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Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo

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School of Forestry, Northeast Forestry University, Harbin 150040, China
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Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, China
3
Department of Natural Resources Management, Faculty of Agricultural Sciences, University of Kinshasa, 117 Kinshasa, Democratic Republic of the Congo
*
Author to whom correspondence should be addressed.
Academic Editor: Vilém Pechanec
Sustainability 2021, 13(12), 6898; https://doi.org/10.3390/su13126898
Received: 14 May 2021 / Revised: 14 June 2021 / Accepted: 15 June 2021 / Published: 18 June 2021
Villages within the Luki Biosphere Reserve and the surrounding cities have undergone rapid demographic growth and urbanization that have impacted the reserve’s natural landscape. However, no study has focused on the spatiotemporal analysis of its land use/land cover. The present research aims at providing a comprehensive analysis of land use/land cover change in the Luki Biosphere Reserve from the year 1987 to 2020, and to predict its future change for the year 2038. Landsat images were classified in order to provide land use/land cover maps for the years 1987, 2002, 2017 and 2020. Based on these maps, change detection, gradient direction, and landscape metric analyses were performed. In addition, land use/land cover change prediction was carried out using the Multilayer Perceptron Markov model. The results revealed significant land use/land cover changes in the Luki Biosphere Reserve during the study period. Indeed, tremendous changes in the primary forest, which lost around 17.8% of its total area, were noted. Other classes, notably savannah, secondary forest, built-up area, fallow land and fields had gained 79.35, 1150.36, 67.63, 3852.12 hectares, respectively. Based on the landscape metric analysis, it was revealed that built-up areas and fallow land and fields experienced an aggregation trend, while other classes showed disaggregation and fragmentation trends. Analysis further revealed that village expansion has significantly affected the process of land use/land cover change in the Luki Biosphere Reserve. However, the prediction results revealed that the primary forest will continue to increase while built-up area, fallow land and fields will follow a trend similar to a previous one. As for secondary forest and savannah, the forecast revealed a decrease of the extent during the period extending from 2020 to 2038. The present findings will benefit the decision makers, particularly in the sustainable natural resources management of the Luki Biosphere Reserve. View Full-Text
Keywords: Luki; multilayer perceptron neural network; Markov chain model; land use change; landscape metrics Luki; multilayer perceptron neural network; Markov chain model; land use change; landscape metrics
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MDPI and ACS Style

Michel, O.O.; Ying, Y.; Wenyi, F.; Chen, C.; Kaiko, K.S. Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo. Sustainability 2021, 13, 6898. https://doi.org/10.3390/su13126898

AMA Style

Michel OO, Ying Y, Wenyi F, Chen C, Kaiko KS. Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo. Sustainability. 2021; 13(12):6898. https://doi.org/10.3390/su13126898

Chicago/Turabian Style

Michel, Opelele O., Yu Ying, Fan Wenyi, Chen Chen, and Kachaka S. Kaiko. 2021. "Examining Land Use/Land Cover Change and Its Prediction Based on a Multilayer Perceptron Markov Approach in the Luki Biosphere Reserve, Democratic Republic of Congo" Sustainability 13, no. 12: 6898. https://doi.org/10.3390/su13126898

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