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Growth Simulation of Agriculturally Dominant Cities by Incorporating Multiple Drivers into a CA-based patch-generating Land Use Simulation Model: A Case Study in Siracusa, Italy
- Source :
- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-5-2024, Pp 39-45 (2024)
- Publication Year :
- 2024
- Publisher :
- Copernicus Publications, 2024.
-
Abstract
- Understanding the historical trajectory of land use and land cover (LULC) and predicting future alterations is essential to advancing the SDGs. Current researches on LULC in agriculture-dominated cities primarily focuses on the spatiotemporal pattern analysis of carbon storage changes, with relatively little attention given to LULC simulation studies. Moreover, most studies employing cellular automata (CA) models concentrate on urban centers, overlooking the specific sustainable development of agricultural cities. This paper selects Siracusa, Italy, as a case study, incorporating multiple drivers and constructing four development scenarios. The patch-generating land use simulation (PLUS) model is employed to predict the LULC for Siracusa by 2030 and to examine potential transformations under each scenario. Our findings show that 60% of the land in Siracusa is designated as cropland, predominantly situated in flat regions. Our simulation results reveal that urbanization and demographic growth are the main factors driving cropland conversion to urban areas. Different development scenarios exhibit significant variations in future land use structures; the cropland protection scenario emphasizes the stability and sustainability of agricultural development, whereas the economic development scenario highlights the substantial impact of urban and industrial expansion on agricultural land. These insights are instrumental for land use planning and policy-making in Siracusa and other agriculture-centric cities, providing a framework to guide urbanization while promoting agricultural sustainability.
Details
- Language :
- English
- ISSN :
- 16821750 and 21949034
- Volume :
- XLVIII-5-2024
- Database :
- Directory of Open Access Journals
- Journal :
- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.276bd98ecff4e1ea0072759925dc400
- Document Type :
- article
- Full Text :
- https://doi.org/10.5194/isprs-archives-XLVIII-5-2024-39-2024