遥感分析刚果民主共和国上加丹加省Likasi镇城市化在土地利用和土地覆盖变化中的作用

Matthieu M. Tshanga, Pierre T. Mashala, Faidance Mashauri
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引用次数: 0

摘要

环境变化的特点是主要由人类活动和自然生态过程引起的环境变化。考虑到刚果民主共和国上加丹加省南部是非洲铜带的一部分,几十年来一直是一个密集采矿的地区,人类以各种方式影响了自然环境:如人口过剩、郊区化、浪费、森林砍伐。因此,重要的是跟踪和控制该地区采矿活动的变化。本研究旨在利用遥感技术分析这些变化。对2002年和2022年的Landsat卫星图像进行了处理和分类,以量化20年间建成区、农业用地和植被覆盖的变化。分类结果显示两个时间点之间存在较大差异,2002 - 2022年,利卡西地区建设用地明显扩大,农业用地和植被覆盖明显减少。这些发现提供了证据,表明城市增长已经改变了利卡西的景观,可能是以牺牲农田和生态系统为代价的。对遥感数据的进一步分析可以量化变化并模拟未来趋势,以支持可持续土地利用规划。利用ERDAS 16.6.13软件,利用2002年和2022年两个不同年份的LANDSAT数据进行土地覆盖和土地利用分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Remote Sensing to Analyse the Role of Urbanization in the Transformation of Land-Use and Land Cover in Likasi Town (Haut-Katanga, DR Congo)
Environmental change is characterized as an alteration in the environment caused primarily by human activities and ecological processes that are natural. Given the fact that the southern part of the province of Haut-Katanga in the Democratic Republic of the Congo (DRC) is part of the African Copperbelt and has been a region of intense mining for decades, humans have affected the physical environment in various ways: such as overpopulation, suburbanization, wastage, deforestation. It is therefore important to track and control the changes in the area’s mining activities. This study aimed to analyze these changes using remote sensing techniques. Landsat satellite images from 2002 and 2022 were processed and classified to quantify changes in built-up area, agricultural land, and vegetation cover over the 20-year period. The classification results revealed sizable differences between the two time points, indicating considerable expansion of built-up land and declines in agricultural land and vegetation cover from 2002 to 2022 in Likasi. These findings provide evidence that urban growth has transformed the landscape in Likasi, likely at the expense of farmland and ecosystems. Further analysis of the remote sensing data could quantify the changes and model future trends to support sustainable land use planning. The land cover and land use analysis were performed with the assistance of the ERDAS 16.6.13 software by mapping LANDSAT data from two different years 2002 and 2022.
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