Spatiotemporal trends and drivers of forest cover change in Metekel Zone forest areas, Northwest Ethiopia

IF 2.9 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Environmental Monitoring and Assessment Pub Date : 2024-11-06 DOI:10.1007/s10661-024-13294-7
Tamiru Toga Wahelo, Daniel Ayalew Mengistu, Tadesse Melesse Merawi
{"title":"Spatiotemporal trends and drivers of forest cover change in Metekel Zone forest areas, Northwest Ethiopia","authors":"Tamiru Toga Wahelo,&nbsp;Daniel Ayalew Mengistu,&nbsp;Tadesse Melesse Merawi","doi":"10.1007/s10661-024-13294-7","DOIUrl":null,"url":null,"abstract":"<div><p>The spatiotemporal dynamics of forest cover are essential for understanding the patterns and processes of forest change over time and space. This research focused on the spatiotemporal trends and drivers of forest cover change in the Metekel Zone of Northwest Ethiopia. Landsat 5, Landsat 7, and Landsat 8 imagery, covering the period from 1986 to 2019, were used for land use/cover classification. Land use/cover classification was performed using random forest (RF) and support vector machine (SVM) algorithms in the Google Earth Engine (GEE) platform, with training samples obtained through visual image interpretation. Spectral indices, such as the normalized difference vegetation index, soil-adjusted vegetation index, leaf area index, and normalized difference water index, were analyzed to examine forest cover dynamics over time. In addition, key informant interviews (KIIs) and focus group discussions (FGDs) were conducted. Findings revealed that forest cover decreased significantly from 51.37% in 1986 to 17.20% in 2019, driven largely by human activities such as agricultural expansion, increased demand for firewood, and urban expansion. Findings from spectral indices further corroborated the finding that forest cover in the study region (mainly in the southwestern part) substantially decreased from 1986 to 2019. Concerning forest depletion, the lack of local community awareness has become a key challenge. This problem is attributed to communities prioritizing immediate needs such as fuel and land for agriculture over long-term forest conservation. To combat ongoing deforestation, the Metekel Zone Administration, in collaboration with the land administration office and other stakeholders, revisited and strengthened existing forest policies and control systems. It is also suggested that community awareness, chiefly among youth, should be enhanced through the strategic expansion of formal and nonformal educational initiatives, which empower the youth as agents of change and promote the dissemination of knowledge throughout the community.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"196 12","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-024-13294-7.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Monitoring and Assessment","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10661-024-13294-7","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The spatiotemporal dynamics of forest cover are essential for understanding the patterns and processes of forest change over time and space. This research focused on the spatiotemporal trends and drivers of forest cover change in the Metekel Zone of Northwest Ethiopia. Landsat 5, Landsat 7, and Landsat 8 imagery, covering the period from 1986 to 2019, were used for land use/cover classification. Land use/cover classification was performed using random forest (RF) and support vector machine (SVM) algorithms in the Google Earth Engine (GEE) platform, with training samples obtained through visual image interpretation. Spectral indices, such as the normalized difference vegetation index, soil-adjusted vegetation index, leaf area index, and normalized difference water index, were analyzed to examine forest cover dynamics over time. In addition, key informant interviews (KIIs) and focus group discussions (FGDs) were conducted. Findings revealed that forest cover decreased significantly from 51.37% in 1986 to 17.20% in 2019, driven largely by human activities such as agricultural expansion, increased demand for firewood, and urban expansion. Findings from spectral indices further corroborated the finding that forest cover in the study region (mainly in the southwestern part) substantially decreased from 1986 to 2019. Concerning forest depletion, the lack of local community awareness has become a key challenge. This problem is attributed to communities prioritizing immediate needs such as fuel and land for agriculture over long-term forest conservation. To combat ongoing deforestation, the Metekel Zone Administration, in collaboration with the land administration office and other stakeholders, revisited and strengthened existing forest policies and control systems. It is also suggested that community awareness, chiefly among youth, should be enhanced through the strategic expansion of formal and nonformal educational initiatives, which empower the youth as agents of change and promote the dissemination of knowledge throughout the community.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
埃塞俄比亚西北部梅特克尔区林区森林植被变化的时空趋势和驱动因素。
森林植被的时空动态对于了解森林随时间和空间变化的模式和过程至关重要。本研究重点关注埃塞俄比亚西北部梅特克尔区森林植被变化的时空趋势和驱动因素。研究使用了覆盖 1986 年至 2019 年的 Landsat 5、Landsat 7 和 Landsat 8 图像进行土地利用/覆盖分类。在谷歌地球引擎(GEE)平台上使用随机森林(RF)和支持向量机(SVM)算法进行土地利用/覆盖分类,训练样本通过视觉图像判读获得。分析了归一化差异植被指数、土壤调整植被指数、叶面积指数和归一化差异水分指数等光谱指数,以研究森林植被随时间变化的动态。此外,还进行了关键信息提供者访谈(KII)和焦点小组讨论(FGD)。研究结果显示,森林覆盖率从 1986 年的 51.37% 大幅下降到 2019 年的 17.20%,这主要是受农业扩张、木柴需求增加和城市扩张等人类活动的影响。光谱指数的结果进一步证实了研究区域(主要在西南部)的森林覆盖率从 1986 年到 2019 年大幅下降的结论。关于森林枯竭,当地社区缺乏认识已成为一个主要挑战。造成这一问题的原因是社区优先考虑燃料和农业用地等眼前需求,而不是长期的森林保护。为了遏制持续的森林砍伐,梅特凯尔区政府与土地管理办公室和其他利益相关者合作,重新审视并加强了现有的森林政策和控制系统。此外,还建议通过战略性地扩大正规和非正规教育举措,提高社区(主要是青年)的认识,增强青年作为变革推动者的能力,并促进知识在整个社区的传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Environmental Monitoring and Assessment
Environmental Monitoring and Assessment 环境科学-环境科学
CiteScore
4.70
自引率
6.70%
发文量
1000
审稿时长
7.3 months
期刊介绍: Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.
期刊最新文献
Characterization of atmospheric microplastics: A case study in Shenzhen City, a southern coastal area of China Beebread pollen composition is affected by seasonality and landscape structure Advancing food security through drone-based hyperspectral imaging: applications in precision agriculture and post-harvest management Assessment of polycyclic aromatic hydrocarbons (PAHs) and heavy metal contamination in Shitalakshya River water: ecological and health risk implications Assessing forest fire likelihood and identification of fire risk zones using maximum entropy-based model in Khyber Pakhtunkhwa, Pakistan
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1