Multi-Decadal Spatial and Temporal Forest Cover Change Analysis of Nkandla Natural Reserve, South Africa

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.

KEYWORDS:

• Natural Forest
• Remote Sensing
• Change Detection
• Sustainable
• Support Vector
• Modeling

Acknowledgments

The authors appreciate the support provided by Ms. Sharon Louw (Ecologist) of Ezemvelo KwaZulu-Natal Wildlife (EKZNW) in securing a permit to conduct the study in the Nkandla forest reserve. We thank Mr. Elliackim Zungu (Conservation Manager), Mr. Simon Makhaye, Mr. Sandebulawa Biyela, and other supporting staff of EKZNW for assisting in the field data collection. The authors also thank Mr. Charles Zungunde (University of KwaZulu-Natal) for driving the field team across the forest as well as assisting in data collection. We further thank the journal editors and reviewers for their efforts, time, and insights.

Disclosure statement

The authors declare no conflict of interest.

Data availability statement

The data for this research is available in the Mendeley data repository. It can be accessed by using the link; http://dx.doi.org/10.17632/rf6hj8kpx2.1

Supplementry data

Supplemental data can be accessed on the publisher’s website. 10.1080/10549811.2021.1891441 here.

Additional information

Funding

This research and study received a block grant from the South African System Analysis Centre (SASAC) through the National Research Foundation (NRF) of South Africa, with grant number 118770. The funders had no role in the study design, analysis, decision to publish, or preparation of the manuscript; National Research Foundation, South Africa [118770];