Assessment of land cover changes in the hinterland of Barranquilla (Colombia) using Landsat imagery and logistic regression Schubert, Henry Caballero Calvo, Andrés Rauchecker, Markus Rojas Zamora, Óscar Brokamp, Grischa Schütt, Brigitta Colombian Caribbean Urbanisation Tropical dry forest Random forest classifier Woody vegetation changes Barranquilla is known as a dynamically growing city in the Colombian Caribbean. Urbanisation induces land use and land cover (LULC) changes in the city and its hinterland affecting the region’s climate and biodiversity. This paper aims to identify the trends of land use and land cover changes in the hinterland of Barranquilla corresponding to 13 municipalities in the north of the Department Atlántico. Landsat TM/ETM/OLI imagery from 1985 to 2017 was used to map and analyse the spatio-temporal development of land use and land cover changes. During the investigation period, the settlement areas grew by approximately 50% (from 103.3 to 153.6 km2), while areas with woody vegetation cover experienced dynamic changes and increased in size since 2001. Peri-urban and rural areas were characterized by highly dynamic changes, particularly regarding clearing and recovery of vegetated areas. Regression analyses were performed to identify the impact factors of detected vegetation cover changes. Computed logistic regression models included 20 independent variables, such as relief, climate, soil, proximity characteristics and socio-economic data. The results of this study may act as a basis to enable researchers and decision-makers to focus on the most important signals of systematic landscape transformations and on the conservation of ecosystems and the services they provide. 2024-01-16T08:42:42Z 2024-01-16T08:42:42Z 2018 info:eu-repo/semantics/article SCHUBERT, H., CABALLERO CALVO, A., RAUCHECKER, M., ROJAS ZAMORA, O., BROKAMP, G. y SCHÜTT, B. (2018). Assessment of land cover changes in the hinterland of Barranquilla (Colombia) using Landsat imagery and logistic regression. Land, 7(4), 152, p. 24. ISSN: 2073-445X. https://doi.org/10.3390/land7040152 https://hdl.handle.net/10481/86814 https://doi.org/10.3390/land7040152 eng info:eu-repo/semantics/openAccess MDPI