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

dc.contributor.authorDelgado, Ellen
dc.contributor.authorBarboza, Elgar
dc.contributor.authorRojas-Briceño, Nilton B.
dc.contributor.authorCotrina-Sanchez, Alexander
dc.contributor.authorValdés-Velásquez, Armando
dc.contributor.authorde la Lama, Rocío López
dc.contributor.authorLlerena-Cayo, Camila
dc.contributor.authorde la Puente, Santiago
dc.date.accessioned2026-05-01T06:26:02Z
dc.date.issued2025
dc.description.abstractUnderstanding 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. © The Author(s) 2025.en_US
dc.description.sponsorshipThis research was funded by the Global Challenges Research Fund (GCRF). The spatial analysis was completed at the Center for Geospatial Research of the University of Georgia. The APC was funded by the Vice-Rectorate for Research of the Universidad Nacional del Amazonas Toribio Rodr\u00EDguez de Mendoza de Amazonas.es_PE
dc.identifier.doihttps://doi.org/10.1186/s12302-025-01181-y
dc.identifier.scopus2-s2.0-105012831566
dc.identifier.urihttps://hdl.handle.net/20.500.12866/19431
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofurn:issn:2190-4707
dc.relation.ispartofseriesEnvironmental Sciences Europe
dc.relation.issn2190-4707
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectCloud computingen_US
dc.subjectCoastal ecosystemsen_US
dc.subjectComparison of subsequent classificationen_US
dc.subjectParacasen_US
dc.subjectRandom foresten_US
dc.titleModeling and predicting land use and land cover changes using remote sensing in tropical coastal ecosystems of southern Peruen_US
dc.typehttps://purl.org/coar/resource_type/c_2df8fbb1
dc.type.localArtículo de revista
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication

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