Chapter 1
Land Change Modeling: Status
and Challenges
Ting Liu and Xiaojun Yang
Abstract Over the past years, land change science has emerged as a fundamental
component of global environmental change and sustainability research, and modeling of land change has been recognized as a premier research area in land change
science. Various land change modeling approaches have been developed to explore
the functioning of land changes at aggregated and individual levels, across various
spatiotemporal scales, as well as in human, natural, or the coupled systems. This
chapter will review a collection of land change modeling approaches including
statistical regression models, artificial neural networks, Markov chain models,
cellular automata, economic models, and agent-based models. For each approach,
the theoretical and methodological basics and major characteristics will be examined. Moreover, several important issues challenging the successful implementation of land change modeling will be discussed, which include coupling human and
environmental systems, scale dependency and multilevel interactions, and temporal
dynamics and complexity. Finally, a review on the progress of integrating land
change models with other environmental modeling techniques for global environmental change research will be provided.
Keywords Land change modeling • Land change science • Global change • Land
use and land cover change • Coupled human-environmental systems
1.1 Introduction
The process of global change is altering the earth system and its capacity to sustain
life (U.S. Global Change Research Program 2014). Rapid human population
growth, along with their increasing demand for food, water, energy, and other
T. Liu (*)
Department of Geography and Environmental Studies, Northeastern Illinois University,
Chicago, IL 60625, USA
e-mail: tliu1@neiu.edu
X. Yang
Department of Geography, Florida State University, Tallahassee, FL 32306, USA
e-mail: xyang@fsu.edu
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_1
3
Land Change Modeling: Status
and Challenges
Ting Liu and Xiaojun Yang
Abstract Over the past years, land change science has emerged as a fundamental
component of global environmental change and sustainability research, and modeling of land change has been recognized as a premier research area in land change
science. Various land change modeling approaches have been developed to explore
the functioning of land changes at aggregated and individual levels, across various
spatiotemporal scales, as well as in human, natural, or the coupled systems. This
chapter will review a collection of land change modeling approaches including
statistical regression models, artificial neural networks, Markov chain models,
cellular automata, economic models, and agent-based models. For each approach,
the theoretical and methodological basics and major characteristics will be examined. Moreover, several important issues challenging the successful implementation of land change modeling will be discussed, which include coupling human and
environmental systems, scale dependency and multilevel interactions, and temporal
dynamics and complexity. Finally, a review on the progress of integrating land
change models with other environmental modeling techniques for global environmental change research will be provided.
Keywords Land change modeling • Land change science • Global change • Land
use and land cover change • Coupled human-environmental systems
1.1 Introduction
The process of global change is altering the earth system and its capacity to sustain
life (U.S. Global Change Research Program 2014). Rapid human population
growth, along with their increasing demand for food, water, energy, and other
T. Liu (*)
Department of Geography and Environmental Studies, Northeastern Illinois University,
Chicago, IL 60625, USA
e-mail: tliu1@neiu.edu
X. Yang
Department of Geography, Florida State University, Tallahassee, FL 32306, USA
e-mail: xyang@fsu.edu
© Springer Science+Business Media Dordrecht 2015
J. Li, X. Yang (eds.), Monitoring and Modeling of Global Changes:
A Geomatics Perspective, Springer Remote Sensing/Photogrammetry,
DOI 10.1007/978-94-017-9813-6_1
3