Oil and Gas Anomaly Extraction by Combining Hyperspectral Image Data with Multispectral Image Data
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摘要: 为了在缺少地面实测数据的情况下对遥感油气异常结果进行验证, 利用多光谱遥感数据和高光谱遥感数据对同一地区进行油气异常解译, 针对同一位置使用两种不同数据的异常结果进行相互验证.并提出了利用高光谱异常提取结果作为先验知识的多光谱异常主分量阈值确定方法, 将该方法与传统主分量阈值方法提取的异常结果, 分别与高光谱提取出的粘土异常区域结果进行重叠率计算, 发现该方法提取出的异常区与高光谱提取的结果重叠率达98.808%, 高于传统主分量阈值方法的98.198%.结果表明利用该方法确定的阈值划分出的异常区具有较高的精度.Abstract: In order to verify the anomalies without any field survey data in remote sensing image caused by hydrocarbon micro seepage phenomenon, the multispectral image and hyperspectral image anomaly interpretation results are used to verify each other in this paper. A new method to confirm the multispectral principal component aberrant threshold value by counting the multispectral pixel value located in the hyperspectral anomaly area is proposed. The overlap rate between the multispectral image anomalies divided by the new method and the hyperspectral image anomay area is computed at 98.808%, higher than the traditional principal component threshold technology.
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图 2 SASI影像大气校正前后植被覆盖地区光谱曲线对比
三条竖线分别代表植被的三个光谱特征位置
Fig. 2. The comparison of the SASI image spectral curves in the area of vegetation cover before & after the process of atmospheric correction
图 5 SASI影像各蚀变矿物异常解译叠加
Fig. 5. The overlay of SASI image with the different alteration mineral anomaly interpretations
图 6 ASTER影像各蚀变矿物异常解译叠加
Fig. 6. The image of overlay the different alteration mineral anomaly interpretations of the ASTER image
图 7 SASI粘土异常提取结果与ASTER粘土异常叠加
Fig. 7. The anomaly results of the clay minerals in the SASI and the ASTER
图 8 高光谱粘土异常范围内多光谱异常主分量像元直方图
Fig. 8. The histogram of the ASTER image clay anomaly principal components which located in the area of hyperspectral clay anomaly
图 9 两种不同异常阈值确定方法提取出的粘土异常区对比
Fig. 9. The comparison chart of the two clay anomaly area which extracted by two different methods
表 1 ASTER文件信息参数
Table 1. The parameters information of the ASTER image
波段 增益 偏差 波长(μm) 波谱Max值(μm) 波谱Min值(μm) 中心波长半极值宽度(μm) 1 0.676 0 -0.676 0 0.556 0 0.600 0.520 0.080 2 0.708 0 -0.708 0 0.661 0 0.690 0.630 0.080 3 0.862 0 -0.862 0 0.807 0 0.860 0.780 0.080 4 0.217 4 -0.217 4 1.656 0 1.700 1.600 0.100 5 0.069 6 -0.069 6 2.167 0 2.185 2.145 0.040 6 0.062 5 -0.062 5 2.209 0 2.225 2.185 0.040 7 0.059 7 -0.059 7 2.262 0 2.285 2.235 0.050 8 0.041 7 -0.041 7 2.336 0 2.365 2.295 0.070 9 0.031 8 -0.031 8 2.400 0 2.430 2.360 0.070 
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