gesjGEOGRAPHY, ENVIRONMENT, SUSTAINABILITYGEOGRAPHY, ENVIRONMENT, SUSTAINABILITY2071-93882542-1565Russian Geographical Society10.24057/2071-9388-2026-4486gesj-5052Research ArticleRESEARCH PAPERСтатьиRemote sensing and geospatial approach for land degradation risk assessment in the costa verde bay southeast of brazilAl AbedMohammad

Rua Vital Brazil Filho, 64, Vital Brazil, Zip Code 24230-340, Niterói, RJ

m.abed@yahoo.comAlmoustafaTurkia

Rd, Manchester, M13 9PL

NajjarDiyaa

Severnaya Dvina Emb. 17, 163002 Arkhangelsk

SaboyaMarcos

Rua Vital Brazil Filho, 64, Vital Brazil, Zip Code 24230-340, Niterói, RJ

Machado PimentelRoberson

Rua Vital Brazil Filho, 64, Vital Brazil, Zip Code 24230-340, Niterói, RJ

Kangussu DonagemmaGuilherme

Rua Jardim Botânico, 1024, Jardim Botânico, CEP 22460-000, Rio de Janeiro, RJ

Ferreira DiasFábio

Rua Vital Brazil Filho, 64, Vital Brazil, Zip Code 24230-340, Niterói, RJ

Department of Animal Science, Faculty of Veterinary Medicine, Fluminense Federal University (UFF)BrazilDepartment of Geography, School of Environment, Education and Development, University of Manchester, OxfordUnited KingdomDepartment of Forestry and Forest Management, Northern Arctic Federal UniversityRussian FederationEMBRAPA SOLOSBrazil202609102026193165175Copyright © Al Abed M., Almoustafa T., Najjar D., Saboya M., Machado Pimentel R., Kangussu Donagemma G., Ferreira Dias F., 20262026Al Abed M., Almoustafa T., Najjar D., Saboya M., Machado Pimentel R., Kangussu Donagemma G., Ferreira Dias F.Al Abed M., Almoustafa T., Najjar D., Saboya M., Machado Pimentel R., Kangussu Donagemma G., Ferreira Dias F.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ges.rgo.ru/jour/article/view/5052

This study evaluates land degradation risk in Brazil’s Costa Verde by adapting the United Nations Environment Program, Priority Actions Program Regional Activity Centre (PAP/RAC) methodology for the first time to a humid tropical coastal environment. Unlike previous applications confined to semi-arid and Mediterranean contexts, this research integrates the PAP/RAC framework with 40 years of multi-source remote sensing data (Landsat 5/8/9; 1985–2025), land use/land cover change detection, and Mann–Kendall trend analysis, a hybrid approach that has not previously been applied in this biome. The results reveal that while 87.37% of the region remains stable, 6.24% faces active degradation from sheet and rill erosion, primarily concentrated on steep coastal slopes and expanding urban-fringe zones. Land use/land cover analysis documented a 254.17% urban expansion (+58.01 km²) since 1985, coinciding with significant losses in sensitive ecosystems, including wetlands (-47.79%) and wooded sandbank vegetation (-18.40%). To validate these dynamics, a Mann–Kendall test confirmed a statistically significant increasing trend in minimum vegetation cover (p<0.01), suggesting a long-term improvement in the minimum vegetation baseline despite localized anthropogenic pressures. A multi-criteria prioritization procedure identified 58.19 km² for immediate curative intervention and 150.74 km² for preventive protection. By bridging the PAP/RAC framework with statistical trend analysis and spatial planning, this study provides a replicable framework for erosion risk assessment in urbanizing tropical zones, offering spatial outputs that directly support the Brazilian Forest Code and municipal master plans.

coastal sustainabilityland degradation riskremote sensingGISAtlantic ForestPAP/RACWe would like to express our sincere gratitude to the Foundation for Research Support of the State of Rio de Janeiro (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPERJ) for their support and provision of scientific scholarship (E- 26/200611/2025). The authors would like to express Their sincere gratitude to The Council for At-Risk Academics /The British Academy/Cara/Leverhulme Researchers at Risk Research Support Grant. The University of Manchester.ReferencesAlAbed M., Almoustafa T., Pimentel R., & Dias F.F. (2026). Geovisualizing land degradation risk in Southeast Brazil using remote sensing and GIS-based assessment. Scientific Reports, 16, Article 22091, https://doi.org/10.1038/s41598-026-49578-wAlAbed M., Almoustafa T., Pimentel R., & Dias F.F. (2026). Geovisualizing land degradation risk in Southeast Brazil using remote sensing and GIS-based assessment. 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The authors declare that there are no conflicts of interest present.