International Journal of Research and Scientific Innovation (IJRSI) |Volume IX, Issue XII, December 2022|ISSN 2321-2705
NDOH MBUE Innocent1,*, Elvis Kah2
1Energy, Materials, Modeling & Methods Laboratory (E3M); National Higher Polytechnic School of Douala (NHPSD), University of Douala, Cameroon, 2701, Cameroon
2School of geology and mining engineering (EGEM), University of Ngaoundere, Cameroon
*Corresponding Author
Abstract. The goals of this study were to use remote sensing and a Geographic Information System to track land use and cover change in Cameroon’s Bamenda highlands and to assess the effects of these changes on the local ecosystem. Supervised classification using the maximum likelihood classification algorithm was used to extract information from Landsat time series images from 2000 to 2018. The classification was relatively acceptable and effective in detecting land-use changes in the area. Between 2000 and 2010, farmland increased by 10.29%, and by 2018, it had increased by 14.39%. Similarly, plantations expanded by 15.07 km2 (4.1%) between 2000 and 2010, reaching 20.51 km2 (5.58%) by 2018, while built-up areas increased by 0.51% between 2000 and 2010, reaching 1.43% by 2018. These increases came at the expense of forest, savannah, and waterbodies, which were reduced by 3.93%, 10.33%, and 17.17%, respectively. Savannah had a strong negative correlation with a built-up area (R2 = 1), and plantation area (R2 = .98). As a consequence, the increase of built-up areas and plantation farms could be at the cost of the reduction in savannah and forestlands. On the whole, increased deforestation, growth in plantations, built-ups, and farmlands, have had an impact on the area’s ecosystem structure and functions. The findings are critical for developing environmental management policies and ecological integrity of the area. Water, energy, food security, climate mitigation, and agroecological sustainability policies, as well as their synergies and tradeoffs in the context of sustainable development goals, are important research areas.
Keywords: Bamenda highlands; land use/cover change; remote sensing; maximum likelihood classification; Landsat time-series imageries; Geographic Information System
I. INTRODUCTION
Humanity is at a crossroads. It has entered a new geological epoch, the Anthropocene, where man constitutes the largest driver of environmental change on Earth. Man has crossed several planetary earth boundaries that govern the system’s stability [1], and thus its ability to provide essential support functions, fundamental conditions for good and healthy lives, and, ultimately, a stable state of the planet. The negative consequences of changing land use and land cover are enormous, including climate change [2, 3], changes in the hydrological cycle, and global environmental degradation risks [4]. The livelihoods of rural people are inextricably linked to the landscapes in which they live, and they are especially vulnerable to changes in these landscapes [5]. Land cover