A counterfactual scenario simulation approach for assessing the impact of farmland preservation policies on urban sprawl and food security in a major grain-producing area of China

Applied Geography

Volumn 37, Issue 1, 2013, Pages 127-138

  He, Jianhua ^a,b   Liu, Yaolin ^a,b   Yu, Yan ^c   Tang, Wenwu ^d   Xiang, Weining ^d,e   Liu, Dianfeng ^a,b  

^a WUHAN UNIVERSITY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c WUHAN UNIVERSITY OF TECHNOLOGY   (China)

^d UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE   (United States)

^e EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

China; Counterfactual analysis; Farmland preservation; Food security; Scenario simulation; Urban sprawl

Indexed keywords

AGRICULTURAL POLICY; ARABLE LAND; DECISION MAKING; FOOD SECURITY; MODELING; POLICY IMPLEMENTATION; SPATIAL ANALYSIS; URBAN AREA;

CHINA;

EID: 84870891331     PISSN: 01436228     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apgeog.2012.11.005     Document Type: Article

References (61)

1. Atherton A. A future for small business? Prospective scenarios for the development of the economy based on current policy thinking and counterfactual reasoning. Futures 2005, 37:777-794.
2. Batty M. Cities and complexity: Understanding cities with cellular automata, agent-based models, and fractals 2005, The MIT Press, Cambridge.
3. Batty M., Xie Y. From cells to cities. Environment and Planning B: Planning and Design 1994, 21(Suppl.):S31-S48.
4. Borges P.J., Fragoso R., Garcia-Gonzalo J., Borges J.G., Marques S., Lucas M.R. Assessing impacts of common agricultural policy changes on regional land use patterns with a decision support system: an application in Southern Portugal. Forest Policy and Economics 2010, 12:111-120.
5. Bourguignon F., William H.B., Melo J.de Adjustment and income distribution: a micro-macro model for counterfactual analysis. Journal of Development Economics 1992, 38:17-39.
6. Clarke K.C., Hoppen S., Gaydos L. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B 1997, 24:247-261.
7. Ding C.R. Land policy reform in China: assessment and prospects. Land Use Policy 2003, 20:109-120.
8. Ferraro P.J. Counterfactual thinking and impact evaluation in environmental policy. New Directions for Evaluation 2009, 122:75-84.
9. Foody G.M. Status of land cover classification accuracy assessment. Remote Sensing of Environment 2002, 80:185-201.
10. Geoghegan J., Villar S.C., Klepeis P., Mendoza P.M., Yelena O., Chowdhury R.R., et al. Modeling tropical deforestation in the southern Yucatan peninsula region: comparing survey and satellite data. Agriculture, Ecosystems and Environment 2001, 85:25-46.
11. Geurs K., van Wee B. Ex-post evaluation of thirty years of compact urban development in the Netherlands. Urban Studies 2006, 43:139-160.
12. Greenberg M., Isserman A., Krueckeberg D., Lowrie K., Mayer H., Simon S., et al. Socioeconomic impacts of US nuclear weapons facilities: a local-scale analysis of Savannah River, 1950-1993. Applied Geography 1998, 18:101-116.
13. Guan Q.F., Wang L.M., Clarke K. An artificial-neural-network-based, constrained CA model for simulating urban growth. Cartograhpy & Geographic Information Science 2005, 32:369-380.
14. Hagen A. Fuzzy set approach to assessing similarity of categorical maps. International Journal of Geographical Information Science 2003, 17:235-249.
15. Han J., Hayashi Y., Cao X., Imura H. Application of an integrated system dynamics and cellular automata model for urban growth assessment: a case study of Shanghai, China. Landscape and Urban Planning 2009, 91:133-141.
16. He C.Y., Okadac N., Zhang Q.F., Shi P.J., Zhang J.S. Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China. Applied Geography 2006, 26:323-345.
17. Heerink N., Qu F.T., Kuiper M., Shi X.P., Tan S.H. Policy reforms, rice production and sustainable land use in China: a macro-micro analysis. Agricultural System 2007, 94:784-800.
18. Koomen E., Rietveld P., Nijs T. Modelling land-use change for spatial planning support. The Annals of Regional Science 2008, 42:1-10.
19. Lagarias A. Urban sprawl simulation linking macro-scale processes to micro-dynamics through cellular automata, an application in Thessaloniki, Greece. Applied Geography 2012, 34:146-160.
20. Lamie R.D., Campbell W., Molnar W. The fiscal-geographic nexus: an overview of fiscal impact assessment in local policy development. Applied Geography 2012, 32:54-60.
21. Lankoski, J., & Ollkainen, M. Counterfactual approach for assessing agri-environmental policy: the case of the Finnish water protection policy. The 122nd EAAS Seminar " Evidence-based Agricultural and Rural Policy Making: Methodological and Empirical Challenges of Policy Evaluation" 2011, Ancona, 1-16.
22. Le Q.B., Park S.J., Vlek P.L.G. Land use dynamic simulator (LUDAS): a multi-agent system model for simulating spatio-temporal dynamics of couples human-landscape system 2. Scenario-based application for impact assessment of land-use policies. Ecological Informatics 2010, 5:201-221.
23. Li X., Liu X.P. Embedding sustainable development strategies in agent-based models for use as a planning tool. International Journal of Geographical Information Science 2008, 22:21-45.
24. Li X., Yang Q.S., Liu X.P. Discovering and evaluating urban signatures for simulating compact development using cellular automata. Landscape and Urban Planning 2008, 86:177-186.
25. Li X., Yeh A.G. Constrained cellular automata for modeling sustainable urban form. Acta Geographic Sinica 1999, 54:289-298. (in Chinese).
26. Li X., Yeh A.G. Modelling sustainable urban development by the integration of constrained cellular automata and GIS. International Journal of Geographical Information Science 2000, 14:131-152.
27. Li X., Yeh A.G. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science 2002, 16:323-343.
28. Lichtenberga E., Ding C.R. Assessing farmland protection policy in China. Land Use Policy 2008, 25:59-68.
29. Liu X., Li X., Yeh A.G. Discovery of transition rules for geographical cellular automata by using ant colony optimization. Science in China (Series D) 2007, 50:1578-1588.
30. Liu Y.L., Molenaar M., Kraak M.J. Spatial object aggregation based on data structure, local triangulation and hierarchical analyzing method. Geo-spatial Information Science 2002, 5:44-54.
31. Long H.L., Tang G.P., Li X.B., Heilig G.K. Socio-economic driving forces of land-use in Kunshan, the Yangtze River Delta economic area of China. Journal of Environmental Management 2007, 83:351-364.
32. Lubowski R.N., Plantinga A.J., Stavins R.N. What drives land-use change in the United States? A national analysis of landowner decisions. Land Economics 2008, 84:529-550.
33. McMillen D.P. An empirical model of urban fringe land use. Land Economics 1989, 65:138-145.
34. Mitsova D., Shuster W., Wang X.H. A cellular automata model of land cover change to integrate urban growth with open space conservation. Landscape and Urban Planning 2011, 99:141-153.
35. Mondal P., Southworth J. Evaluation of conservation interventions using a cellular automata-Markov model. Forest Ecology and Management 2010, 260:1716-1725.
36. Pontius R. Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogrammetric Engineering and Remote Sensing 2002, 68(10):1041-1049.
37. Serneels S., Lambine E.F. Proximate causes of land use change in Narok district Kenya: a spatial statistical model. Agriculture, Ecosystems and Environment 2001, 85:65-82.
38. Siciliano G. Urbanization strategies, rural development and land use changes in China: a multiple-level integrated assessment. Land Use Policy 2012, 29:165-178.
39. Takeyama M., Couclelis H. Map dynamics: integrating cellular automata and GIS through geo-algebra. International Journal of Geographical Information Science 1997, 11:73-92.
40. Tan M.H., Li X.B., Xie H., Lu C.H. Urban land expansion and arable land loss in China-a case study of Beijing-Tianjin-Hebei region. Land Use Policy 2005, 22:187-196.
41. Tavares A.O., Pato R.L., Magalhães M.C. Spatial and temporal land use change and occupation over the last half century in a peri-urban area. Applied Geography 2012, 34:432-444.
42. Tian G., Ouyang Y., Quan Q., Wu J.G. Simulating spatiotemporal dynamics of urbanization with multi-agent systems - a case study of the Phoenix metropolitan region, USA. Ecological Modeling 2011, 222:1129-1138.
43. Trescott P.B. Federal reserve policy in the great contraction: a counterfactual assessment. Explorations in Economic History 1982, 19:211-220.
44. Turner R., Paavola J., Cooper P., Farber S., Jessamy V., Georgiou S. Valuing nature: lesson learned and future research directions. Ecological Economics 2003, 46:493-510.
45. Verburg P.H. Simulating feedbacks in land use and land cover change models. Landscape Ecology 2006, 21:1171-1183.
46. Verburg P.H., Chen Y.Q., Veldkamp T. Spatial explorations of land use change and grain production in China. Agriculture, Ecosystems and Environment 2000, 82:333-354.
47. Verburg P.H., Soepboer W., Veldkamp A., Limpiada R., Espaldon V. Modeling the spatial dynamics of regional land use: the CLUE-s model. Journal of Environmental Management 2002, 30:391-405.
48. Vliet J.V., Bregt A.K., Hagen-Zanker A. Revisiting kappa to account for change in the accuracy assessment of land-use change models. Ecological Modeling 2011, 222:1367-1375.
49. Vliet J.V., White R., Dragicevic S. Modeling urban growth using a variable grid cellular automaton. Computers. Environment and Urban Systems 2009, 33:35-43.
50. 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.
51. White R., Engelen G. High resolution integrated modeling of the spatial dynamics of urban and regional systems. Computers, Environment and Urban Systems 2000, 24:383-400.
52. White R., Engelen G., Uijee I. The use of constrained cellular automata for high resolution modeling of urban land use dynamics. Environment and Planning B 1997, 24:323-343.
53. Wu F. An experiment on the generic polycentricity of urban growth in a cellular automatic city. Environment and Planning B 1998, 25:731-752.
54. Wu F. Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Science 2002, 16:795-818.
55. Wu F., Webster C.J. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B: Planning and Design 1998, 25:103-126.
56. Wu J.G., David J.L. A spatially explicitly hierarchical approach to modeling complex ecological systems: theory and applications. Ecological Modeling 2002, 153:7-26.
57. Wu Y., Zhang X., Shen L. The impact of urbanization policy on land use change: a scenario analysis. Cities 2011, 28:147-159.
58. Xiang W.N., Clarke K.C. The use of scenarios in land-use planning. Environment and Planning B 2003, 30:885-909.
59. Xie Y.C., Yu M., Tian G.J., Xing X.R. Socio-economic driving forces of arable land conversion: a case study of Wuxian City, China. Global Environmental Change 2005, 15:238-252.
60. Yang H., Li X.B. Cultivated land and food supply in China. Land Use Policy 2000, 17:73-88.
61. Yang Q.S., Li X., Shi X. Cellular automata for simulating land use changes based on support vector machines. Computers and Geosciences 2008, 34:592-602.