Abstract
Land system science as a complex system has been explored by using various approaches such as remote sensing, economics, ecology, and geography. Agent-based modeling (ABM), as a third way of doing science, enables researchers to explore the complex system deeper on land science. Interdisciplinary approach has brought land use science into agent-based modeling. Bottom-up view and inclusion of agent as real-life representation brought a powerful method to analyze land use change and cover (LUCC) and explore coupling between human and natural system. Land use decision-making is a function of interaction between internal models of the land manager with its environment. This study incorporates two variables, commercial and farm expectation, as a representation between productivity farmland and other commercial objectives of the land. Agents have the ability to alter land use based on rational and irrational decision-making process. The objective of this paper is to capture the behavior of the agent and observe land use change that resulted from agent decision-making.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Firman, T. (2000). Rural to urban land conversion in Indonesia during boom and bust periods. Land Use Policy, 17(1), 13–20.
Verburg, P. H., Bouma, J., Veldkamp, A., & Bouma, J. (1999). Land-use change under conditions of high population pressure-The Java Case. Global Environmental Change, 9, 303–312.
Thamrin, F. D., Rizal, S., Bunasor, S., & Hari, W. (2015). Economic behaviour versus rice farmer environmental behaviour in making food independence: Case west Java-Indonesia. Asian Journal of Scientific Research, 8(1), 67–73.
Firman, T. (2009). The continuity and change in mega-urbanization in Indonesia: A survey of Jakarta–Bandung Region (JBR) development. Habitat International, 33(4), 327–339.
Turner II B. L., Lambin, E. F., & Reenberg, A. 2007. The emergence of land change science for global environmental change and sustainability, presented at the Proceedings of the National Academy of Sciences of The United States of America, vol. 104, pp. 20666–20671.
P. H. Verburg, K. H. Erb, O. Mertz, & G. Espindola 2013, October, Land system science: Between global challenges and local realities Current Opinion in Environmental Sustainability, 5(5), 433–437.
Brown, D. G., Verburg, P. H., Pontius Jr., R. G., & Lange, M. D. (2013). Opportunities to improve impact, integration, and evaluation of land change models. Current Opinion in Environmental Sustainability, 5(5), 452–457.
Parker, D. C., Hessl, A., & Davis, S. C. (2008). Complexity, land-use modeling, and the human dimension: Fundamental challenges for mapping unknown outcome spaces. Geoforum, 39(2), 789–804.
Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118.
Rounsevell, M. D. A., Pedroli, B., Erb, K.-H., Gramberger, M., Busck, A. G., Haberl, H., Kristensen, S., Kuemmerle, T., Lavorel, S., Lindner, M., Lotze-Campen, H., Metzger, M. J., Murray-Rust, D., Popp, A., Pérez-Soba, M., Reenberg, A., Vadineanu, A., Verburg, P. H., & Wolfslehner, B. (2012). Challenges for land system science. Land Use Policy, 29(4), 899–910.
Jokar Arsanjani, J. (2012). Dynamic land use/cover change modelling. Berlin/Heidelberg: Springer Berlin Heidelberg.
Moore, N., Alagarswamy, G., Pijanowski, B., Thornton, P., Lofgren, B., Olson, J., Andresen, J., Yanda, P., & Qi, J. (2011). East African food security as influenced by future climate change and land use change at local to regional scales. Climatic Change, 110(3–4), 823–844.
Kohler, T. A., & Gummerman, G. J. (2001). Dynamics of human and primate societies: Agent-based modeling of social and spatial processes. Oxford University Press.
Aroengbinang, B. W., & Kaswanto. (2015). Driving force analysis of landuse and cover changes in Cimandiri and Cibuni Watersheds. Procedia Environmental Sciences, 24, 184–188.
Meyfroidt, P., Lambin, E. F., Erb, K.-H., & Hertel, T. W. (2013). Globalization of land use: Distant drivers of land change and geographic displacement of land use. Current Opinion in Environmental Sustainability, 5(5), 438–444.
Hersperger, A. M., Gennaio, M.-P., Verburg, P. H., & Bürgi, M. 2010. Linking land change with driving forces and actors: Four conceptual models. Ecology and Society, 15.
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., Huse, G., Huth, A., Jepsen, J. U., Jørgensen, C., Mooij, W. M., Müller, B., Pe’er, G., Piou, C., Railsback, S. F., Robbins, A. M., Robbins, M. M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R. A., Vabø, R., Visser, U., & DeAngelis, D. L. (2006, September). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1–2), 115–126.
Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H., & Schwarz, N. (2013). Describing human decisions in agent-based models – ODD + D, an extension of the ODD protocol. Environmental Modelling & Software, 48, 37–48.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Nurdayat, I.F., Siallagan, M. (2017). Land Use Decision-Making Strategy in Bandung: An Agent-Based Modeling Approach. In: Putro, U., Ichikawa, M., Siallagan, M. (eds) Agent-Based Approaches in Economics and Social Complex Systems IX. Agent-Based Social Systems, vol 15. Springer, Singapore. https://doi.org/10.1007/978-981-10-3662-0_7
Download citation
DOI: https://doi.org/10.1007/978-981-10-3662-0_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3661-3
Online ISBN: 978-981-10-3662-0
eBook Packages: Business and ManagementBusiness and Management (R0)