Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 953-959, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
22 Jun 2016
A. Petrasova1,2, V. Petras1,2, D. Van Berkel1, B. A. Harmon1,4, H. Mitasova1,2, and R. K. Meentemeyer1,3 1Center for Geospatial Analytics, North Carolina State University, USA
2Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, USA
3Department of Forestry and Environmental Resources, North Carolina State University, USA
4Department of Landscape Architecture, North Carolina State University, USA
Keywords: GRASS GIS, FUTURES, urbanization, land change, open science, simulation Abstract. Spatial patterns of land use change due to urbanization and its impact on the landscape are the subject of ongoing research. Urban growth scenario simulation is a powerful tool for exploring these impacts and empowering planners to make informed decisions. We present FUTURES (FUTure Urban – Regional Environment Simulation) – a patch-based, stochastic, multi-level land change modeling framework as a case showing how what was once a closed and inaccessible model benefited from integration with open source GIS.We will describe our motivation for releasing this project as open source and the advantages of integrating it with GRASS GIS, a free, libre and open source GIS and research platform for the geospatial domain. GRASS GIS provides efficient libraries for FUTURES model development as well as standard GIS tools and graphical user interface for model users. Releasing FUTURES as a GRASS GIS add-on simplifies the distribution of FUTURES across all main operating systems and ensures the maintainability of our project in the future. We will describe FUTURES integration into GRASS GIS and demonstrate its usage on a case study in Asheville, North Carolina. The developed dataset and tutorial for this case study enable researchers to experiment with the model, explore its potential or even modify the model for their applications.
Conference paper (PDF, 3075 KB)

Citation: Petrasova, A., Petras, V., Van Berkel, D., Harmon, B. A., Mitasova, H., and Meentemeyer, R. K.: OPEN SOURCE APPROACH TO URBAN GROWTH SIMULATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 953-959,, 2016.

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