摘要
针对植被覆盖区遥感技术在矿产勘查中的实际问题,提出了一种利用金属元素迁移规律和金属胁迫后植被光谱发生变异的特点开展植被覆盖区地质找矿的遥感新方法。该方法基于植被叶片光谱曲线反射和吸收特征的原理,结合地球化学数据,间接实现重金属元素分布遥感制图。采集矿区和矿区周围背景区乌毛蕨叶样本及对应光谱数据,基于化学分析测定获得矿区和背景区乌毛蕨叶钼元素含量,明确矿区乌毛蕨叶受到了钼元素影响。对比分析矿区和背景区乌毛蕨叶在波形、红边位置、叶绿素及水吸收、植被指数上的差异,结果表明,受钼金属胁迫后矿区乌毛蕨叶光谱在光谱曲线和水吸收特征方面较背景区均存在明显差异,其中970 nm处的水吸收特征差异最明显。研究成果可为遥感技术在植被覆盖区开展地质找矿提供新思路。
In response to the remote sensing technology problems in mineral exploration in vegetation-covered areas,the authors proposed a new method of geological prospecting using remote sensing,taking advantage of the migration rules of metal elements and the spectral variation caused by metal stress on vegetation.The method is based on the principle of reflectance and absorption characteristics of leaf spectra of ferns,combined with geochemical data,to indirectly achieve remote sensing mapping of heavy metal element distribution.Silky fern samples and the corresponding spectral data were collected from the deposit area and the surrounding background area to determine molybdenum element content in silky fern leaves by chemical analysis.The silky fern leaves were confirmed to be affected by molybdenum elements,and the differences between silky fern leaves in the deposit area and those in the background area in terms of waveform,red edge position,chlorophyll and water absorption,and vegetation index were compared and analyzed.The results show that the fern leaves affected by molybdenum metal stress in the deposit area have obvious differences in spectral curves and absorption characteristics compared with those in the background area,especially at 970 nm water absorption feature.The research results could provide new ideas for the application of remote sensing technology in geological prospecting in vegetation-covered areas.
作者
史超
李书
王学平
SHI Chao;LI Shu;WANG Xueping(Changjiang Reconnaissance Technology Research Institute,Ministry of Water Resources,Hubei Wuhan 430011,China;Faculty of Earth Resources,China University of Geosciences,Hubei Wuhan 430074,China)
出处
《中国地质调查》
CAS
2024年第5期112-119,共8页
Geological Survey of China
基金
水利部重大科技项目“三峡库区河流湿地“碳汇”潜力评价研究(编号:SKS-2022082)”
长江设计集团自主创新项目“基于机器学习的膨胀土边坡稳定性预测评价研究(编号:CX2023Z34-1)”联合资助。
关键词
矾山铜钼矿区
高光谱遥感
钼金属胁迫
乌毛蕨叶光谱特征
地质找矿
Fanshan copper-molybdenum deposit area
hyperspectral remote sensing
molybdenum metal stress
silky fern leaves spectral characteristics
geological prospecting
