利用卫星和航空高光谱成像检测太阳能光伏电站

Remote. Sens. Pub Date : 2023-07-05 DOI:10.3390/rs15133403
Christoph Jörges, Hedwig Sophie Vidal, T. Hank, H. Bach
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引用次数: 0

摘要

太阳能光伏板作为一种可再生能源技术,在减少温室气体排放方面具有巨大的潜力。近年来,太阳能光伏的数量显著增加,预计还会进一步增加。因此,利用遥感方法对光伏组件进行精确的全球测绘和监测,对于预测能源生产潜力、揭示社会经济驱动因素、支持城市规划和评估生态影响具有重要意义。根据光伏组件的物理吸收和反射特性,高光谱图像为识别光伏组件提供了关键信息。本文首次研究了30 m低分辨率的星载PRISMA数据和5.3 m中分辨率的机载AVIRIS-NG数据的光谱特征,用于太阳能光伏探测。研究区域位于德国南部的伊尔巴赫附近。利用光谱指数nHI、NSPI、aVNIR、PEP和VPEP对高光谱图像进行物理分类。利用研究区太阳能光伏地面真实数据验证,PRISMA高光谱数据的用户精度为70.53%,生产者精度为88.06%,AVIRIS-NG高光谱数据的用户精度为65.94%,生产者精度为82.77%。
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Detection of Solar Photovoltaic Power Plants Using Satellite and Airborne Hyperspectral Imaging
Solar photovoltaic panels (PV) provide great potential to reduce greenhouse gas emissions as a renewable energy technology. The number of solar PV has increased significantly in recent years and is expected to increase even further. Therefore, accurate and global mapping and monitoring of PV modules with remote sensing methods is important for predicting energy production potentials, revealing socio-economic drivers, supporting urban planning, and estimating ecological impacts. Hyperspectral imagery provides crucial information to identify PV modules based on their physical absorption and reflection properties. This study investigated spectral signatures of spaceborne PRISMA data of 30 m low resolution for the first time, as well as airborne AVIRIS-NG data of 5.3 m medium resolution for the detection of solar PV. The study region is located around Irlbach in southern Germany. A physics-based approach using the spectral indices nHI, NSPI, aVNIR, PEP, and VPEP was used for the classification of the hyperspectral images. By validation with a solar PV ground truth dataset of the study area, a user’s accuracy of 70.53% and a producer’s accuracy of 88.06% for the PRISMA hyperspectral data, and a user’s accuracy of 65.94% and a producer’s accuracy of 82.77% for AVIRIS-NG were achieved.
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