Automatic Detection for Cropland Destruction and Reclamation in Coal-Grain Composite Region Using Long-Term Landsat Imagery

IF 3.7 2区 农林科学 Q2 ENVIRONMENTAL SCIENCES Land Degradation & Development Pub Date : 2025-03-13 DOI:10.1002/ldr.5575
Kegui Jiang, Keming Yang, Mengting Gao, Xinyang Chen, Lishun Peng, Xinru Gu
{"title":"Automatic Detection for Cropland Destruction and Reclamation in Coal-Grain Composite Region Using Long-Term Landsat Imagery","authors":"Kegui Jiang,&nbsp;Keming Yang,&nbsp;Mengting Gao,&nbsp;Xinyang Chen,&nbsp;Lishun Peng,&nbsp;Xinru Gu","doi":"10.1002/ldr.5575","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The eastern plains of China are home to numerous “coal-grain composite regions,” where extensive underground coal mining has led to widespread land subsidence and cropland destruction, profoundly affecting regional ecological environments, agricultural production, and food security. This study proposes an automatic method for detecting cropland destruction and reclamation. The Normalized Difference Vegetation Index (NDVI) derived from long-term Landsat imagery was selected as the primary factor. First, by extracting a substantial number of NDVI samples from the mining areas, the threshold for cropland destruction due to mining disturbances was determined. Various types and scales of NDVI change templates were constructed based on the mechanisms of cropland disturbance. Subsequently, the Fast Dynamic Time Warping algorithm was employed to match the time-series curves and identify disturbance types, along with formulating detection rule for the year and magnitude of the cropland disturbance. Finally, patch indicators for disturbed croplands were established, and a random forest model was utilized to eliminate the disturbance noise induced by anthropogenic construction. The proposed method was applied to the Huaibei coal base, mapping cropland destruction and reclamation due to mining activities from 1987 to 2022, with overall accuracies of 0.85 and 0.81, respectively. This study revealed that the total area of cropland destroyed by mining activities amounted to 10179.71 ha during the monitoring period. From 1987 to 2005, the area of cropland destruction was small, accounting for 27.51% of the entire period. Between 2006 and 2018, the area of cropland destruction significantly increased, totaling 6102.01 ha and accounting for 59.94% of the entire period. The area of cropland destruction rapidly decreased and stabilized after 2018. Reclamation efforts began roughly in 1995, achieving a total reclaimed area of 2734.83 ha, with a reclamation rate of 26.86%. This study provides a crucial reference for monitoring the environmental impacts of mining and assessing the effectiveness of ecological restoration.</p>\n </div>","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"36 10","pages":"3439-3453"},"PeriodicalIF":3.7000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Land Degradation & Development","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ldr.5575","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The eastern plains of China are home to numerous “coal-grain composite regions,” where extensive underground coal mining has led to widespread land subsidence and cropland destruction, profoundly affecting regional ecological environments, agricultural production, and food security. This study proposes an automatic method for detecting cropland destruction and reclamation. The Normalized Difference Vegetation Index (NDVI) derived from long-term Landsat imagery was selected as the primary factor. First, by extracting a substantial number of NDVI samples from the mining areas, the threshold for cropland destruction due to mining disturbances was determined. Various types and scales of NDVI change templates were constructed based on the mechanisms of cropland disturbance. Subsequently, the Fast Dynamic Time Warping algorithm was employed to match the time-series curves and identify disturbance types, along with formulating detection rule for the year and magnitude of the cropland disturbance. Finally, patch indicators for disturbed croplands were established, and a random forest model was utilized to eliminate the disturbance noise induced by anthropogenic construction. The proposed method was applied to the Huaibei coal base, mapping cropland destruction and reclamation due to mining activities from 1987 to 2022, with overall accuracies of 0.85 and 0.81, respectively. This study revealed that the total area of cropland destroyed by mining activities amounted to 10179.71 ha during the monitoring period. From 1987 to 2005, the area of cropland destruction was small, accounting for 27.51% of the entire period. Between 2006 and 2018, the area of cropland destruction significantly increased, totaling 6102.01 ha and accounting for 59.94% of the entire period. The area of cropland destruction rapidly decreased and stabilized after 2018. Reclamation efforts began roughly in 1995, achieving a total reclaimed area of 2734.83 ha, with a reclamation rate of 26.86%. This study provides a crucial reference for monitoring the environmental impacts of mining and assessing the effectiveness of ecological restoration.

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
基于长期Landsat影像的煤粮复合区耕地破坏复垦自动检测
中国东部平原是众多“煤粮复合区”的所在地,在那里,大规模的地下煤矿开采导致了广泛的地面沉降和农田破坏,深刻影响了区域生态环境、农业生产和粮食安全。本研究提出了一种农田破坏与复垦的自动检测方法。选取长期Landsat影像的归一化植被指数(NDVI)作为主要因子。首先,通过从矿区提取大量的NDVI样本,确定了因采矿干扰而导致耕地破坏的阈值。基于耕地干扰机制,构建了不同类型和尺度的NDVI变化模板。随后,采用Fast Dynamic Time Warping算法对时间序列曲线进行匹配,识别干扰类型,并制定了耕地干扰年份和程度的检测规则。最后,建立受干扰农田的斑块指标,并利用随机森林模型消除人为建设引起的干扰噪声。将该方法应用于淮北煤炭基地,对1987 - 2022年采矿活动造成的耕地破坏和复垦进行了制图,总体精度分别为0.85和0.81。研究结果显示,在监测期间,因采矿活动而破坏的耕地总面积达10179.71公顷。1987 - 2005年耕地破坏面积较小,占整个时期的27.51%。2006 - 2018年,耕地破坏面积显著增加,累计6102.01公顷,占同期耕地破坏面积的59.94%。2018年以后,耕地破坏面积迅速减少并趋于稳定。大致于1995年开始填海,填海总面积2734.83公顷,填海率26.86%。该研究为矿山开采环境影响监测和生态恢复效果评价提供了重要参考。
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
Land Degradation & Development
Land Degradation & Development 农林科学-环境科学
CiteScore
7.70
自引率
8.50%
发文量
379
审稿时长
5.5 months
期刊介绍: Land Degradation & Development is an international journal which seeks to promote rational study of the recognition, monitoring, control and rehabilitation of degradation in terrestrial environments. The journal focuses on: - what land degradation is; - what causes land degradation; - the impacts of land degradation - the scale of land degradation; - the history, current status or future trends of land degradation; - avoidance, mitigation and control of land degradation; - remedial actions to rehabilitate or restore degraded land; - sustainable land management.
期刊最新文献
Can Conservation Tillage Practice Increase Maize Yields? Causal Evidence From Northeast China Spatiotemporal Analysis of Soil Salinity-Induced Land Degradation Using Remote Sensing Techniques Evaluating the Impacts of Human Activity and Climate on Vegetation Dynamics Using an Integrated Human Activity Index: A Case Study of China's Loess Plateau Extracellular Enzyme Stoichiometry Reveals Microbial Nutrient Limitation Under Construction Disturbance: A Case Study of the Wangbuqu Alpine Meadow in the Eastern Qinghai–Tibet Plateau Shifts in the Relationship Between Plant Species Diversity and Functional Diversity During Ecosystem Degradation Succession
×
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:604180095
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