2003, 27: 637-658.
    Lopez E, Bocco G, Mendoza M, et al. Predicting land cover and land use change in the urban fringe: a case in Morelia city, Mexico. Landscape and Urban Planning, 2001, 55(4): 271-285.
    Maria de Almeida C, Batty M, Vieira Monteiroa A M, et al. Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation. Computers, Environment and Urban Systems, 2003, 27: 481-509.
    Muller M R, Middleton J. A Markov model of land use change dynamics in the Niagara region, Ontario, Canada. Landscape Ecology, 1994, 9(2): 151-157.
    Myint S W, Wang L. Multicriteria decision approach for land use land cover change using Markov chain analysis and a cellular automata approach. Canadian Journal of Remote Sensing, 2006, 32(6): 390-404.
    Olsen E R, Ramsey R D, Winn D S. Modified fractal dimension as a measure of landscape diversity. Photogrammetric Engineering and Remote Sensing, 1993, 59: 1517-1520.
    O'neill R V, Krummel J R, Gardner R H, et al. Indices of landscape pattern. Landscape Ecology, 1988, 1(3): 153-162.
    Parker D C, Manson S M, Janssen M A, et al. Multi-agent systems for the simulation of land-use and land-cover change: a review. Annals of the Association of American Geographers, 2003, 93(2): 314-337.
    Phipps M. From local to global: The lesson of cellular automata. In: Deangelis D L, Gross L J (eds.), Individual based models and approaches in ecology: Populations, communities and ecosystems. New York, Chapman and Hall, 1992, pp 165-187.
    Pijanowski B C, Brown D G, Shellito B A, et al. Using neural nets and GIS to forecast land use changes: A land transformation model. Computers, Environment and Urban Systems, 2002, 26(6): 553-575.
    Pinder J E, Kroh G C, White J D, et al. The relationships between vegetation type and topography in Lassen Volcanic National Park. Plant Ecology, 1997, 131(1): 17-29.
    Pontius R G, Cornell J D, Hall C A S. Modeling the spatial pattern of land-use change with GEOMOD2: Application and validation for Costa Rica. Agriculture, Ecosystems and Environment, 2001, 1775: 1-13.
    Riitters K H, O'neill R V, Jones K B. Assessing habitat suitability at multiple scales: a landscape-level approach. Biological Conservation, 1997, 81: 191-202.
    Shannon C E, Weaver W. The mathematical theory of communication. Urbana: University of Illinois Press, 1949.
    Silverton J, Holtier S, Johnson J, et al. Cellular automaton models of interspecific competition for space-the effect of pattern on process. Journal of Ecology, 1992, 80: 527-534.
    Soares-Filho B S, Coutinho-Cerqueira G, Lopes-Pennachin C. DINAMICA-a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecological Modelling, 2002, 154: 217-235.
    Syphard A D, Clarke K C, Franklin J. Using a cellular automaton model to forecast the effects of urban growth on habitat pattern in southern California. Ecological Complexity, 2005, 2: 185-203.
    Ter Braak C J F. Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology, 1986, 67: 1167-1179.
    Theobald D M, Hobbs N T. Forecasting rural land-use change: a comparison of regression and spatial transition-based models. Geographical and Environmental Modelling, 1998, 2(1): 65-82.
    Tobler W R A. Computer movie simulating urban growth in the Detroit region. Economic Geography, 1970, 46: 234-240.
    Torrens P M. SprawlSim: modeling sprawling urban growth using automata-based models. In: Parker D, Berger T, Manson S (eds.), Agent-based models of land-use/land-cover change. Beigium, LUCC International Project office, 2003, pp 72-79.
    Torrens P M. Geosimulation and its application to urban growth modeling. Berlin, Springer, 2006a.
    Torrens P M. Simulating sprawl. Annals of the Association of American Geographers, 2006b, 96(2): 248-275.
    Turner M G. Spatial simulation of landscape changes in Georgia: a comparison of 3 transition models. Landscape Ecology, 1987, 1: 29-36.
    Turner M G. A Spatial simulation model of land use changes in a piedmont country in Georgia. Applied Mathematics and Computation, 1988, 27(1): 39-51.
    Turner M G. Spatial and temporal analysis of landscape patterns. Landscape Ecology, 1990, 4(1): 21-30.
    Turner M G, Gardner R H. Quantitative methods in landscape ecology: the analysis and interpretation of landscape heterogeneity. New York: Springer, 1990.
    Veldkamp A, Verbug P H, Kok K, et al. The need for scale sensitive approaches in spatially explicit land use change modeling. Environmental Modeling and Assessment, 2001, 6: 111-121.
    Waddell P. Modeling urban development for land use, transportation, and environmental planning. Journal of the American Planning Association, 2002, 68(3): 297-314.
    Wang X, Li T, Xu Q, et al. Study on the distribution of non-point source pollution in the watershed of Miyun reservoir, Beijing, China. Water Science and Technology, 2001, 44(7): 35-40.
    Wang Y, Zhang X. A dynamic modelling approach to simulate socioeconomic effects on landscape changes. Ecological Modelling, 2001, 140: 141-162.
    Ward D P, Murray A T, Phinn S R. An optimized cellular automata approach for sustainable urban development in rapidly urbanizing regions. International Journal of Geographical Information Science, 1999, 7(5): 235-250.
    Weng Q. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. Journal of Environmental Management, 2002, 64: 273-284.
    White R, Engelen G. Cellular automata and fractal urban form: a cellular modeling approach to the evolution of urban land use patterns. Environment and Planning A, 1993, 25: 1175-1189.
    White R, Engelen G. Cellular automata as the basis of integrated dynamic regional modelling. Environment and Planning B, 1997, 24: 235-246.
    White R, Engelen G, Uljee I. The use of constrained cellular automata for high-resolution modeling of urban land use dynamics. Environment and Planning B, 1997, 24(3): 323-343.
    White R, Engelen G. High-resolution integrated modeling of the spatial dynamics of urban and regional system. Computer, Environment and Urban System, 2000, 24: 383-400.
    Wu F. SimLand: A prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules, International Journal of Geographical Information Science, 1998a, 12(1): 63-82.
    Wu F. Simulating urban encroachment on rural land with fuzzy-logic-controlled cellular automata in a geographical information system. Journal of Environmental Management, 1998b, 53(4): 293-308.
    Wu F. The new structure of building provision and the transformation of the urban landscape in metropolitan Guangzhou, China. Urban Studies, 1998c, 35(2): 259-283.
    Wu F. An experiment on the generic polycentricity of urban growth in a cellular automatic city. Environment and Planning B: Planning and Design, 1998d, 25: 731-752.
    Wu F. Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Science, 2002, 16(8): 795-818.
    Wu F, Webster C J. Simulation of land development through the integration of cellular automata and multi criteria evaluation. Environment and Planning B, 1998, 25:103-126.
    Wu F, Yeh A G O. Changing spatial distribution and determinants of land development in Chinese cities in the transition from a centrally planned economy to a socialist market economy: A case study of Guangzhou. Urban Studies, 1997, 34(11): 1851-1879.
    Xie Y. A generalized model for cellular urban dynamics. Geographical Analysis, 1997, 28: 350-373.
    Zhang J T. A study on relations of vegetation, climate and soils in Shanxi Province, China. Plant Ecology, 2002, 162: 23-31.
    白顺江,陆贵巧,谷建才.雾灵山自然保护区不同森林类型枯落物水文作用研究.河北农业大学学报, 2006, 29(3): 49-52.
    柏延臣,王劲峰.结合多分类器的遥感数据专题分类方法研究.遥感学报, 2005, 9(5): 555-563.
    摆万奇,阎建忠,张镱锂.大渡河上游地区土地利用/土地覆被变化与驱动力分析.地理科学进展, 2004, 23(1): 71-78.
    摆万奇,赵世洞.土地利用/覆盖变化研究模型综述.自然资源学报, 1997, 12(2): 169-175.
    鲍全盛,曹利军,王华东.密云水库非点源污染负荷评价研究.水资源保护, 1997, (1): 8-14.
    毕晓丽,周睿,刘丽娟等.泾河沿岸景观格局梯度变化及驱动力分析.生态学报, 2005, 25(5):1041-1047.
    卜振军,韩富贵,王娟等.密云水库水源保护区水污染及防治.北京水务, 2007, 3: 43-44,50.
    蔡为民,唐华俊,陈佑启等.近20年黄河三角洲典型地区农村居民点景观格局.资源科学, 2004, 26(5): 89-97.
    蔡运龙.土地利用/土地覆被变化研究:寻求新的综合途径.地理研究, 2001 ,20 (6): 645-652.
    曹宏彬. 3S技术在水土保持动态监测中的应用.水利水电工程设计, 2005, 3: 41-43.
    曹中初,孙苏南. CA和GIS的集成用于地理信息的动态模拟和建模.测绘通报, 1999, (11): 7-9.
    车洪军,程兵峰,王秀丽.密云、官厅水库2003年来水量较少原因分析.海河水利, 2004, 2: 17-18.
    陈建刚,侯旭峰.密云水库集水区水土流失及其防治对策.北京水利, 2001, 1: 32-33.
    陈健飞,刘卫民. Fuzzy综合评判在土地适宜性评价中的应用.资源科学, 1999, 21(4): 71-74.
    陈龙泉,郑海金.基于Markov CA的土地利用/土地覆盖变化动态模型研究.测绘信息与工程, 2004, 1: 36-38.
    陈佑启, Peter H Verburg.中国土地利用/覆被的多尺度空间分布特征分析.地理科学, 2000, 20(3): 197-202.
    陈圆,马钦彦,王玉涛等.北京密云水库及入库径流水化学特征分析.北京林业大学学报, 2007, 29 (3): 105-111.
    除多,张镱锂,郑度.拉萨地区土地利用变化情景分析.地理研究, 2005, 24(6): 869-877.
    丁泽斌.论雾灵山自然保护区的生态威胁因素.河北林业科技, 2005, z1: 53-54.
    董文福,李秀彬.潮白河密云水库流域水资源问题分析.环境科学与技术, 2006, 29(2): 58-60.
    董悦安,孟庆义,张景峰等.密云水库表底层水体交换实验研究.北京水利, 2004, 2: 45-46.
    杜桂森,孟繁艳.密云水库水质现状及发展趋势.环境科学, 1999, 20(2): 110-112.
    段增强,张凤荣,苗利梅.基于IPAT-S脚本语言的土地利用情景分析及其应用.农业工程学报, 2006, 22(7):75-81.
    甘红,刘彦随,王大伟.土地利用类型转换的人文驱动因子模拟分析.资源科学, 2004, 26(2): 88-93.
    甘敬.北京山区森林健康评价研究.北京林业大学博士学位论文, 2008.
    高成德.密云水库集水区(北京境区)水源保护林最优林种结构的研究.林业科技通讯, 2000, 5: 30-31.
    高成德,田晓瑞.北京密云水库集水区水源保护林最佳森林覆盖率研究.林业实用技术, 2005, 8: 3-5.
    高甲荣.北京密云水库集水区水源保护林建设与发展对策.水土保持通报, 1999, 19(5): 1-6.
    高阳,高甲荣.密云水库集水区水源涵养林生态价值计算的一种新方法.林业调查规划, 2006, 31(1):63-66.
    高迎春,姚治君,刘宝勤等.密云水库入库径流变化趋势及动因分析.地理科学进展, 2002, 21(6): 546-552.
    郭丽英,王道龙,邱建军.环渤海区域土地利用类型动态变化研究.地域研究与开发, 2009, 28(3): 92-95.
    郭鹏,薛惠锋,赵宁等.基于复杂适应系统理论与CA模型的城市增长仿真.地理与地理信息科学, 2004, 20(6): 69-72, 80.
    哈力克瓦哈甫,依米提海米提,特依拜塔西甫拉提.绿洲耕地变化趋势及其驱动力—塔里木盆地南部策勒绿洲为例.地理学报, 2004, 59(4): 608-614.
    韩玲玲,何政伟,唐菊兴等.基于CA的城市增长与土地增值动态模拟方法探讨.地理与地理信息科学, 2003, 19(2): 32-35.
    韩文权,常禹.景观动态的Markov模型研究.生态学报, 2004, 24 (9): 1958-1969.
    韩文权,常禹,胡远满.景观格局优化研究进展.生态学杂志, 2005, 24(12): 1487 -1492.
    郝丽娟.密云水库流域降雨径流关系变化及影响因素分析.北京水利, 2004, 3: 41-43.
    何春阳.北京地区城市化过程中土地利用/覆盖变化动力学研究.?北京师范大学博士学位论文, 2003.
    何春阳,陈晋,史培军等.基于CA的城市空间动态模型研究.地球科学进展, 2002, 17(2):188-195.
    何春阳,陈晋.大都市区城市扩展模型-以北京城市扩展模拟为例.地理学报, 2003, 58(2): 294- 304.
    何春阳,史培军,陈晋等.基于系统动力学模型和元胞自动机模型的土地利用情景模型研究.中国科学, D辑, 2005, 35(5): 464-473.
    贺然,王棒,朱国平等.密云水库北京集水区土壤侵蚀预测.农业环境科学学报, 2007, 26(B10): 579-582.
    贺伟,张国权.密云水库上游水土保持地理信息系统.北京水利, 1996, 4: 16-19.
    侯西勇,常斌,于信芳.基于CA-Markov的河西走廊土地利用变化研究.农业工程学报, 2004, 20(5): 286-291.
    胡艳霞,周连第,严茂超等.北京密云水库生态经济系统特征、资产基础及功能效益评估.自然资源学报, 2007, 22(4): 497-506
    华文,丁建中,张燕等.温州市土地利用变化与利用效率分析.土壤, 2001, 33(2): 81-85.
    黄生斌,刘宝元,刘晓霞等.密云水库流域农业非点源污染基本特征分析.农业环境科学学报, 2007, 26(4): 1219-1223.
    黄生斌,叶芝菡,刘宝元.密云水库流域非点源污染研究概述.中国生态农业学报, 2008, 16(5): 1311-1316.
    黄跃进,唐锦春,孙柄楠.基于GIS的农用地土地适宜性评价模型的建立.浙江林学报, 1999, 16(4): 406-410.
    贾宝全,慈龙骏.绿洲景观生态研究.北京:科学出版社, 2003.
    贾华,祝国瑞.土地利用变化研究中的细胞自动机与灰色局势决策.武汉测绘科技大学学报, 1998, 24(2): 166-169.
    姜广辉,张凤荣,孔祥斌.北京山区农村居民点整理用地转换方向模拟.农业工程学报, 2009, 25(2): 214-221.
    姜云天,谭燕梅.雾灵山自然保护区的森林资源及其动态.河北林果研究, 2001, 16(3): 274-279.
    焦峰,秦伯强. GIS支持下的小尺度土地驱动力研究—以宜兴市湖滏小流域为例.长江流域资源与环境, 2003, 12(3): 205-210.
    解修平,周杰,张海龙等.基于景观生态和马尔可夫过程的西安地区土地利用变化分析.资源科学, 2006, 28(6): 175-181.
    金小刚.基于Matlab的元胞自动机的仿真设计.计算机仿真, 2002, 19(4): 27-30.
    康东伟,赵媛媛.雾灵山自然保护区的生态效应与保护对策.中国环境管理干部学院学报, 2007, 17(4): 22-24, 57.
    孔凡斌.试论森林生态补偿制度的政策理论、对象和实现途径.西北林学院学报, 2003, 18(2): 101-104,115.
    黎夏,叶嘉安.约束性单元自动演化CA模型及可持续发展形态的模拟.地理学报, 1999, 54(4): 289-298.
    黎夏,叶嘉安.主成分分析与Cellular Automata在空间决策与城市模拟中的应用.中国科学(D辑), 2001, 31(8): 683-690.
    黎夏,叶嘉安.基于神经网络的单元自动机CA及真实和优化的城市模拟.地理学报, 2002, 57(2): 159-166.
    黎夏,叶嘉安.基于神经网络的元胞自动机及模拟复杂土地利用系统.地理研究, 2005, 24(1): 19-27.
    黎夏,伍少坤.面向对象的地理元胞自动机.中山大学学报:自然科学版, 2006, 45(3): 90-94.
    李德成.利用马氏过程模拟和预测土壤侵蚀的动态演变.遥感学报, 1995, 10(2): 89-96.
    李芬.森林生态效益补偿的研究现状及趋势分析.环境科学与管理, 2006, 7: 31-33, 38.
    李海涛.暖温带山地森林生态系统的能量平衡及蒸发散研究. 1997.见:陈灵芝主编,暖温带森林生态系统结构与功能的研究.北京:科学出版社.
    李慧敏,孟凡艳,杜桂森等.密云水库东西库区的水质与浮游藻类分析.湖泊科学, 2007,19(2): 146-150.
    李俊波,华珞,冯琰等.密云水库周边地区土壤侵蚀状况的有效性判定.自然灾害学报, 2005, 14(4): 8-13.
    李巧茹,魏连雨,马寿峰.基于马尔柯夫过程的城市交叉口车辆到达模型.长安大学学报, 2004, 24(3): 54-61.
    李仁东,程学军,随小丽.江汉平原土地利用的时空变化及其驱动因素分析.地理研究, 2003, 22(4): 423-431.
    李书娟,曾辉,夏洁等.景观空间动态模型研究现状和应重点解决的问题.应用生态学报, 2004, 15(4): 701-706.
    李团胜.陕西省土地利用动态变化分析.地理研究, 2004, 23(2): 157-164.
    李小英,彭望琭,曹彤.在遥感时间序列数据分析中马尔柯夫链方法与空间信息最佳结合的探讨.北京师范大学学报(自然科学版), 2002, 38(5): 700-705.
    李新琪.新疆艾比湖流域平原区景观生态安全研究.华东师范大学博士学位论文, 2008.
    李勇,苏文贵,肖笃宁.地理信息系统在典型区土地利用适宜性评价中的应用-以大洼县小三角洲为例. 土壤, 1996, 28(1): 14-20.
    李月臣,何春阳.中国北方土地利用/覆盖变化的情景模拟与预测.科学通报, 2008, 53(6): 713-723.
    李子君,李秀彬,朱会义等.降水变化与人类活动对密云水库入库泥沙量的影响,北京林业大学学报, 2008, 30(1): 101-107.
    梁发超,张文开,居风云.基于MARKOV—灰色模型的土地利用结构变化预测.沈阳大学学报, 2008, 20(6): 110-113.
    梁爽,姜楠,谷树忠.城市水源地农户环境保护支付意愿及其影响因素分析-以首都水源地密云为例. 中国农村经济, 2005, 2: 55-60.
    廖和平.未利用适宜性评价方法研究—以攀枝花市仁和区为例.西南大学学报(自然科学版), 1997, 22(2): 199-205.
    刘璨,马广仁.密云水库水源涵养林环境经济政策研究.林业经济, 1999, 4: 18-27.
    刘凤芹,吴伟,鲁绍伟等.北京密云水库集水区景观生态分类.水土保持研究, 2006, 13(4): 133-136.
    刘纪远.中国资源环境遥感宏观调查与动态分析.北京:中国科学技术出版社, 1996, 23-28.
    刘纪远,张增祥.中国近期土地利用变化的空间格局分析.中国科学: D辑, 2002, 32(12): 1031-1040.
    刘纪远,庄大方,张增祥等.中国土地利用时空数据平台建设及其支持下的相关研究.地球信息科学, 2002, 3: 1-8.
    刘继生,陈彦光.基于GIS的细胞自动机模型与人地关系的复杂性探讨.地理研究, 2002, 21(2): 155-162.
    刘家福,王平,李京等.基于Markov模型的长岭县土地利用时空变化研究.水土保持研究, 2009, 16(3): 16-19.
    刘晶,彭补拙.锡山市土地利用变化的社会驱动力分析.土壤, 2001, 33(6): 295-299.
    刘妙龙,陈鹏.城市空间扩散增长模型与模拟.人文地理, 2004, 19(2): 6-11.
    刘起峰,周新涛,李涛等.冬季密云水库水的预臭氧氧化处理研究.环境污染与防治, 2008, 30(7): 5-8.
    刘强,何岩,章光新.松嫩平原西部荒漠化景观动态及驱动力研究-以吉林省大安市为研究区域.干旱区资源与环境, 2006, 20(1): 93-98.
    刘世海,于志民.北京密云水库集水区板栗林水化学元素性质研究,北京林业大学学报, 2001, 23(2): 12-15.
    刘霞,杜桂森,张会等.密云水库的浮游植物及水体营养程度.环境科学研究, 2003, 16(1): 27-29.
    刘县明. CA Markov复合模型及其在城市土地利用中的应用研究.南昌大学硕士学位论文, 2008
    刘彦随,陈百明.中国可持续发展问题与土地利用/覆被变化研究.地理研究, 2002, 21(3): 324-330.
    刘耀林,刘艳芳,明冬萍.基于灰色局势决策规则的元胞自动机城市扩展模型,武汉大学学报(信息科学版), 2004, 29(1): 7-13.
    卢玲,李新,程国栋等.黑河流域景观结构分析.生态学报, 2001, 21(8): 1217-1225.
    陆汝成,黄贤金,左天惠等.基于CLUE-S和Markov模型的土地利用情景模拟研究—以江苏省环太湖地区为例.地理科学, 2009, 29(4): 577-581.
    路炳军,袁爱萍,李永贵等.密云水库上游典型水保措施减少面源污染效益分析.中国水土保持, 2007, 1: 30-31.
    吕洪滨.密云水库可持续利用研究.海河水利, 2004, 2: 51-53.
    罗名海.利用CA模型进行城市空间增长动力的研究.武汉大学学报(信息科学版), 2005, 30(1): 51-55.
    罗平,杜清运,雷元新等.城市土地利用演化CA模型的扩展研究.地理与地理信息科学, 2004a, 20(4): 48-51.
    罗平,杜清运,雷元新等.地理特征元胞自动机及城市土地利用演化研究.武汉大学学报:信息科学版, 2004b, 29(6): 504-512.
    马安青,陈东景,王建华等.基于RS和GIS的陇东黄土高原土地景观格局变化研究.水土保持学报, 2002, 16(3): 56-59.
    马力,杨新民,吴照柏等.不同土地利用模式下土壤侵蚀空间演化模拟.水土保持通报, 2003, 23(1): 59-51.
    蒙吉军,李正国,吴秀芹. 1995-2000年河西走廊土地利用变化研究.自然资源学报, 2003, 18(6): 645-651.
    牟磊.基于GIS和CA模型的土地利用变化研究.新疆大学硕士学位论文,2007.
    屈广义,郭怀成.北京密云水库地区可持续发展模式研究.中国人口资源与环境, 2002, 12(2): 81-86.
    任志远.土地利用变化及驱动因素分析.干旱区研究, 2003, 20(3): 202-205.
    任志远,张艳芳.土地利用变化与生态安全评价.北京:科学出版社, 2003.
    沈泽昊,张新时.三峡大老岭地区森林植被的空间格局分析及其地形解释.植物学报, 2000, 42(10): 1089-1095.
    沈志勇.雾灵山自然保护区.行游数码, 2008, 4: 110-111.
    史培军,宫鹏,李晓兵等.土地利用/覆盖变化研究的方法与实践.北京:科学出版社, 2000a.
    史培军,陈晋,潘耀忠.深圳市土地利用变化机制分析.地理学报, 2000b, 55(2): 151-160.
    史培军,李京,潘耀忠等.生态资产遥感测量.北京:科学出版社, 2005.
    宋福春,张香,张文林等.北京雾灵山自然保护区冬季鸟类物种多样性调查.动物学杂志, 2005, 40(2): 50-54.
    宋如华,齐实,孙保平等.区域土地资源的适宜性评级和空间布局.土壤侵蚀与水土保持学报, 1997, 3(3): 23-30.
    宋轩,石端晓,张学雷等.基于元胞自动机的郑州市区土地利用变化研究.河南科学, 2008, 26(8): 971-976.
    宋毓.基于GIS和Geo CA的土地利用模型研究-以阿克苏河流域为例.西安:陕西师范大学学位论文, 2005.
    孙贤斌,刘红玉,李玉凤等.基于CA Markov模型土地利用对景观格局影响辨识.生态与农村环境学报, 2009, 25(1): 1-7.
    孙战利.空间复杂性与地理元胞自动机模拟研究.地球信息科学, 1999, (2): 32-37.
    索安宁,巨天珍,熊友才等.泾河流域土地利用区域分异与驱动力的关系.中国水土保持科学, 2006, 4(6): 75-80.
    唐国平,杨志峰.密云水库库区人口,经济发展与水环境关系的定量分析.水文水资源, 1999, 20(3): 4-6.
    田静毅.秦皇岛市生态环境信息图谱模型及生态安全研究.吉林大学博士学位论文, 2007.
    仝川,郝敦元,高霞等.利用马尔柯夫过程预测锡林河流域草原退化格局的变化.自然资源学报, 2002, 17(4): 488-493.
    汪明冲.基于RS与GIS的黄土丘陵沟壑区土壤侵蚀的景观格局分析与模拟.西北师范大学硕士学位论文, 2007.
    汪雪格.吉林西部生态景观格局变化与空间优化研究.吉林大学博士学位论文, 2008.
    王春峰.用遥感和单元自动演化方法研究城市扩展问题.北京:测绘出版社, 2002.
    王桂新,陈萍.城市未来发展持续性评价决策支持系统构建和设计.中国人口资源与环境, 2006, 16(5): 41-46.
    王桂忠,王德艺.雾灵山自然保护区森林的天然更新.河北林果研究, 2000, 15(1): 15-19.
    王海鹰.三维虚拟城市自动生成方法研究.河南大学硕士学位论文, 2008.
    王红,闾国年.细胞自动机及在南京城市演化预测中的应用.人文地理, 2001, 17(1): 47-50.
    王家骥.应用卫星遥感技术调查和评价潮白河密云水库流域的植被.农村生态环境, 1989, 1: 26-30.
    王家骥.潮白河密云水库流域自然景观的分级和评价.环境科学研究, 1992, 5(4): 41-45.
    王静怡,王晓燕.密云水库流域径流变化特征及影响因素分析.首都师范大学学报:自然科学版, 2007, 28(2): 89-97.
    王良健,刘伟,包浩生.梧州市土地利用变化的驱动力研究.经济地理, 1999, 14 (4): 74-79.
    王让会,张慧芝,游先祥等.塔里木河流域生态景观格局的遥感信息提取与分析.北京林业大学学报, 2003, 25(2): 43-47.
    王思远,刘纪远,张增祥等.近10年中国土地利用格局及其演变.地理学报, 2002, 57(5): 523-530.
    王晓燕,蔡新广.北京密云水库流域非点源污染现状研究.环境科学与技术, 2002, 25(4): 1-3.
    王晓燕,郭芳,蔡新广等.密云水库潮白河流域非点源污染负荷.城市环境与城市生态, 2003, 16(1): 31-33.
    王晓燕,王晓峰,汪清平等.北京密云水库小流域非点源污染负荷估算.地理科学, 2004, 24(2): 227-231.
    王晓燕,秦福来,欧洋等.基于SWAT模型的流域非点源污染模拟-以密云水库北部流域为例.农业环境科学学报, 2008, 27(3): 1098-1105.
    王晓燕,汪清平.密云水库流域畜禽养殖粪便的污染影响及污染控制.农业环境与发展, 2008, 3: 65-68.
    王行风,汪云甲,李永峰.基于生命周期理论的煤矿区土地利用演化模拟.地理研究, 2009, 28(2): 379-390.
    王秀兰,包玉海.基于CA模型的土地利用变化研究.地理科学进展, 1999, 18(1): 81-87.
    王秀兰.土地利用/土地覆盖变化中的人口因素分析.资源科学, 2000, 22(3): 39-42.
    王学雷,吴宜进.马尔柯夫模型在四湖地区湿地景观变化研究中的应用.华中农业大学学报, 2002, 21(3): 288-291.
    王雪军,杨建新,孙玉军.晋陕蒙接壤地区土地利用格局动态遥感研究与预测.水土保持学报, 2002, 16(4): 58-61.
    王亚娟,赵志新,吴海山.白河堡水库向密云水库调水分析.北京水利, 2004, 3: 44-46.
    王彦丽,李忠峰.基于RS与GIS支持下的定边县土地利用变化分析与发展趋势研究.安徽农业科学, 2007, 35(20): 6226-6227.
    王铮.城市土地利用演变信息的数据挖掘—以上海市为例.地理研究, 2002, 21(6): 675-681.
    韦素琼,陈键飞.福建省土地利用动态变化及趋势预测.福建师范大学学报(自然科学版), 2003, 19(4): 85-91.
    魏秀菊,胡振琪,何蔓.土地整理可能引发的生态环境问题及宏观管理对策.农业工程学报, 2005, 21(2): 127-130.
    温仲明,焦峰,张晓萍等.纸坊沟流域近60年来土地利用景观变化的环境效应.生态学报, 2004, 24(9): 1903-1909.
    邬建国.景观生态学—格局、过程、尺度与等级.北京:高等教育出版社, 2000.
    伍业刚,李哈滨.景观生态学的理论发展.见:刘建国.当代生态学博论.北京:中国科学技术出版社, 1992.
    武晓波,赵健,魏成阶等.细胞自动机模型用于城市发展模拟的方法初探-以海口市为例.城市规划, 2002, 26(8): 69-73.
    夏军,李璐,严茂超等.气候变化对密云水库资源的影响及其适应性管理对策.气候变化研究进展, 2008, 4(6): 319-323.
    肖笃宁.景观生态学—理论、方法及应用.北京:中国林业出版社, 1991.
    肖笃宁.景观生态学研究进展.长沙:湖南科技出版社, 1999.
    肖寒,欧阳志云.森林生态系统服务功能及其生态经济价值评估初探—以海南岛尖峰岭热带森林为例. 应用生态学报, 2000, 11(4): 481-484.
    肖寒,欧阳志云.海南岛景观空间结构分析.生态学报, 2001, 21(1): 20-27.
    肖洋,陈丽华,余新晓等.北京密云水库油松人工林对降水分配的影响.水土保持学报, 2007, 21(3): 154-157
    谢志霄,肖笃宁.城郊景观动态模型研究-以沈阳市东陵区为例,应用生态学报, 1996, 7(1): 77-82.
    谢庄,雷振发.密云水库上游地区降水分布特征及其预报.北京气象, 1996, 3: 7-9.
    熊利亚,常斌,周相广.基于地理元胞自动机的土地利用变化研究.资源科学, 2005, 27(4): 38-43.
    徐建刚,陈昌勇,沈青.基于GIS-CA模型的城镇空间发展分析-以吴江市临沪经济区为例.规划50年-2006中国城市规划年会论文集(下册), 2006.
    徐昔保.基于GIS与元胞自动机的城市土地利用动态演化模拟与优化研究.兰州大学博士学位论文, 2007.
    杨光.基于3S的盐池县景观格局及荒漠化动态研究.北京林业大学博士学位论文, 2008.
    杨国清,刘耀林,吴志峰.基于CA Markov模型的土地利用格局变化研究.武汉大学学报(信息科学版), 2007, 32(5): 414-418.
    杨青生.基于元胞自动机的土地资源节约利用模拟.自然资源学报, 2009, 24(5): 753-762.
    叶亚妮,施宏伟.国外流域水资源管理模式演进及对我国的借鉴意义.西安石油大学学报:社会科学版, 2007, 16(2): 11-16.
    于涛,沈浩,仲嘉亮.基于CA-Markov模型的新疆克州土地利用动态模拟研究.新疆环境保护, 2008,30(1): 11-14.
    于秀玲.非点源污染对密云水库水质的影响.中国环境科学研究院科学论文集(1980-1990).北京:中国环境科学出版社, 1990, 27-31.
    喻锋.基于Markov-CA的土地利用变化预测研究.国土资源情报, 2009, 4: 38-46.
    袁秀,邢韶华,向魏忠等.北京雾灵山自然保护区的植物资源.林业调查规划, 2006, 31(1): 42-46.
    袁荫棠.概率论与数理统计.北京:中国人民大学出版社, 1990.
    岳跃民,王克林,张伟等.基于典范对应分析的喀斯特峰丛洼地土壤—环境关系研究.环境科学, 2008, 29(5): 243-249.
    翟慧敏,吴郭泉.基于CA的城市模型研究进展.山西建筑, 2009, 35(10): 20-21.
    张彪,李文华,谢高地等.北京市森林生态系统水源涵养功能.生态学报, 2008, 28(11): 5619-5624.
    张金屯.数量生态学.北京:科学出版社, 2004, 157-164.
    张蕾娜.基于水文站划分的子流域土地利用变化时空特征分析-以密云水库上游白河流域为例.国土与自然资源研究, 2004, 2: 46-47.
    张丽娟.密云水库水文特性分析.北京水务, 2007, 4: 40-42.
    张明.区域土地利用结构及其驱动因子的统计分析.自然资源学报, 1999, 14(4): 381-384.
    张明.榆林地区脆弱生态环境的景观格局与演化研究.地理研究, 2000, 19(1): 30-36.
    张山山.基于CA的时空过程模拟建模方法.武汉大学学报(信息科学版), 2004, 29(2): 175-178.
    张显峰,崔伟宏.运用RS、GPS和GIS技术进行大比例尺土地利用动态监测的实验研究.地理科学进展, 1999, 15(2): 15-21.
    张显峰,崔伟宏.基于GIS和CA模型的时空建模方法研究.中国图象图形学报, 2000, 5(A版)(12):1012-1018.
    张显峰,崔伟宏.集成GIS和细胞自动机模型进行地理时空过程模拟与预测的新方法.测绘学报, 2001, 30(2): 148-155.
    张滢,丁建丽.绿洲土地利用变化未来趋势预测及其调控研究.干旱区资源与环境, 2006, 20(6): 29-35.
    赵光,李木山.密云水库上游水土保持重点防治取得初步成效.中国水土保持, 1991, 8: 14-16.
    赵晶.上海城市土地利用与景观格局的空间演变.华东师范大学博士论文, 2004.
    赵丽,赵乔贵.建设用地需求量预测方法比较研究.地矿测绘, 2009, 25(1): 3-7.
    赵睿.干旱区LUCC时空特征分析及其模拟研究.新疆大学硕士学位论文, 2006.
    赵守彦,杨立宏.密云水库水污染源状况与水环境监测.北京水利, 1999, 6: 34-35.
    赵弈,李月辉.论景观的稳定性.景观生态学研究进展.长沙:湖南科学技术出版社, 1999.
    郑海金,华珞,欧立业.中国土地利用/土地覆盖变化研究综述.首都师范大学学报, 2003, 24(3): 89-95.
    郑玉涛,王晓燕,尹洁等.水源保护区不同类型村庄生活垃圾产生特征分析.农业环境科学学报, 2008, 27(4): 1450-1454.
    周成虎,孙战利,谢一春.地理元胞自动机研究.北京:科学出版社, 1999.
    朱德举.土地评价.北京:中国大地出版社, 2002.
    朱海涌,李新琪,仲嘉亮.基于CA-Markov模型的艾比湖流域平原区景观格局动态模拟预测.干旱环境监测, 2008, 22(3): 134-139.
    朱会义,何书金,张明.环渤海地区土地利用变化的驱动力分析.地理研究, 2001, 20(6): 669-678.
    朱守辉.基于CA模型的土地利用变化研究-以新疆鄯善县为例.安徽农业科学, 2009, 15: 6887-6891.
    左春刚,黄诗峰,杨海波等.密云水库水源地多时相遥感监测与分析.中国水利水电科学研究院学报, 2007, 5(3): 201-205.

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