Major land-use/land-cover change due to rapid urbanization has been known to increase the land-surface temperature around the world. Consequently, examining the variation of land-surface temperatures and mitigating the related impacts remain a challenge. The present study employed remote-sensing and geoinformational techniques to examine land-use/land-cover change and its effects on land-surface temperature variations in the villages within the Luki Biosphere Reserve, Democratic Republic of Congo. Land-use/land-cover change for the year 2038 was predicted by using the CA–Markov chain. Additionally, focus-group discussions (FGDs) with local communities from different villages were applied to better understand the impact of climate change, considering the increase of land-surface temperature. The results revealed major changes in land-use/land-cover in the four villages from 2002 to 2020, principally the expansion of fallow land and built-up areas, as well as the decline in forest land, and the complex of young secondary and degraded forest. There was an increase in mean LST values over all villages between 2002 and 2020. The highest value was observed in Tsumba kituti (25.12 °C), followed by Kisavu (24.87 °C), Kibuya (23.31 °C) and Kiobo (21.82 °C). Between 2002 and 2020, the mean LST of built-up areas increased from 23.18 to 25.12 °C, 21.55 to 23.38 °C, 21.4 to 25.78 °C and 22.31 to 25.62 °C in Tsumba kituti, Kiobo, Kisavu and Kibuya, respectively. Moreover, the mean LST of fallow land increased from 20.8 to 23.2 °C, 21.13 to 22.12 °C, 21.89 to 23.12 °C and 20.31 to 23.47 °C in Tsumba, Kiobo, Kibuya and Kisavu, respectively. This indicates that built-up and fallow land experienced the highest land-surface temperature compared to other land-use/land-cover categories. Meanwhile, the conversion of all land-use/land-cover categories into built-up areas in all the villages resulted in the increase of the land-surface temperature. FGDs results recognize the recurrent land-use/land-cover change as the major driver of the increase in LST (86%). However, it was predicted that farmland and built-up area will still increase within all the villages, while the forest land will decline. As for the complex of secondary and degraded forest, it will decrease in Tsumba kituti, while, in Kiobo and Kisavu, it is expected to increase. Through a combination of remote-sensing and primary data, this study provides accurate information that will benefit decision-makers to implement appropriate landscape-planning techniques to mitigate the effect of the increased land-surface temperature in the villages.
Analysis of the impact of Land use/Land cover change on Land Surface Temperature with Remote Sensing
