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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Henry Schubert & Andrés Caballero Calvo & Markus Rauchecker & Oscar Rojas-Zamora & Grischa Brokamp & Brigitta Schütt, 2018. "Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression," Land, MDPI, vol. 7(4), pages 1-24, December.
  • Handle: RePEc:gam:jlands:v:7:y:2018:i:4:p:152-:d:188475
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    References listed on IDEAS

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    1. Norbert Anselm & Grischa Brokamp & Brigitta Schütt, 2018. "Assessment of Land Cover Change in Peri-Urban High Andean Environments South of Bogotá, Colombia," Land, MDPI, vol. 7(2), pages 1-28, June.
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    Cited by:

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    3. Mawuli Asempah & Wahib Sahwan & Brigitta Schütt, 2021. "Assessment of Land Cover Dynamics and Drivers of Urban Expansion Using Geospatial and Logistic Regression Approach in Wa Municipality, Ghana," Land, MDPI, vol. 10(11), pages 1-19, November.
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    5. Andrew K. Marondedze & Brigitta Schütt, 2019. "Dynamics of Land Use and Land Cover Changes in Harare, Zimbabwe: A Case Study on the Linkage between Drivers and the Axis of Urban Expansion," Land, MDPI, vol. 8(10), pages 1-20, October.
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