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Gyamfi-Ampadu, E., Gebreslasie, M., & Mendoza Ponce, A. 
ORCID: https://orcid.org/0000-0002-9069-0652
(2021).
Multi-Decadal Spatial and Temporal Forest Cover Change Analysis of Nkandla Natural Reserve, South Africa.
Journal of Sustainable Forestry 1-24. 10.1080/10549811.2021.1891441.
Abstract
Forest cover change analyses have an essential role in forest management. Thus, this study adopted Landsat satellite imagery to assess the decadal spatiotemporal forest cover changes that occurred between 1989 and 2019 and predicted the 2029 land cover distribution of the Nkandla forest reserve, facing encroachment threats. The support vector machine algorithm and Land Change Modeling were utilized to classify and detect changes that occurred between 1989–1999, 1999–2009, 2009–2019. The Markov Chain Model and Multi-Layer Perceptron were adopted for the future land cover prediction. Consistent changes through inter-transitioning between the land cover types (closed canopy forest, open canopy forest, grassland, and bare sites) were detected. The closed canopy forest increased from 883.46 ha to 1059.23 ha, whereas the open canopy forest declined from 1091.89 ha to 910.60 ha between 1989 and 2019. Generally, the observed changes were caused by ecological processes and human disturbances. The future cover prediction indicated that the closed canopy forest will decline between 2019 and 2029, whereas the open canopy forest, grassland, and bare sites will increase. The information provided through this study will support the management of the Nkandla forest to ensure its continual supply of ecosystem services of national and global importance.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Natural Forest, Remote Sensing, Change Detection, Sustainable, Support Vector, Modeling |
| Research Programs: | Biodiversity and Natural Resources (BNR) Biodiversity and Natural Resources (BNR) > Agriculture, Forestry, and Ecosystem Services (AFE) |
| Depositing User: | Luke Kirwan |
| Date Deposited: | 29 Mar 2022 14:03 |
| Last Modified: | 18 Oct 2022 11:16 |
| URI: | https://pure.iiasa.ac.at/17928 |
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