利用谷歌地球引擎和随机森林算法分析土地利用/土地覆盖变化及其对埃塞俄比亚上特凯泽盆地土地退化管理的影响。

Q2 Environmental Science
The Scientific World Journal Pub Date : 2024-07-30 eCollection Date: 2024-01-01 DOI:10.1155/2024/3937558
Alemu Eshetu Fentaw, Assefa Abegaz
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引用次数: 0

摘要

没有适当管理措施的土地利用和土地覆被变化(LULCC)已被确定为导致土地退化的主要因素,对生态系统服务和气候变化产生重大影响,进而影响人类生计。因此,不同空间尺度上最新、准确的 LULCC 数据和地图对于定期监测现有生态系统、合理规划自然资源管理以及促进区域可持续发展具有重要意义。本研究利用先进的遥感技术,如谷歌地球引擎(GEE)和随机森林(RF)算法,研究了埃塞俄比亚 Tekeze 河上游流域 31 年(1990-2021 年)间土地利用、土地覆被和土壤覆盖(LULC)的时空动态变化。使用了大地遥感卫星专题成像仪(TM)(1990 年、2000 年和 2010 年)和大地遥感卫星 8 业务陆地成像仪(OLI)传感器(2021 年)的大地遥感卫星表面反射率图像。此外,还利用辅助数据来改进 LULC 类别的分类。使用谷歌地球引擎(GEE)中的随机森林(RF)分类算法对 LULC 进行分类。OpenLand R 软件包用于绘制整个研究期间 LULC 的过渡和变化强度图。尽管研究区域的地形和气候特征十分复杂,但 RF 算法的准确度很高,总体准确度和 Kappa 值分别为 0.83 和 0.75。从 1990 年到 2021 年的土地利用、土地利用变化结果显示,森林、灌木林、灌木地和裸地分别减少了 12.2%、24.8%、1.2% 和 15.4%。裸地已变为农田、定居点、干河床和河道。从 1990 年到 2021 年,干涸河道和沙质地表不断扩大。灌木丛从 1900 年到 2010 年增加了 17.2%,但从 2010 年到 2021 年减少了 19.5%。在整个研究期间,水域、农田、干流河道和河床以及城市住区的净收益分别为 484%、8.7%、82% 和 26778.5%。然而,森林、灌木丛、灌木林和裸地分别减少了 12.17%、24.8%、1.2% 和 15.37%。观测到的变化显示了该流域现有的土地退化情况和未来的脆弱性,这一方面证明了通过避免未来将森林、灌木林和灌木地转化为农田,另一方面证明了通过在退化和脆弱地区推广可持续农田管理和植树造林做法,可以缓解土地退化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing Land Use/Land Cover Changes Using Google Earth Engine and Random Forest Algorithm and Their Implications to the Management of Land Degradation in the Upper Tekeze Basin, Ethiopia.

Land use and land cover change (LULCC) without appropriate management practices has been identified as a major factor contributing to land degradation, with significant impacts on ecosystem services and climate change and hence on human livelihoods. Therefore, up-to-date and accurate LULCC data and maps at different spatial scales are significant for regular monitoring of existing ecosystems, proper planning of natural resource management, and promotion of sustainable regional development. This study investigates the temporal and spatial dynamics of land use land cover (LULC) changes over 31 years (1990-2021) in the upper Tekeze River basin, Ethiopia, utilizing advanced remote sensing techniques such as Google Earth Engine (GEE) and the Random Forest (RF) algorithm. Landsat surface reflectance images from Landsat Thematic Mapper (TM) (1990, 2000, and 2010) and Landsat 8 Operational land imager (OLI) sensors (2021) were used. Besides, auxiliary data were utilized to improve the classification of LULC classes. LULC was classified using the Random Forest (RF) classification algorithm in the Google Earth Engine (GEE). The OpenLand R package was used to map the LULC transition and intensity of changes across the study period. Despite the complexity of the topographic and climatic features of the study area, the RF algorithm achieved high accuracy with 0.83 and 0.75 overall accuracy and Kappa values, respectively. The LULC change results from 1990 to 2021 showed that forest, bushland, shrubland, and bareland decreased by 12.2, 24.8, 1.2, and 15.4%, respectively. Bareland has changed to farmland, settlement, and dry riverbed and stream channels. Expansion of dry stream channels and sandy land surfaces has been observed from 1990 to 2021. Bushland has shown an increment by 17.2% from 1900 to 2010 but decreased by 19.5% from 2010 to 2021. Throughout the study period, water, farmland, dry stream channels and riverbeds, and urban settlements showed positive net gains of 484, 8.7, 82, and 26778.5%, respectively. However, forest, bush, shrub, and bareland experienced 12.17, 24.8, 1.2, and 15.37% losses. The observed changes showed the existing land degradation and the future vulnerability of the basin which would serve as an evidence to mitigate land degradation by avoiding the future conversion of forest, bushland, and shrubland to farmland, on the one hand, and by scaling up sustainable farmland management, and afforestation practices on degraded and vulnerable areas, on the other hand.

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来源期刊
The Scientific World Journal
The Scientific World Journal 综合性期刊-综合性期刊
CiteScore
5.60
自引率
0.00%
发文量
170
审稿时长
3.7 months
期刊介绍: The Scientific World Journal is a peer-reviewed, Open Access journal that publishes original research, reviews, and clinical studies covering a wide range of subjects in science, technology, and medicine. The journal is divided into 81 subject areas.
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