Version 1
: Received: 7 November 2020 / Approved: 9 November 2020 / Online: 9 November 2020 (22:56:32 CET)
How to cite:
MOHAMED, B.; Fatiha, B.; Hassan, R.; SAID, B.; TAOUFIK, B.; NAJAT, B.; Mohamed, B. Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco. Preprints2020, 2020110287. https://doi.org/10.20944/preprints202011.0287.v1
MOHAMED, B.; Fatiha, B.; Hassan, R.; SAID, B.; TAOUFIK, B.; NAJAT, B.; Mohamed, B. Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco. Preprints 2020, 2020110287. https://doi.org/10.20944/preprints202011.0287.v1
MOHAMED, B.; Fatiha, B.; Hassan, R.; SAID, B.; TAOUFIK, B.; NAJAT, B.; Mohamed, B. Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco. Preprints2020, 2020110287. https://doi.org/10.20944/preprints202011.0287.v1
APA Style
MOHAMED, B., Fatiha, B., Hassan, R., SAID, B., TAOUFIK, B., NAJAT, B., & Mohamed, B. (2020). Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco. Preprints. https://doi.org/10.20944/preprints202011.0287.v1
Chicago/Turabian Style
MOHAMED, B., BENCHELHA NAJAT and Bezza Mohamed. 2020 "Modeling of Urban Growth Using Cellular Automata and GIS Case of Benslimane in Morocco" Preprints. https://doi.org/10.20944/preprints202011.0287.v1
Abstract
In this study, our goal was to research land-use change by combining spatio–temporal land use/land cover monitoring (LULC (1989–2019) and urban growth modeling (1999–2039) in Benslimane, Morocco, to determine the effect of urban growth on different groups based on cellular automata (CA) and geospatial methods. A further goal was to test the reliability of the AC algorithm for urban expansion modeling. To do this, four years of satellite data were used at the same time as population density, downtown distance, slope, and ground road distance. The LULC satellite reported a rise of 3.8 km2 (318% variation) during 1989–2019. Spatial transformation analysis reveals a good classification similarity ranging from 89% to 91% with the main component analysis (PCA) technique. The statistical accuracy between the satellite scale and the replicated built region of 2019 gave 97.23 %t of the confusion matrix overall accuracy, and the region under the receiver operational characteristics (ROC) curve to 0.94, suggesting the model's high accuracy. Although the constructed area remains low relative to the total area of the municipality's territory, the LULC project shows that the urban area will extend to 5,044 km2 in 2019, principally in the western and southwestern sections. In 2019–2039, urban development is expected to lead to a transformation of the other class (loss of 1,364 km2), followed by vegetation cover (loss of 0.345 km2). In spatial modeling and statistical calculations, the GDAL and NumPy Python 3.8 libraries were successful.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
