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Modeling and predicting land use and land cover changes using remote sensing in tropical coastal ecosystems of southern Peru

  • Ellen Delgado
  • , Elgar Barboza
  • , Nilton B. Rojas-Briceño
  • , Alexander Cotrina-Sanchez
  • , Armando Valdés-Velásquez
  • , Rocío López de la Lama
  • , Camila Llerena-Cayo
  • , Santiago de la Puente
  • Universidad Peruana Cayetano Heredia
  • Inc. (ESRI)
  • University of Georgia
  • Universidad Nacional Toribio Rodrıguez de Mendoza de Amazonas
  • Universidad Nacional de Moquegua
  • University of British Columbia
  • Norwegian Institute for Water Research

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Understanding the spatial impacts of human activities on coastal marine ecosystems is fundamental to manage the dynamic changes in land use that affect these natural spaces. In this study, we assessed land-use and land-cover (LULC) changes from 1990 to 2020 and their projection to 2030 in the Ica region (Peru). Through the integration of geographic information systems (GIS) and remote sensing techniques, LULC changes were analyzed. The kappa index reported an accuracy of the LULC maps above 87% in the analysis period. In addition, the quantitative analysis revealed that in 1990, 2000, 2010 and 2020, cultivated areas increased by 48.9, 53.2, 60.11 and 75.72% in influence zones A1, A2, A3 and A4, respectively, while urban development increased by 2.84, 4.81, 4.82 and 7.82% ha in the same zones. Likewise, the loss and gain analysis of land cover by period revealed that, in 1990, 2000, 2010 and 2020, cultivated areas increased by 48.9, 53.2, 60.11 and 75.72% in the zones of influence A1, A2, A3 and A4, respectively, while urban development increased by 2.84, 4.81, 4.82 and 7.82% ha in the same zones. In addition, during the period 2010–2020, the rate of transformation reached 53.1 ha/year towards urban uses in the coastal zone (A3) and 981.2 ha/year towards crops in zone A4. By 2030, urban expansion along the coast and major roads is expected to significantly reduce natural cover. Importantly, these results underscore the greater relevance of our integrated approach, which is applicable to others like it.

Original languageEnglish
Article number139
JournalEnvironmental Sciences Europe
Volume37
Issue number1
DOIs
StatePublished - Dec 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Cloud computing
  • Coastal ecosystems
  • Comparison of subsequent classification
  • Paracas
  • Random forest

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