基于遥感手段监测矿区植被覆盖度变化

Monitoring of Vegetation Coverage Change of Mining Area Based on Remote Sensing

植被退化威胁着矿区的生态安全,能够反映出矿区环境的破坏程度,是环保领域的一个重要研究课题。及时有效地监测植被退化是加强植被保护、改善植被生态的基础。本研究首先采用景观功能分析法(LFA)作为衡量和监测生态系统功能优劣和恢复程度的方法,再根据研究区实测数据、对比实验区LFA指数数据,建立起区域植被退化的监测标准,同时应用主成分分析法(PCA)对光谱降维的精度进行了评价,然后利用多端元光谱混合分析法(MSESA)对陆地卫星影像进行了典型植被类型识别。该方法不仅使植被退化监测更加及时、便捷、有效,同时为其他相关研究提供了有价值的参考。

Vegetation degradation seriously reflects the scale of damage and threatens the ecological security in the mining area, which is a significant research topic in environment protection. Proper regional vegetation degradation monitoring is the basis of enhancing vegetation protection and improving vegetation ecology. In this study, Landscape Function Analysis(LFA) is adopted as a method of measuring and monitoring ecosystem function and rehabilitation progress. According to the measured data in study area, the control grazing experimental area data, regional vegetation degradation monitoring standard was established. Principal Component Analysis(PCA) was applied to evaluate the accuracy about spectral dimensionality reduction. From the Landsat images, the typical vegetation types were identified by multi endmember spectral mixture analysis(MSESA). This new method not only makes vegetation degradation monitoring more accurate, but also offers a valuable reference for other related research.