Modeling grassland conversion: Challenges of using satellite imagery data

American Journal of Agricultural Economics

Volumn 95, Issue 2, 2013, Pages 404-411

  Rashford, Benjamin S ^a   Albeke, Shannon E ^a   Lewis, David J ^b  

^a UNIVERSITY OF WYOMING   (United States)

^b UNIVERSITY OF PUGET SOUND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL PRODUCTION; BIODIVERSITY; GRASSLAND; LAND USE CHANGE; SATELLITE DATA; SATELLITE IMAGERY;

GREAT PLAINS;

EID: 84872694090     PISSN: 00029092     EISSN: 14678276     Source Type: Journal    
DOI: 10.1093/ajae/aas110     Document Type: Conference Paper

References (16)

1. Beron, K.J., and W.P.M. Vijverberg. 2004. Probit in a Spatial Context: A Monte Carlo Analysis. In L. Anselin and R. Florax, eds. Advances in Spatial Econometrics. Berlin: Springer Verlag, pp. 169-195.
2. Cameron, A.C., and P.K. Trivedi. 2005. Microeconometrics: Methods and Applications. New York: Cambridge.
3. Crookston, N., G. Rehfeldt. 2010. Current Climate Data. U.S. Forest Service, Rocky Mountain Research Station, Moscow, Idaho. Available at: http://forest.moscowfsl.wsu.edu.Accessed on 15February 2012.
4. Efron, B., and R.J. Tibshirani. 1993. An Introduction to the Bootstrap, Monographs on Statistics and Applied Probability 57. New York: Chapman & Hall.
5. Hoekstra, J.M., T.M. Boucher, T.H. Ricketts, and C. Roberts. 2005. Confronting a Biome Crisis: Global Disparities of Habitat Loss and Protection. Ecology Letters 8(1): 23-29.
6. King, G., and L. Zeng. 2001. Logistic Regression in Rare Events Data. Political Analysis 9(2):137-163.
7. Lewis, D.J., and A.J. Plantinga. 2007. Policies for Habitat Fragmentation: Combining Econometrics With GIS-Based Landscape Simulations. Land Economics 83(2): 109-127.
8. Lubowski, R.N. 2002. Determinants of Land-Use Transitions in the United States: Econometric Analysis of Changes Among Major Land-Use Categories. Ph.D. dissertation, Harvard University.
9. Munroe, D.K., J. Southworth, and C.M. Tucker. 2002. The Dynamics of Land-Cover Change in Western Honduras: Exploring Spatial and Temporal Complexity. Agricultural Economics 27(3):355-369.
10. R Development Core Team. 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Available at:http://www.R-project.org/.Accessed on: date.
11. Rashford, B.S., C.T. Bastian, and J.G. Cole. 2011. Agricultural Land-Use Change in Prairie Canada: Implications for Wetland and Waterfowl Habitat. Canadian Journal of Agricultural Economics 59(2):185-205.
12. Rashford, B.S., J.A. Walker, and C.T. Bastian. 2010. Economics of Grassland Conversion to Cropland in the Prairie Pothole Region. Conservation Biology 25(2):276-284.
13. Ross, S.M. 2002. Simulation. San Diego: Academic Press.
14. Schnier, K.E., and R.G. Felthoven. 2011. Accounting for Spatial Heterogeneity and Autocorrelation in Spatial Discrete Choice Models: Implications for Behavioral Response. Land Economics 87(3): 382-402.
15. Soil Survey Staff, NRCS. 2011. Soil Survey Geographic (SSURGO) Database for Montana, Nebraska, North Dakota, South Dakota and Wyoming. U.S. Department of Agriculture. Available online at: http://soildatamart.nrcs.usda.gov. Accessed on: 1 June 2011.
16. Wu, J., and S. Cho. 2006. The Effect of Local Land Use Regulations on Urban Development in the Western United States. Regional Science and Urban Economics 37(1):69-86.