Brown DG, Robinson DT (2006) Effects of heterogeneity in residential preferences on an agentbased model of urban sprawl. Ecol Soc 11(1):46
Brown DG, Goovaerts P, Burnicki A, Li MY (2002) Stochastic simulation of land-cover change
using geostatistics and generalized additive models. Photogramm Eng Remote Sens
68(10):1051–1061
Camill P (2010) Global change. Nat Educ Knowl 3(10):49
Clarke KC, Gaydos LJ (1998) Loose-coupling a cellular automaton model and GIS: long-term
urban growth prediction for San Francisco and Washington/Baltimore. Int J Geogr Inf Sci
12(7):699–714
Clarke KC, Hoppen S, Gaydos L (1997) A self-modifying cellular automaton model of historical
urbanization in the San Francisco Bay area. Environ Plan B Plan Des 24(2):247–261
Couclelis H (2001) Modeling frameworks, paradigms, and approaches. In: Clarke KC, Parks BO,
Crane MP (eds) Geographic information systems and environmental modeling. Prentice Hall,
Upper Saddle River, pp 36–50
Evans TP, Kelley H (2004) Multi-scale analysis of a household level agent-based model of
landcover change. J Environ Manag 72(1–2):57–72
FAO (2010) Global forest resources assessment. Food and Agriculture Organization of the United
Nations, Rome
Gotway CA, Young LJ (2002) Combining incompatible spatial data. J Am Stat Assoc
97(458):632–648
Haberl H, Erb KH, Krausmann F, Gaube V, Bondeau A, Plutzar C, Gingrich S, Lucht W, FischerKowalski M (2007) Quantifying and mapping the human appropriation of net primary production in earth’s terrestrial ecosystems. Proc Natl Acad Sci U S A 104(31):12942–12945
Haith DA, Shoemaker LL (1987) Generalized watershed loading functions for stream-flow
nutrients. Water Resour Bull 23(3):471–478
Hoshino S (2001) Multilevel modeling on farmland distribution in Japan. Land Use Policy
18(1):75–90
Howard DM, Howard PJA, Howard DC (1995) A Markov model projection of soil organic-carbon
stores following land-use changes. J Environ Manag 45(3):287–302
Hu ZY, Lo CP (2007) Modeling urban growth in Atlanta using logistic regression. Comput
Environ Urban Syst 31(6):667–688
Irwin EG, Bockstael NE (2002) Interacting agents, spatial externalities and the evolution of
residential land use patterns. J Econ Geogr 2(1):31–54
Jantz CA, Goetz SJ, Shelley MK (2004) Using the SLEUTH urban growth model to simulate the
impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan
area. Environ Plan B Plan Des 31(2):251–271
Jensen JR (1983) Biophysical remote-sensing. Ann Assoc Am Geogr 73(1):111–132
Kerr S, Liu SG, Pfaff ASP, Hughes RF (2003) Carbon dynamics and land-use choices: building a
regional-scale multidisciplinary model. J Environ Manag 69(1):25–37
Lesschen JP, Verburg PH, Staal SJ (2005) Statistical methods for analysing the spatial dimension
of changes in land use and farming systems. LUCC report series no. 7. International Livestock
Research Institute/LUCC Focus 3 Office, Nairobi/Wageningen
Li X, Yeh AG (2002) Neural-network-based cellular automata for simulating multiple land use
changes using GIS. Int J Geogr Inf Sci 16(4):323–343
Ligmann-Zielinska A (2009) The impact of risk-taking attitudes on a land use pattern: an agentbased model of residential development. J Land Use Sci 4(4):215–232
Lin YP, Hong NM, Wu PJ, Lin CJ (2007) Modeling and assessing land-use and hydrological
processes to future land-use and climate change scenarios in watershed land-use planning.
Environ Geol 53(3):623–634
Liu WG, Seto KC (2008) Using the ART-MMAP neural network to model and predict urban
growth: a spatiotemporal data mining approach. Environ Plan B Plan Des 35(2):296–317
1 Land Change Modeling: Status and Challenges
15
Brown DG, Goovaerts P, Burnicki A, Li MY (2002) Stochastic simulation of land-cover change
using geostatistics and generalized additive models. Photogramm Eng Remote Sens
68(10):1051–1061
Camill P (2010) Global change. Nat Educ Knowl 3(10):49
Clarke KC, Gaydos LJ (1998) Loose-coupling a cellular automaton model and GIS: long-term
urban growth prediction for San Francisco and Washington/Baltimore. Int J Geogr Inf Sci
12(7):699–714
Clarke KC, Hoppen S, Gaydos L (1997) A self-modifying cellular automaton model of historical
urbanization in the San Francisco Bay area. Environ Plan B Plan Des 24(2):247–261
Couclelis H (2001) Modeling frameworks, paradigms, and approaches. In: Clarke KC, Parks BO,
Crane MP (eds) Geographic information systems and environmental modeling. Prentice Hall,
Upper Saddle River, pp 36–50
Evans TP, Kelley H (2004) Multi-scale analysis of a household level agent-based model of
landcover change. J Environ Manag 72(1–2):57–72
FAO (2010) Global forest resources assessment. Food and Agriculture Organization of the United
Nations, Rome
Gotway CA, Young LJ (2002) Combining incompatible spatial data. J Am Stat Assoc
97(458):632–648
Haberl H, Erb KH, Krausmann F, Gaube V, Bondeau A, Plutzar C, Gingrich S, Lucht W, FischerKowalski M (2007) Quantifying and mapping the human appropriation of net primary production in earth’s terrestrial ecosystems. Proc Natl Acad Sci U S A 104(31):12942–12945
Haith DA, Shoemaker LL (1987) Generalized watershed loading functions for stream-flow
nutrients. Water Resour Bull 23(3):471–478
Hoshino S (2001) Multilevel modeling on farmland distribution in Japan. Land Use Policy
18(1):75–90
Howard DM, Howard PJA, Howard DC (1995) A Markov model projection of soil organic-carbon
stores following land-use changes. J Environ Manag 45(3):287–302
Hu ZY, Lo CP (2007) Modeling urban growth in Atlanta using logistic regression. Comput
Environ Urban Syst 31(6):667–688
Irwin EG, Bockstael NE (2002) Interacting agents, spatial externalities and the evolution of
residential land use patterns. J Econ Geogr 2(1):31–54
Jantz CA, Goetz SJ, Shelley MK (2004) Using the SLEUTH urban growth model to simulate the
impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan
area. Environ Plan B Plan Des 31(2):251–271
Jensen JR (1983) Biophysical remote-sensing. Ann Assoc Am Geogr 73(1):111–132
Kerr S, Liu SG, Pfaff ASP, Hughes RF (2003) Carbon dynamics and land-use choices: building a
regional-scale multidisciplinary model. J Environ Manag 69(1):25–37
Lesschen JP, Verburg PH, Staal SJ (2005) Statistical methods for analysing the spatial dimension
of changes in land use and farming systems. LUCC report series no. 7. International Livestock
Research Institute/LUCC Focus 3 Office, Nairobi/Wageningen
Li X, Yeh AG (2002) Neural-network-based cellular automata for simulating multiple land use
changes using GIS. Int J Geogr Inf Sci 16(4):323–343
Ligmann-Zielinska A (2009) The impact of risk-taking attitudes on a land use pattern: an agentbased model of residential development. J Land Use Sci 4(4):215–232
Lin YP, Hong NM, Wu PJ, Lin CJ (2007) Modeling and assessing land-use and hydrological
processes to future land-use and climate change scenarios in watershed land-use planning.
Environ Geol 53(3):623–634
Liu WG, Seto KC (2008) Using the ART-MMAP neural network to model and predict urban
growth: a spatiotemporal data mining approach. Environ Plan B Plan Des 35(2):296–317
1 Land Change Modeling: Status and Challenges
15