Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression

Henry Schubert, Andrés Caballero Calvo, Markus Rauchecker, Oscar Rojas-Zamora, Grischa Brokamp and Brigitta Schütt
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Henry Schubert: Department of Earth Sciences, Physical Geography, Freie Universität Berlin, Malteserstr. 74-100, Haus H, 12249 Berlin, Germany
Andrés Caballero Calvo: Departamento de Arquitectura y Urbanismo, Universidad del Norte, Km.5 Vía Puerto Colombia, Área Metropolitana de Barranquilla 081007, Colombia
Markus Rauchecker: Institute for Latin American Studies, Freie Universität Berlin, Rüdesheimer Str. 54-56, 14197 Berlin, Germany
Oscar Rojas-Zamora: Departamento de Química y Biología, Universidad del Norte, Km.5 Vía Puerto Colombia, Área Metropolitana de Barranquilla 081007, Colombia
Grischa Brokamp: Botanischer Garten und Botanisches Museum Berlin-Dahlem, Freie Universität Berlin, Königin-Luise-Straße 6-8, 14195 Berlin, Germany
Brigitta Schütt: Department of Earth Sciences, Physical Geography, Freie Universität Berlin, Malteserstr. 74-100, Haus H, 12249 Berlin, Germany

Land, 2018, vol. 7, issue 4, 1-24

Abstract: 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 km 2 ), 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.

Keywords: Colombian Caribbean; urbanisation; tropical dry forest; random forest classifier; woody vegetation changes (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:7:y:2018:i:4:p:152-:d:188475

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