首页> 外文期刊>International journal of applied earth observation and geoinformation >Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data
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Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data

机译:使用ASTER VNIR / SWIR数据进行区域规模的矿物制图,并使用机载高光谱CASI / SASI数据验证反射率和矿物图产品

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ASTER data have been widely and successfully used in lithological mapping and mineral exploration for decades. The errors due to atmospheric water vapor and the characteristics of the photoelectric sensor could lead to the anomalous characteristics of band 5 and 9 in the ASTER standard reflectivity product. These anomalies could result in the spectroscopic misidentification of minerals. This study proposed a simple method of atmospheric correction for converting radiance-at-sensor to ground reflectance. The ASTER VNIR/SWIR reflectance correction factor was derived to correct the spectral shape bias resulting from the radiometric calibration error using airborne hyperspectral CASLSASI data. The ASTER VNIR/SWIR reflectance correction factor was derived to correct the spectral shape bias resulting from the radiometric calibration error. After applying the reflectance factor to the atmospheric-corrected ASTER L1B data, a band combination mapping method was proposed for identifying minerals more quickly and accurately. The results indicate that this method for atmospheric correction of ASTER data produces very good results in the arid and bare areas. It is still unknown whether the method is suitable for humid and rainy areas where atmospheric water vapor varies spatially more than in arid and bare areas. After applying the reflectance factor to the atmospheric-corrected ASTER L1B data, the mean error of all reflectance bands decreased from 0.0256 to 0.002, and the standard deviation decreased from 0.04251 to 0.0007. The errors of the 2/1,5/6 and 9/8 band ratios decreased from 2.38%, 4.102%, and 4.28% to 1.26%, -0.162%, and 0.31%, respectively. The radiometric calibration error of the ASTER band 1-9 data can lead to the overestimation of kaolinite. A band index of 2/1 for retrieving Fe3+ cannot produce a reliable Fe3+ distribution map, and a new index should be developed.
机译:几十年来,ASTER数据已被广泛成功地用于岩性制图和矿物勘探。由大气水蒸气和光电传感器的特性引起的误差可能会导致ASTER标准反射率产品中的波段5和9出现异常特性。这些异常可能导致矿物光谱错误识别。这项研究提出了一种简单的大气校正方法,可将传感器的辐射率转换为地面反射率。利用机载高光谱CASLSASI数据推导出ASTER VNIR / SWIR反射率校正因子,以校正由辐射定标误差引起的光谱形状偏差。推导了ASTER VNIR / SWIR反射率校正因子,以校正由辐射校准误差引起的光谱形状偏差。将反射系数应用于大气校正的ASTER L1B数据后,提出了一种波段组合映射方法,可以更快,更准确地识别矿物。结果表明,这种用于大气校正ASTER数据的方法在干旱和裸露的地区产生了很好的结果。尚不知道该方法是否适用于潮湿和多雨的地区,在这些地区,大气水蒸气的空间变化比干旱和裸露的空间大。将反射系数应用于大气校正的ASTER L1B数据后,所有反射带的平均误差从0.0256降低至0.002,标准偏差从0.04251降低至0.0007。 2 / 1,5 / 6和9/8波段比率的误差分别从2.38%,4.102%和4.28%降低到1.26%,-0.162%和0.31%。 ASTER 1-9波段数据的辐射校准误差会导致高岭石的高估。用于检索Fe3 +的带指数2/1不能产生可靠的Fe3 +分布图,应开发新的指数。

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