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佛山市耕地变化驱动机理及空间布局优化研究
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摘要
耕地保护是我国的一项基本国策。耕地是土地的精华,耕地保护是实现粮食安全战略的重要措施与途径,是实现经济社会可持续发展的重要保障之一。目前我国正处在经济高速发展、城市化和工业化突飞猛进的时期,对建设用地的需求将进一步增长,从而增加了我国耕地保护的难度。面对有限的耕地资源既要保证“吃饭”又要保证“建设”的两难局面,不仅要保障工业化和城镇化进程,更要确保耕地质量底线和粮食安全。而这一难题在经济发达地区更为突出,已成为制约区域经济社会发展的“瓶颈”。
     论文以经济发达典型区域的广东省佛山市为例,利用数理统计、空间分析等方法,从佛山市实际情况出发,分析研究区耕地变化特征,利用时间序列分析、相关性分析以及回归分析法,对佛山市耕地利用变化驱动机制进行了研究,采用情景分析法结合地理学研究中的空间模拟技术,构建了三种土地动态变化情景,并对三种情景下耕地空间格局特征进行了模拟,分析了不同情境下,佛山市2015年和2030年耕地利用的特点。最后根据佛山市建设用地扩展特点与耕地空间分布特征,从技术、法律与经济角度,系统地提出了耕地保护的政策与措施。研究结果显示:
     (1)佛山市耕地保护形势比较严峻,耕地变化主要驱动力为人口、GDP、人均GDP、建设用地、固定资产投入以及工业生产总值,利用spss相关性分析显示,耕地数量与人口、GDP、人均GDP、建设用地、固定资产投入以及工业生产总值等因素呈显著相关,其关系数分别为:-0.952、-0.891、-0.874、-0.893、-0.956和-0.869。耕地空间布局变化主要影响因素为上述因素所引起的建设用地扩张。
     (2)耕地空间布局变化主要影响因素为建设用地扩张。佛山市建设用地可分为建设用地优先发展决策模式、保护优先决策模式以及发展与保护兼顾决策模式等三种情景。利用SLEUTH模型分别模拟了不同情境下,2015年和2030年佛山市城市扩展的特征。情景Ⅰ是基于建设用地优先发展情景,城市增长方式以离心式外延扩展为主,建设用地变化剧烈,虽然城镇用地经济产出增长迅速,同时也将伴随着耕地流失规模大、生态风险增加较快等不利后果;情景Ⅱ是保护优先决策模式,城市增长方式以向心式内部填充与更新改造和景观生态保护为主。建设用地变化节奏以及耕地占用量得到明显控制,耕地和生态得到很好的保护,但土地资源“瓶颈”制约相对突出;情景Ⅲ是基于发展与保护兼顾决策模式,城市增长方式以城乡结合部地区建设用地扩张为主,以边缘增长形式为辅,更趋向于可持续发展,是上述两种情景之间的折中型城乡用地优化情景,城镇用地扩张规模与速度处于上述两种情景之间,是一种兼顾发展与保护要求的“折中型”建设用地发展模式,也是最具参考价值的城乡用地优化方案。
     (3)在不同情景模式下,耕地空间分布特征显著。情景Ⅰ决策模式下,耕地和桑基鱼塘减少面积大、速度快,全市耕地减少49%以上,年减少速率达到2.2%以上。桑基鱼塘减少62%左右,年减少速率达到2.8%以上。耕地主要分布在高明区的西部和三水区北部两个集中区,桑基鱼塘主要分散在高明、三水、顺德和南海四区,顺德区和南海区原有的桑基鱼塘这一人工生态系统将逐步消失;情景Ⅱ决策模式下,耕地和桑基鱼塘减少受到严格控制,全市耕地减少13%左右,年减少速率不到0.6%。桑基鱼塘减少15%左右,年减少速率在0.7%左右。耕地主要分布三水区的东北部和南部地区,高明区的西北部地区以及南海区的东南部地区。桑基鱼塘主要分布在顺德区、南海区的西南部、三水区的东南部以及高明的东北地区;情景Ⅲ决策模式下,耕地和桑基鱼塘减少得到有效控制,全市耕地减少29%左右,年减少速率在1.3%左右。桑基鱼塘减少36%左右,年减少速率在1.6%左右。耕地主要分布高明区的西北部、三水区的东北部以及南海区的东南部地区。桑基鱼塘主要分布在顺德区中西部、南海区的西南部、三水区的东南部以及高明的东北地区。情景Ⅲ是介于情景Ⅰ和情景Ⅱ之间的折中型耕地布局优化情景,耕地和桑基鱼塘减少规模与速度处于两种情景之间,是一种兼顾发展与保护要求的“折中型”未来耕地空间布局模式,最具参考价值。
     (4)最后根据模拟结果,结合佛山市经济社会发展特征,从技术、法律与经济角度,提出建立建设用地和耕地动态监测和预警系统、实施建设用地空间管制制度、建立耕地保护激励机制等相应的优化调控措施和建议。
Farmland is land essence, The cultivated land protection is one of our basic state policies. It is not only the important measure&way to achieve food security strategy, but also one of the important guarantee to achieve sustainable economic and social development. At present, China is undergoing a period of rapid in which economic development and urbanization&industrialization is advancing by leaps and bounds. Therefore, the demand for construction land will further growth and the difficulty of the cultivated land protection is increasing. Facing the dilemma that the limited arable land resources have to guarantee both "dinner" and "construction",We should not only security industrialization and urbanization, but also to ensure the quality of cultivated land and food security still further. And the problem is more outstanding in the economic developed area and have become the "bottle-neck" to restricte the development of regional economy society.
     Taking the typical developed economy area--Foshan, Guangdong province, as an example, based on the statistics and spatial analysis methods, the dissertation analyzes the characteristics of cultivated land change in Foshan.And these comprehensive methods,including correlation analysis, area time series analysis, regression analysis etc.,are used in the dissertation to study the driving mechanism of foshan cultivated land use changes. And based on the scenario analysis combined with space simulation technology, three kinds of land dynamic change scene are constructed, and three situations of cultivated land space pattern are simulated. Under these situations,the dissertation analyzes the characteristics of land use of Foshan in2015and2030. Finally, according to the characteristics of construction land expansion and the spatial distribution of cultivated land in Foshan, The study puts forward systematically the policies and measures of cultivated land protection from the standpoints of technology, legal and economic. Research results show that:
     (1)The situation of cultivated land protection in Foshan is comparison severe.and the main driving factors of farmland change are population, GDP, per capita GDP and construction land, fixed assets investment and gross industrial production. The correlation analysis by SPSS shows that the quantity of cultivated land correlates dramaticlly with the population, GDP, per capita GDP and construction land, fixed assets investment and gross industrial production, and correlation coefficients are respectively-0.952、-0.891、-0.874、-0.893、-0.956and-0.869.The construction land expansion caused by above factors is the major effect factors of cultivated land space layout changing.
     (2) The major effect factor of cultivated land space layout changes is the construction land expansion. Foshan construction land can be divided into three decision-making modes,including the model of giving priority to construction land development, the mode of giving priority to protecting farmland and the mode of integrating the development and farmland protection. By using SLEUTH mode, the paper simulates the city expansion characteristics in2015and2030under three modes mentioned above. Based on scenario I, urban growth mode with centrifugal extension expansion is given priority to, construction land use change drastically. Although urban use economic output is growing rapidly, also will be accompanied with adverse consequences, such as cultivated land losing by large scale, ecological risk increasing quickly etc.; Based on scenario II, urban growth mode is centripetal filling and internal renewal and ecological protection mainly. Construction land use change rhythm and cultivated land change get a control, cultivated land and ecological get good protection, but land resources "bottleneck" restriction is relatively prominent; Based on scenario Ⅲ, the urban growth mode is primarily the construction land expansion in urban and rural areas, by edge growth complementary, have a tendency to sustainable development.The urban sprawl in the scale and speed is between two scenarios above. This is a "discount medium" construction land development mode of balancing development and protection requirements, and it is also the most reference value of the urban and rural land-use optimization scheme.
     (3) The spatial distribution characteristics of cultivated land is notable in different scenario. Based on scenario Ⅰ,farmland&mulberry fish ponds will reduce with large scale and fast speed, the cultivated land will reduce49%, at the rate of reduction2.2%per year. Mulberry fish ponds will reduce62%, at reducing rate2.8%per year. Farmland is mainly distributed in the west of Gaoming, the northern of Sanshui, and mulberry fish ponds are scattered mainly in Gaoming,Sanshui, Shunde and Nanhai. Mulberry fish ponds, this artificial ecosystem in Shunde and Nanhai will gradually disappear; Based on scenario Ⅱ, the loss of farmland&mulberry fish ponds, will be strictly controlled, the farmland will reduce13%or so, at reducing rate0.6%per year. Mulberry fish ponds, reduce about15%, at reducing rate around0.7%. The cultivated land is mainly distributed in the northeast and south of Sanshui, the northwest of Gaoming,and the southeast of Nanhai. Mulberry fish ponds are mainly distributed in Shunde, the southeast of Nanhai, the southwest of Sanshui and the northeast of Gaoming; Based on scenario Ⅲ, the shrinking of farmland and mulberry fish ponds are effectively controlled, the cultivated land will reduce29%, at the rate of reduction1.3%per year. Mulberry fish.ponds, reduce about36%, at reducing rate around1.6%per year. The main distribution of farmland is in northwest of Gaoming, the northeast of Sanshui,the southeastern of Nanhai. Mulberry fish ponds are mainly distributed in the mid-west of shunde,the southwest of Nanhai, and the northeast of Gaoming. Scenario Ⅲ is a fold medium farmland layout optimization scene, and it is also the most reference value of the farmland optimization scheme.
     (4) Finally,based on the simulation results and the development characteristics in Foshan, From the standpoints of technology, legal and economic,the dissertation puts forward the policies and measures of cultivated land protection, such as to implement the mechanisms of dynamic monitoring and advance-warning about construction land and the farmland, to implement construction land space control system, to establish incentive mechanism of cultivated land protection,
引文
1. American Farmland Trust(AFT).Farmland Information Center Fact Sheet[J/OL].http://www.farmland.org.
    2. ANTROP M. Landscape Change and the Urbanization Proces in Europe[J]. Landscape and Urban Planning,2004,67(1):9-26.
    3. Aspinall R. Modelling land use change with generalized linear models:a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana[J]. Journal of Environmental Management,2004,72(1-2):91-103.
    4. Batty M, Xie Y.Possible urban automata.Environment and Planning B,1997, 24:175-192.
    5. Batty M. Urban evolution on the desktop:Simulation with the use of extended cellular automata.Environment and Planning A,1998,30:1943-1967.
    6. Batty M, Xie Y, Sun Z.Modeling urban dynamics through GIS-based cellular automata.Computers, Environment and Urban Systems,1999,23:205-233.
    7. Bell K P, Irwin E G. Spatially explicit micro-level modeling of land use change at the rural-urban interface[J]. Agricultural Economics,2002,27(3):217-232.
    8. Bertalanffy, L.V.,1968.General System Theory:Foundations, Development, Application.
    9. Brian M.Steele.Combining multiple classiers:An application using spatical and remotely sensed information for land cover type mapping.Remote sensing of Environment,2000,74:545-556.
    10. Bryan C.Pijanowski, Daniel GBrown.Using neural networks and GIS to forecast Land use changes:a land Transformation Model.Computers, Envirnment and Uran System 26(2002)553-575.
    11. Candau J, Rasmussen S, Clarke K C. A coupled cellular automaton model for land use/land cover dynamics[C]. The 4th International Conference on Integrating GIS and Environmental Modeling:Problems, Prospects and Research Needs. Banff, Alberta, Canada,2000.
    12. Carol A.Ferguson, Richard L.Bowen, M.Akram Kahn.1991.A statewide LESA system for Hawaii. Journal of Soil and Water Conservation 46(4):263-267
    13. CHENG J, MASSER I. Urban Growth Pattern Modelling:A Case Study of Wuhan City, P R China[J]. Landscape and Urban Planning,2003,62(4):199-217.
    14. Clarke K C, Hoppen S, GaydosL.A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning & Planning and Design,1997,24:247-261.
    15. Clarke K C, Gay do s L J. Loo se-coupling a Cellular Auto maton Model and GIS:Long-term Urban Growth Prediction for San Francisco and Washington/Baltimore [J].International Journal of Geographical Information Science,1998,12(7):699-714.
    16. Dale V.H..The relationship between land use change and climate change[J], Ecological Application,1997,7(3):753-769.
    17. DAVIS C, SCHAUB T. A Transboundary Study of Urban Sprawl in the Pacific Coast Region of North America:The Benefits of Multiple Measurement Methods [J]. International Journal of Applied Earth Observation and Geoinformation,2005,7(4):268-283.
    18. De SOYZA A.G, WHITFORD W.G, HERRICK J.E, et al.Early warning indicators of desertification:examples of tests in the Chihuahuan desert[J].Journal of Arid Environments,1998,39(2):101-112.
    19. Dietzel C, Clarke K C. Spatial differences in multi-resolution urban automata modeling[J]. Transactions in GIS,2004,8(4):479-492.
    20. Dietzel C, Clarke K C. The effect of disaggregating land use categories in cellular automata during model calibration and forecasting [J]. Computers, Environment and Urban Systems,2006,30(1):78-101.
    21. Dietzel C, Clarke K C. Toward optimal calibration of the SLEUTH land use change model [J]. Transactions in GIS,2007,11(1):29-45.
    22. Donald E. Van Meter.1986.Agriculture and soil conservation in Poland and the Soviet Union. Journal of Soil and Water Conservation 41(6):379-380
    23. Duke M Joshua, Lynch Lori.2006.Farmland Retention Techniques:Property rights implications and Comparative Evaluation[J].Land Economics 82(2):189-213.
    24. FAO.1992.Sustainable Development and the Environment.FAO Policies and Actions
    25. FAO.1993.FESLM, An International Framework for Evaluating Sustainable Land Management. World Soil Resources Report 73. Rome, Italy
    26. Ferguson C A et al.1991.A Statewide LESA System for Hawaii, Journal of Soil and Water Conservation (4)
    27. FOLEY J A, DEFRIES R, ASNER G P, et al. Global Consequences of Land Use[J]. Science,2005,309(22):570-574.
    28. GLP. Science plan and implementation strategy. IGBP Report No.53 and IHDP Report No.19,2005.
    29. Hong Yang, Xiubin Li.2000.Cultivated Land and Food Supply in China[J]. Land Use Policy 17(2):73-88.
    30. IAASTD (2009) Executive Summary of the Synthesis Report and Summary for Decision Makers of the Global Report, http://www.iaastd.com/International Assessment of Agricultural Knowledge, Science and Technology for Development.
    31. IIASA. Modeling land-use and land-cover change in Europe and Northern Asia. 1999 Research Plan,1998.
    32. Jantz C A, Goetz S J, AJantz P, et al. Resource land loss and forest vulnerability in the Chesapeake Bay Watershed[C]. In:Warnell School of Forest Resources, University of Georgia, Athens, G A. Proceedings of the 4th Southern Forestry and Natural Resources GIS Conference. Athens,2004:16-17.
    33. Jeffrey E. Herrick.Soil quality:an indicator of sustainable land management?[J].Applied Soil Ecology,2000,15(1):75-83.
    34. John P.Reganold, Michael J.Singer.1979.Defining prime farmland by three land classification systems. Journal of Soil and Water Conservation 34(4):172-176
    35. KALNAY E, CAI M. Impact of Urbanization and Land-Use Change on Climate[J]. Nature,2003,423(6939):528-531.
    36. K. Culbertson.1993.Toward a Definition of Sustainable Development in the Vampa Valley of Colorado. Mountain Research and Development 13(4):298-312
    37. Kevin S. Hanna.1997.Regulation and land-use conservation:A case study of the British Columbia agricultural land reserve. Journal of Soil and Water Conservation 52(3):166-170
    38. Kim, T.J.1986.Modelling the Density Variations of Urban Land Uses With Transportation Network Congestion. Journal of Urban Economics 19:264-276.
    39. Kok K, Farrow A, Veldkamp A, et al. A method and application of multi-scale validation in spatial land use models. Agr Ecosys Environ,2001,85:223-238.
    40. Kok K, Winograd M. Modelling land-use change for Central America, with special reference to the impact of hurricane Mitch[J]. Ecological Modeling,2002, 149(1-2):53-69.
    41.Loomis, R.S& Williams, W.A.1963.Maximum crop productivity:Aestimate J.Crop Science 3(5):11-18.
    42. LiXia, Yeh A G O. Neural-network-based cellular automata for simulating multiple land use changes using GIS.International Journal of Geographical Information Science,2002,16(4):323-343.
    43. LiXia, YehA G O. Data mining of cellular automatas transition rules. International Journal of Geographical Information Science,2004,18(8):723-744.
    44. LiXia, YehA G O.Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science,2000,14(2):131-152.
    45. LiXia, YehA G O.Constrained cellular automata for modelling sustainable urban forms.Acta Geographical Sinica,1999,54(4):289-298.
    46. Linda R.Klein, John P.Reganold.1997. Agricultural changes and farmland protection in western Washington.Journal of Soil and Water Conservation 52(1):6-12
    47. Lloyd E.Wright, Warren Zitzmann, Keith Young, et al.1983 LESA-agricultural land Evaluation and Site Assessment. Journal of Soil and Water Conservation 38(2):82-86
    48. Lloyd E.Wright.1984.Agricultural land evaluation and site assessment-A new agricultural land protection tool in the U. S. A.Soil Survey and Land Evaluation 4(2):25-38.
    49. Manson S M. Agent-based modeling and genetic programming for modeling land change in the Southern Yucatan Peninsular Region of Mexico. Agr Ecosys Environ,2005,111:47-62.
    50. Marlow Vesterby and Ralph E.Heimlich.1991. Land Use and Demographic Change:Results from Fast-Growth Counties[J].Land Economics 67(3):279-291.
    51. McConnell W J. Agent-based models of land-use and land-cover change. LUCC Report No.6,2001.
    52. Medler K E, Okey B W, Lucas M F, etal.Landscape change with agricultural intensification in a rural waetrshed south western Ohio, U.S.A.Landscpe Ecology, 1995,10:161-176.
    53. MENARD A, MARCEAU D J.Simulating the impact of forest management scenarios in an agricultural landscape of southern Quebec, Canada, usinga geographic cellular automata[J].Landscape and Urban Planning,2007, 79:253-265.
    54. Michael J.Singer.1978.The USDA land capability classification and storie index rating:A comparison.Journal of Soil and Water Conservation 33(4):178-182.
    55. Moran E F. News on the land project. Global Change Newslett,2003,54: 19-21.
    56. Moran E, Ojima D, Buchmann N, et al.Global land project:science plan and implementation strategy.2005.IGBP Report NO.53/IHDP Report NO.19.
    57. Morita H, S Hoshino, M. Kagatsume, et al. An application of the land use change model for the Japan case study area[R]. In:Interim Report IR-97-065. Laxenburg, Austria:International Institute for Applied Systems Analysis(IIASA),1997.
    58. Oguz H, Klein A, Srinivasan R. Modeling urban growth and landuse and landcover change in the Houston metropolitan area from 2002 to 2030[C]. In: ASPRS. Proceedings of the ASPRS 2004 Fall Conference. Kansas City,2004.
    59. P.M.Raup, What is Prime Land?, J.of Soil and Water Conservation,1976, (5).
    60. Pearce D.W, Atkinson G.1993. Capital Theory And The Measure Of Sustainable Development:An Indicator Of Weak Sustainability.Ecological Economics (8):103-108.
    61.Rafiee R, Mahiny A S, Khorasani N, et al. Simulating urban growth in Mashad City, Iran through the SLEUTH model(UGM)[J]. Cities,2009,26(1):19-26.
    62. Richard P.Greene and John M.Harlin.1995.Threat to High Market Value Agricultural Lands from Urban Encroachment:A National and Regional Perspective[J].The Social Science Journal 32(2).
    63. Robert J.Southerland, Thomas J.Nieman.1985.Protecting agricultural land in the Bluegrass.Journal of Soil and Water Conservation 40(6):485-487
    64. RaymondI.Dideriksen R.NeilSampson.1976.Importantfarmlands:Anationalview.Journalofsil and Water Conservation 31(5):195-197
    65. Raymond E. E. Jongschaap.Run-time calibration of simulation models by integrating remote sensing estimates of leaf area index and canopy nitrogen[J].European Journal of Agronomy,2006,24(4):316-324.
    66. R Gil Pontius Jr, Joseph D Cornell, Charles A S Hall.Modeling the spatial pattern of land-use change with GEOMOD2:Application and validation for Costa Rica. Agriculture, Ecosystems and Environment,2001,85:191-203.
    67. Robert M.Ward.1987.A farmland preservation policy in the United States. International Journal of Environmental Studies 30(2):125-135
    68. Rosen R.1983.Some comments on systems and systems Theory, International Journal of General Systems 13(1)1-3.
    69. Schneider L C, R. Pontius J G. Modeling land-use change in the Ipswich watershed, Massachusetts, USA[J]. Agriculture, Ecosystems & Environment, 2001,85(1-3):83-94.
    70. Silva E A, Clarke K C. Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal [J]. Computers, Environment and Urban Systems, 2002,26(6):525-552.
    71. Smit.B.1981.Prime Farmland, Land Evaluation and Land Use Policy, Journal of Soil and Water Conservation (4).
    72. 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[J]. Ecological Complexity,2005,2(2):185-203.
    73. TIAN G, LIU J, XIE Y, et al. Analysis of Spatio-Temporal Dynamic Pattern and Driving Forces of Urban Land in China in 1990s Using TM Images and G1S[J], Cities,2005,22(6):400-410.
    74. Turner B.L..The sustainability principle in global agendas:Implication far understanding landuse/land cover change (J), The Geographical Journal,1997, 163(2):133-140.
    75. Veldkamp A, Fresco L O. Exploring land use scenarios, an alternative approach based on actual land use. Agr Sys,1997,55:1-17.
    76. Verburg P H, Schulp C J E, Witte N, et al. Downscaling of land use change scenarios to assess the dynamics of European landscapes[J]. Agriculture, Ecosystems & Environment,2006,14(1):39-56.
    77. Vijendra Kumar.An early warning system for agricultural drought in an arid region using limited data[J]. Journal of Arid Environments,1998,40(2):199-209.
    78. V.W.Benson, B.L.Harris, C.W.Richardson, et al.1992.Using export systems and process models to enhance U.S.agriculture.Journal of Soil and Water Conservation 47(3):234-235.
    79. Ward D P, Murray A T. An optimized cellular automata approach for sustainable urban development in rapidly urbanizing regions. International Journal of Geographical Information Science,1999,7(5):235-250.
    80. White R, Engelen G. Cellular automata and fractal urban form:a cellular modelling approach to the evolution of urban land-use patterns.Environment and Planning A,1993,25:1175-1199.
    81. World Bank.1995.Monitorine Environmental Progress:A Report On Work In Progress. Washington D. C.
    82. 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.
    83. Wu F L, Webster C J. Simulation of land development through the integration of cellular automata and multi-criteria evaluation [J]. Environment and Planning B, 1998,25(1):103-126.
    84. Xavier Baulies, Gerard Szejwach.LUCC Data Requirements Workshop. Survey of needs, gaps and priorities on data for land-use/land-cover change researeh (C), Barcelona:IGBP,1997:43-48.
    85. XIE Y, ME1 Y, TIAN G, et al. Socio-Economic Driving Forces of Arable Land Conversion:A Case Study of Wuxian City, China[J]. Global Environmental Change,2005,15(3):238-252.
    86. Yang X, Lo C P. Modeling urban growth and landscape change in the Atlanta metropolitan area[J]. International Journal of Geographical Information Science, 2003,17(5):463-488.
    87. Yue T, Fan Z, Liu J. Changes of major terrestrial ecosystem in china since 1960. Glob Planet Change,2005,48:287-302.
    88.摆万奇,赵士洞.土地利用变化驱动力系统分析[J].资源科学,2001,23(3):39-41.
    89.毕如田,王镔,段永红,等.耕地资源管理信息系统的建立及应用—以永济市为例[J].土壤学报,2004,41(6):962-968.
    90.陈百明.试论中国土地利用和土地覆被变化及其人类驱动力研究[J].自然资源学报,1997,14:31-36.
    91.陈百明.耕地与基本农田保护态势与对策[J].中国农业资源与区划,2004,25(5):1-4.
    92.陈海燕,彭补拙.耕地保护的一般原则与模式研究[J].南京大学学报(自然科学),2001,37(3):304-310
    93.陈美球.国外耕地保护的常用手段,中国土地,2008第6期,54-57
    94.陈美球,周丙娟等.当前农户耕地保护积极性的现状分析与思考[J].中国人口·资源与环境,2007,17(1):114-118.
    95.陈美球,魏晓华,刘桃菊.欧美耕地保护的做法与启示,2009-06-22,中国国土资源报.
    96.程锋、王茹、郧文聚.浅谈永久基本农田的划定[J].资源与产业,2009,11(2):118-120.
    97.程锋.基于GIS与决策模型整合的基本农田保护规划系统[D].中国农业大学博士论文,2003
    98.程锋,石英,朱德举.耕地入选基本农田决策模型研究[J].地理与地理信息科学,2003,19(3):50-53
    99.程雄,吴争研,刘艳芳.GIS技术在基本农田保护工作中的应用[J].国土资源信息化,2002,(4):37-39.
    100.陈逢珍,林文鹏.基本农田信息系统的设计与实例研究[J].地球信息科学,2002,6(2):94-99.
    101.邓祥征.土地用途转换分析[M].北京:中国大地出版社,2008.
    102.丁菡.中国沿海经济发达地区土地利用变化及其驱动机制与预测模型研究——以浙江省沿海地区为例[D].杭州:浙江大学,2006.
    103.翟文侠,黄贤金.我国耕地保护政策运行效果分析[J].中国土地科学,2003,17(2):8-13.
    104.国家粮食安全中长期规划纲要2008-2020年
    105.关小克,张凤荣,郭力娜,赵婷婷.北京市耕地多目标适宜性评价及空间布局研究[J].资源科学,2010,32(3):580-587.
    106.龚子同,陈鸿昭,张甘霖,赵玉国,保护耕地:问题、症结和途径——谈我国1.2亿公顷耕地的警戒线[J].生态环境2007.16(5):1570-1573.
    107.广东省基本农田保护检查工作总结报告,2005年
    108.广东省国土年鉴2000-2009.
    109.广东省土壤肥料总站.珠江三角洲耕地质量评价与利用[M].北京:中国农业出版社,2007..[5]144
    110.广东省统计年鉴2000-2009.
    111.郗凤明,胡远满,贺红士等.基于SLEUTH模型的沈阳-抚顺都市区城市规划[J].中国科学院研究生院学报,2009,26(6):765—773.
    112.何蔓,张军岩(LUCC)研究及其进展[J].国土资源,2005,(9):22—25.
    113.何春阳,陈晋,史培军,等.大都市区城市扩展模型-以北京城市扩展模拟为例[J].地理学报,2003,58(2):294-304.
    114.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[J].中国科学(D辑),2005,35(5):464-473.
    115.胡茂桂,傅晓阳,张树清,宋开山,王宗明.基于元胞自动机的莫莫格湿地土地覆被预测模拟[J].资源科学,2007,29(2):142-148.
    116.黄庆旭,史培军,何春阳,等.中国北方未来干旱化情景下的土地利用变化模拟[J].地理学报,2006,61(21):1299-1310.
    117.纪昌品,汤江龙,陈荣清.耕地保护政策的内涵及其公平与效率分析[J].国土资源科技管理,2005,3:28-32
    118.蒋志欣,李满春,毛亮,刘永学.标准农田规划空间决策支持模型的研究与实现[J].地球信息科学,2007,9(3):79-84.
    119.柯武刚,史漫飞著;韩朝华译,制度经济学:社会秩序与公共政策[M].北京:商务印书馆,2000,P239-240.
    120.孔祥斌.基本农田保护应对新问题,www.lcrc.org.cn/Upload/
    121.兰德尔.资源经济学[M].北京:商务印书馆,1989.
    122.李秀斌.中国近20年来耕地面积的变化极其政策启示[J].自然资源学报,1999,14(4):329-333.
    123.李秀彬.全球环境变化研究的核心领域-土地利用/土地覆被变化国际研究动向[J].地理学报,1996,51(6):553-557.
    124.李兆富,杨桂山.苏州市近50年耕地资源变化过程与经济发展关系研究[J].资源科学,2005,27(4),50-54.
    125.李明艳,赵珂.耕地保护制度供求机制探讨[J].农村经济,2005,9:95-97
    126.李赓,吴次芳,曹顺爱.划定基本农田指标体系的研究[J].农机化研究,2006,8:46-48
    127.李桂林,陈杰,孙志英.苏州市非农用地扩展的驱动因素时空变化研究[J].生态与农村环境学报,2006,22(4):1—7.
    128.梁书民、金陶陶.中国大城市建成区扩张与城郊耕地保护研究-以北京、上海和广州为例,环境保护,2005,11:59-63
    129.林孝松.基本农田地理信息系统设计与开发[J].重庆师范大学学报(自然科学版),2005,22(2):68-71.
    130.刘纪远,邓祥征LUCC时空过程研究的方法进展[J].科学通报,2009,54(21):3251-3258.
    131.刘小平,黎夏,彭晓鹃.“生态位”元胞自动机在土地可持续规划模型中的应用[J].生态学报,2007,27(6):2391-2402.
    132.刘彦随,王介勇,郭丽英.中国粮食生产与耕地变化的时空动态[J].中国农业科学,2009,42(14):4269-4274.
    133.刘勇,吴次芳,岳文泽,等.基于SLEUTH模型的杭州市城市扩展研究[J].自然资源学报,2008,23(5):797-807.
    134.雷广海,方斌,刘友兆.我国基本农田保护的合理规模估算及其政策制度修正 探讨[J].农村经济,2008,2:18-21.
    135.马建华,管华.系统科学及其在地理学中的应用[M].北京:科学出版社,2003.
    136.马中.环境与资源经济学概论[M].北京:高等教育出版社,1999,P29.
    137.聂庆华,包浩生.中国基本农田保护的回顾与展望[J].中国人口·资源与环境.1999,9(2):31-35
    138.农业科学自然资源和农业区划研究所,农业部全国土壤肥料总站.中国耕地资源及其开发利用[M].北京:测绘出版社,1992:8-24.
    139.曲福田.资源经济学[M],北京:中国农业出版社,2001,P69.
    140.彭补拙,周生路.土地利用规划学[M].南京:东南大学出版社,2003.
    141.邱炳文,陈崇成.基于多目标决策和CA模型的土地利用变化预测模型及其应用[J].地理学报,2008,63(2):165-173.
    142.钱鑫,樊宏,高燕,等.基于GIS技术的基本农田保护究——以成都市龙泉驿区为例[J].国土资源科技管理,2006,(6):80-83.
    143.萨缪尔森,诺德豪斯.经济学[M].北京:华夏出版社,1999.
    144.生物能源打破全球粮食供求的均衡,张建东,2008-6-12,新华网
    145.石英,朱德举,程锋,等.属性层次模型在乡级基本农田保护区布局优化的应用[J].农业工程学报,2006,22(3):27-30.
    146.石英,程锋.基于遗传算法的乡级土地利用规划空间布局方案研究[J].江西农业大学学报,2008,30:380-384
    147.涂小松,濮励杰,吴骏,等.基于SLEUTH模型的无锡市区土地利用变化情景模拟[J].长江流域资源与环境,2008,17(6):860-865.
    148.涂小松.环太湖地区土地利用变化与城乡用地优化研究[D].南京大学博士学位论文,2009.
    149.王思远,刘纪远,张增祥等.中国土地利用时空特征分析[J].地理学报,2001,56(6):631-639.
    150.王汉花,刘艳芳.基于MOP-CA整合模型的土地利用优化研究[J].武汉大学学报(信息科学版),2009,34(2):174-177.
    151.王万茂,李边疆.基本农田分级保护政策体系构想[J].南京农业大学学报(社会科学版),2006,6(1):177-182.
    152.汪涌,蔡运龙,蒙吉军.中国耕地流转驱动力研究综述[J].资源科学,2007,29(3):1-5.
    153.吴先华、齐相贞.江苏省耕地转化为建设用地的经济学分析[J].地理与地理信息科学,2004,20(6):51—56.
    154.吴晓青,胡远满,贺红士,等.SLEUTH城市扩展模型的应用与准确性评估[J].武汉大学学报·信息科学版,2008,33(3):293-296.
    155.郗凤明,贺红士,胡远满,等.营口市城市及村镇聚落增长与土地利用变化的模拟预测[J].应用生态学报,2008,19(7):1529-1536.
    156.许月卿.区域耕地变化及可持续利用评价[J].地理科学进展,2002,21(1):35-42.
    157.许福涛.基本农田保护区耕地质量监测体系的建立与管理[J].土壤,2005,37(6):566—568.
    158.许国志,顾基发,车宏安.2000.系统科学.上海:上海科技教育出版社.
    159.郧文聚,周尚意,朱阿兴.连片集中保护优质耕地[N].中国国土资源报,2008年3月21日第5版.
    160.杨桂山.土地利用/覆被变化与区域经济发展—长江三角洲近50年耕地数量变 化研究的启示[J].地理学报,2004,59(增刊):41-46.
    161.杨青生,黎夏.多智能体与元胞自动机结合及城市用地扩张模拟[J].地理科学,2007,27(4):542-548.
    162.杨树佳,郑新奇,王爱萍,杜娟,姚慧.耕地保护与基本农田布局方法研究——以济南市为例[J].水土保持研究,2007,14(2):4-7
    163.杨树佳,王爱萍,郑新奇.基本农田指标分解的熵权系数法研究[J].资源开发与市场.2006,22(4):305-306
    164.赵其国院士访谈:保护耕地要有战略性.科技日报,2004-7-12
    165.赵其国,周炳中,杨浩等.中国耕地资源安全问题及相关对策思考[J].土壤,2002,34(6):293-302.
    166.张永民,赵士洞,Verburg P H. CLUE-S模型及其在奈曼旗土地利用时空动态变化模拟中的应用[J].自然资源学报,2003,18:310-318.
    167.于兴修,杨桂山.中国土地利用/覆被变化研究的现状与问题[J].地理科学进展,2002,21(1):52-57.
    168.张效军,耕地保护区域补偿机制研究,[D].博士论文,2008
    169.张君宇,等.建立和完善耕地保护社会监督机制的思路探讨[J].中国国土资源经济,2007.(2):28-29.
    170.张玉宝.耕地占补平衡得失观[J].中国土地,2004,(12):28—30.
    171.张侠,葛向东,濮励杰,黄贤金,彭补拙.土地利用的经济生态位分析和耕地保护机制研究[J].自然资源学报,2002,17(6):677—683.
    172.张鸿辉,曾永年,金晓斌,尹长林,邹滨.多智能体城市土地扩张模型及其应用[J].地理学报,2008,23(6):618-624.
    173.张鸿辉,尹长林,曾永年等.基于SLEUTH模型的城市增长模拟研究—以长沙市为例[J].遥感技术与应用,2008,63(8):869-881.
    174.张军岩,贾绍风,高婷.石家庄城市化进程中的耕地变化[J].地理学报,2003(7):620-628.
    175.臧俊梅,王万茂,李边疆.我国基本农田保护政策演变的制度经济学分析[J].经济体制改革,2006,6:84-88
    176.张良悦、师博、刘东.中国城市土地利用效率与耕地保护--基于地级以上城市的DEA分析,2007
    177.张兆瑞,曲晨晓,苏中伟CPPIS县级基本农田保护规划信息系统的开发研制[J].河南农业大学学报,2000,34(3):292-294
    178.张炳宁,张月平,张秀美,等.基本农田信息系统的建立及其应用[J].土壤学报,1999,36(4):510-520.
    179.曾尊固,陆诚,庄仁兴.英国农业地理.北京:商务印书馆,1990.
    180.钟太洋,黄贤金,马其芳.区域人均基本农田需求面积测算模型及应用—以江苏省为例[J].自然资源学报,2006,21(5):717-725.
    181.周成虎,孙战利,谢一春.地理元胞自动机研究[M].北京:科学出版社,1999.
    182.周尚意,朱阿兴,邱维理,刘峰,戴俊骋.基于GIS的农用地连片性分析及其在基本农田保护规划中的应用[J].农业工程学报,2008,24(7):72-77.
    183.张建东,生物能源打破全球粮食供求的均衡,新华网,2008-6-12.
    184.赵晶,陈华根,许惠平.元胞自动机与神经网络相结合的土地演变模拟[J].同济大学学报(自然科学版),2007,35(8):1128-1132.
    185.朱利凯,蒙吉军.国际LUCC模型研究进展及趋势[J].地理科学进展,2009, 28(5):782-790.
    186.赵亚莉,吴群.基本农田保护研究综述[J].国土资源科技管理,2007(6):30-34.
    187.朱启才.权利、制度与经济增长[M].北京:经济科学出版社,2004.

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