Landuse-Landcover Change Using Open Source GIS

7-10 February 2017, Ben Gurion University, Sde Boker Israel

Among the many geo-spatial analysis tools available in GIS applications, Landuse Landcover Change (LULCC) analysis is key to understanding environmental changes over time.  Whether these changes are anthropogenic or induced by climate change, a properly configured LULCC procedure can pinpoint which classifications have changed, and where the changes occurred. Additionally, a prediction model is implemented to extrapolate the changes to a future date. The workshop was conducted  using the open source GIS application QGIS [1]. Over the past decade, open source GIS tools have stabilized and currently cover the whole spectrum of spatial analysis[2], remote sensing, geo-statistics, geo-spatial databases and web mapping. The workshop focused on a QGIS plugin known as “MOLUSCE”[3].  A dataset, prepared in advance, included MODIS based landcover data at two dates, elevation data from SRTM, a streams layer, and administrative boundaries. The analysis region for the workshop was chosen in northern Ethiopia, where past research[4] on multi-temporal landcover change was already published.  Participants loaded the data layers, and stepped through the initial preparatory stages to match all data sets for input into the LULCC model. Then the model was run, and results were incorporated into the maps for display.

[1]    http://www.qgis.org/en/site/

[2]    See, for example: Petrasova, A., V. Petras, D. Van Berkel, B. A. Harmon, H. Mitasova, and R. K. Meentemeyer. “OPEN SOURCE APPROACH TO URBAN GROWTH SIMULATION.” ISPRS – International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 22, 2016): 953–59. doi:10.5194/isprsarchives-XLI-B7-953-2016.

[3] http://wiki.gis-lab.info/w/Landscape_change_analysis_with_MOLUSCE_-_methods_and_algorithms

[4 ] Worku Zewdie & Elmar Csaplovies (2015) Remote Sensing based multi-temporal land cover classification and change detection in northwestern Ethiopia, European Journal of Remote Sensing, 48:1, 121-139.

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