叶面降尘遥感监测是评估矿山粉尘污染状况的重要手段之一,与自然粉尘相比,重金属富集的矿山粉尘对人类健康和植被生长造成更严重的威胁。以往叶面降尘遥感监测大多针对降尘量进行反演、监测,而没有研究矿区粉尘与自然粉尘的差异。本文使用哨兵2号数据,以内蒙古甲乌拉—查干铅锌银矿区为例,在分析叶面降尘的光谱响应特征基础上,基于面向对象的主成分分析(FPCS)方法,提取研究区叶面降尘范围和强度,利用尘源光谱指数,区分矿山粉尘与自然粉尘,并分析了叶面降尘类型、强度与矿山地物分布的相关性,分析研究区主要矿山尘源及扬尘扩散特征,利用端元分解模型和光谱特征匹配(SFF)分析矿山开发降尘和自然降尘的矿物成分差异和光谱特征。结果表明叶面降尘导致植被可见光波段反射率升高、近红外波段反射率降低、植被红边“蓝移”,远离粉尘源方向,可见光波段反射率逐渐降低,红边位置逐渐向长波方向移动；矿山尘源与自然尘源光谱特征存在差异,矿山尘源叶面降尘像元在865nm处显示反射率吸收特征,SFF结果显示该吸收特征与黄铁矿相关； FPCS成功提取了叶面降尘的范围和强度,尘源光谱指数(DSI)能区分矿山降尘与自然降尘,提取的矿山叶面降尘像元与矿山地物空间相关性强,研究区主要矿山尘源为废石堆和矿山道路,其中废石堆扬尘扩散强度和距离大于矿山道路。该研究可为矿山开发粉尘污染快速评估提供一种技术思路。

Remote sensing monitoring of foliar dust is one of the important methods to assess mine dust pollution. Comparing with natural dust, mine dust, enriched with heavy metals, poses a more serious threat to human health and vegetation growth. Recently, most of foliar dust monitoring carried out inversion and monitoring for the amount of foliar dust, without trying to distinguish between mine dust and natural dust in mining areas. In this paper, methods were proposed to extract foliar dust information and to identify dust source, taking the Jiawula-Chagan Pb-Zn-Ag mining area in Inner Mongolia as an example. The objectives of this study are (1) to analyze the spectral response characteristics of foliar dust fall for sentinel-2 data, (2) to extract the distribution and intensity of foliar dust, using the object-oriented principal component analysis (FPCS) method, (3) to propose a spectral index of dust sources based on the reflectance differences between mine foliar dust and natural foliar dust, distinguishing extracted foliar dust information between mine dust and natural dust, (4) to analyze the correlation between the dust source type, intensity of foliar dust and the distribution of mine objects, assessing the main mine dust sources and their dust diffusion characteristics, and (5) to analyze mineral composition and spectral characteristics difference between natural dust and mine dust, using member-decomposition model and spectral feature matching (SFF) method. Results showed that the foliar dust increased the reflectance of visible regions, decreased reflectance of near infrared regions, shifted the red edge of the vegetation to shorter wavelength direction. the spectral reflectance gradually decreases with the increase of distances away from dust sources. Mine dust sources and the affecting vegetation showed reflectance absorption characteristics at 865nm, attributing to pyrite oxidation from SFF results. The distribution and intensity of foliar dust were extracted by FPCS successfully. The dust source spectrum index could distinguish mine dust fall from natural dust fall. The extracted mine foliar dust pixels had a strong spatial correlation with the mine objects. The main mine dust sources in the study area were mine dumps and mine roads, and the dust diffusion intensity of mine dumps are greater. This research provided a method for the rapid assessment of dust pollution in mine areas.