{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T16:14:58Z","timestamp":1774714498785,"version":"3.50.1"},"reference-count":139,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T00:00:00Z","timestamp":1730160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of History, Geography and Social Sciences, Edge Hill University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Greater Amanzule Peatlands (GAP) in Ghana is an important biodiversity hotspot facing increasing pressure from anthropogenic land-use activities driven by rapid agricultural plantation expansion, urbanisation, and the burgeoning oil and gas industry. Accurate measurement of how these pressures alter land cover over time, along with the projection of future changes, is crucial for sustainable management. This study aims to analyse these changes from 2010 to 2020 and predict future scenarios up to 2040 using multi-source remote sensing and machine learning techniques. Optical, radar, and topographical remote sensing data from Landsat-7, Landsat-8, ALOS\/PALSAR, and Shuttle Radar Topography Mission derived digital elevation models (DEMs) were integrated to perform land cover change analysis using Random Forest (RF), while Cellular Automata Artificial Neural Networks (CA-ANNs) were employed for predictive modelling. The classification model achieved overall accuracies of 93% in 2010 and 94% in both 2015 and 2020, with weighted F1 scores of 80.0%, 75.8%, and 75.7%, respectively. Validation of the predictive model yielded a Kappa value of 0.70, with an overall accuracy rate of 80%, ensuring reliable spatial predictions of future land cover dynamics. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6570 \u00b1 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 \u00b1 110.96 hectares to 56,617 \u00b1 220.90 hectares) and a 6% reduction in natural forest cover (5965 \u00b1 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 \u00b1 163.79 hectares to 29,424 \u00b1 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, they do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the understudied GAP region, offering critical insights for developing targeted conservation strategies. Additionally, the methodological framework, which combines optical, radar, and topographical data with machine learning, provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands that is applicable to other regions facing similar environmental challenges.<\/jats:p>","DOI":"10.3390\/rs16214013","type":"journal-article","created":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T06:29:57Z","timestamp":1730183397000},"page":"4013","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Predictive Modelling of Land Cover Changes in the Greater Amanzule Peatlands Using Multi-Source Remote Sensing and Machine Learning Techniques"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8394-1241","authenticated-orcid":false,"given":"Alex Owusu","family":"Amoakoh","sequence":"first","affiliation":[{"name":"Department of History, Geography and Social Sciences, Edge Hill University, Ormskirk L39 4QP, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9394-5630","authenticated-orcid":false,"given":"Paul","family":"Aplin","sequence":"additional","affiliation":[{"name":"Department of Geography, Mary Immaculate College, V94 VN26 Limerick, Ireland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4845-4215","authenticated-orcid":false,"given":"Pedro","family":"Rodr\u00edguez-Veiga","sequence":"additional","affiliation":[{"name":"Sylvera Ltd., London N1 7SR, UK"},{"name":"School of Geography, Geology and the Environment, University of Leicester, Leicester LE1 7RH, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7222-9486","authenticated-orcid":false,"given":"Cherith","family":"Moses","sequence":"additional","affiliation":[{"name":"Department of History, Geography and Social Sciences, Edge Hill University, Ormskirk L39 4QP, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8589-0553","authenticated-orcid":false,"given":"Carolina Pe\u00f1a","family":"Alonso","sequence":"additional","affiliation":[{"name":"Grupo de Geograf\u00eda, Medio Ambiente y Tecnolog\u00edas de la Informaci\u00f3n Geogr\u00e1fica, Instituto de Oceanograf\u00eda y Cambio Global, Universidad de Las Palmas de Gran Canaria, 35214 Las Palmas, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0062-6954","authenticated-orcid":false,"given":"Joaqu\u00edn A.","family":"Cort\u00e9s","sequence":"additional","affiliation":[{"name":"Department of History, Geography and Social Sciences, Edge Hill University, Ormskirk L39 4QP, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8101-0670","authenticated-orcid":false,"given":"Irene","family":"Delgado-Fernandez","sequence":"additional","affiliation":[{"name":"Earth Sciences Department, Faculty of Marine and Environmental Sciences (INMAR), University of Cadiz, 11001 Cadiz, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6479-5928","authenticated-orcid":false,"given":"Stephen","family":"Kankam","sequence":"additional","affiliation":[{"name":"Hen Mpoano (Our Coast), Takoradi WS-289-9503, Ghana"}]},{"given":"Justice Camillus","family":"Mensah","sequence":"additional","affiliation":[{"name":"Hen Mpoano (Our Coast), Takoradi WS-289-9503, Ghana"}]},{"given":"Daniel Doku Nii","family":"Nortey","sequence":"additional","affiliation":[{"name":"Hen Mpoano (Our Coast), Takoradi WS-289-9503, Ghana"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,29]]},"reference":[{"key":"ref_1","unstructured":"FAO (2020). 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