摘要
红边指数对植被叶绿素浓度、叶表面冠层、叶聚丛和冠层结构敏感。研究采矿胁迫下红边指数的响应规律,可为沉陷区植被损伤诊断、植被自然恢复和人工修复效果评估提供生态学指标。以黄河流域鄂尔多斯市泊江海子矿113101首采工作面为例,结合Sentinel-1A数据D InSAR技术获得的形变场,同步选取2016年10月至2017年10月间11期带有红边波段的Sentinel-2A多时相遥感数据,利用归一化植被指数(NDVI)和5种典型红边植被指数(NDVIre,NDre,MCARI,TCI,MSRre),同步分析沉陷区植被指数的时空变化规律。结果表明:①一个生命周期的植被指数呈GAUSS单峰变化,研究区4月进入返青期,8月达到峰值,10月进入衰退期。②沉陷区6种植被指数线性回归斜率都小于对照区,沉陷区植被的增长速度慢于非沉陷区。③受沉陷扰动的影响,沉陷区植被指数的增量都小于非沉陷区,6种植被指数平均降幅达18.8%~32.8%。④二元Logistic回归显示,除MCARI,TCI以外的4种植被指数在植被生长期的4,5,6,8月份与采矿活动相关或显著相关(显著性水平P为0.001~0.100)。在生长季,采矿活动对工作面上方的植被指数有显著影响。基于红边波段组合的植被指数能敏感反映采矿胁迫下植被生长状况的细微变化,可以作为黄河流域黄土—风积沙矿区植被损伤诊断及生态环境评价的优势指标。
Red Edge Vegetation Index(VIre)is sensitive to chlorophyll concentration,leaf surface canopy,leaf cluster and canopy structure.The research on the response characteristics of VIre under mining stress can provide quantitative ecological indicators for vegetation damage diagnosis,natural vegetation restoration and artificial reclamation effectiveness evaluation in mining subsidence area.Taking the first mining face(No.113101)of Bojianghaizi Mine in Ordos City along the upper and middle Yellow River Basin as research instance,the mining-induced deformation field was obtained by DInSAR technology using Sentinel-1A SAR remotely sensed data,meanwhile,based on the traditional vegetation index,the red edge band was introduced to improve the existing vegetation index,the spatiotemporal variation of the vegetation indices in subsidence was analyzed with the help of normalized difference vegetation index(NDVI)and 5 typical VIre:NDVIre(Red Edge Normalized Difference Vegetation Index),NDre(Normalized Difference Red Edge),MCARI(Modified Chlorophyll Absorption in Reflectance Index),TCI(Triangular Chlorophyll Index),MSRre(Modified Red Edge Simple Ratio)-inversed from 11 periods of Sentinel-2A multi-temporal remote sensing data from October 2016 to October 2017.The results showed that①the vegetation indices within a life cycle exhibit a single peak change of GAUSS.In this research area,the starting date of growing season(SOS)is in April,the peak is in August,and the ending date of the season(EOS)is in October.②The linear regression of 6 vegetation indices in subsidence area is smaller than that in check area(CK),which indicates that the growth rate of vegetation in subsidence area is slower than that in non-subsidence area.③By studying the decline of subsidence area relative to non-subsidence area,it is found that affected by the subsidence disturbance,the increment of vegetation indices(δVIs)in the subsidence area is smaller than that in the non-subsidence area,and the average decrease of 6 vegetation indices is 18.8%-32.8%.The fitting effect of TCI is the best(R2=0.9821).It further shows that the vegetation growth speed above the subsidence area is slower due to mining,and the red edge index is more sensitive to the vegetation growth in the mining subsidence area.④Binary logistic regression shows that 4 vegetation indices(except for MCARI and TCI)are significantly correlated with coal mining activities in April,May,June and August(Significant level 0.001-0.100).However,in August,the 6 vegetation indices are significantly correlated(Significant level 0.001-0.026),and the significance level of TCI model is the highest.In the peak season of vegetation growth,coal mining activities have a significant impact on vegetation index above the working face.The vegetation indices based on red edge band combination can sensitively reflect the subtle changes of vegetation growth under mining stress,and can be used as the dominant indicators for the vegetation damage diagnosis and eco-environmental assessment of loess-aeolian coal mine in the Yellow River Basin.
作者
李晓婷
杨丽帆
邹友峰
马超
LI Xiaoting;YANG Lifan;ZOU Youfeng;MA Chao(College of Surveying & Land Information Engineering,Henan Polytechnic University,Jiaozuo 454003,China;School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,China;Key Laboratory of Spatio-temporal Information and Ecological Restoration of Mines (Ministry of Natural Resources,MNR),Henan Polytechnic University,Jiaozuo 454003,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2021年第5期1508-1520,共13页
Journal of China Coal Society
基金
国家自然科学基金项目重点资助项目(U1261206)
国家自然基金委与英国皇家学会合作资助项目(4191101440)。
