1. China Aero Geophysical Survey and Romote Sensing Center for Natural Resources, Beijing 100083, China 2. Key Laboratory of Airborne Geophysics and Remote Sensing Geology, Ministry of Natural Resources, Beijing 100083, China 3. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
When coastal hyperspectral remote sensing measurement and survey are conducted, the water surface cannot be used for ground control point measurement, and hence the accurate external orientation element of the data cannot be obtained by the traditional aerial triangulation method. Therefore, how to ensure the geometric accuracy of the aerial remote sensing data is one of the key problems in measurement. In this study, the authors summarized and analyzed the geometrical correction principle and model characteristics of CASI 1500H push-broom airborne hyperspectral instrument and designed a set of geometric calibration schemes for this system. The calibration results show that the geometric accuracy of CASI 1500H hyperspectral image can still be significantly improved without control points. Using this geometric calibration method, the authors acquired CASI airborne hyperspectral data of Dajin Island and its surrounding waters. Based on these data, the authors retrieved the suspended sediment concentration in the surrounding waters of Dajin Island, and the overall accuracy was better than 70%, which can meet the need of coastal airborne remote sensing survey.
Ma Y, Zhang J, Zhang H D , et al. Advances in application research on the marine airborne hyperspectral remote sensing in China[J]. Advances in Marine Science, 2002,20(4):94-98.
Ma Y, Zhang J, Cui T W . Research on airborne hyperspectral identification of red tide organism dominant species based on SVM[J]. Spectroscopy and Spectral Analysis, 2006,26(12):2302-2305.
Bu Z G, Zhou K, Huang J . Spectral extraction and hyperspectral analysis of oil polluted water from airborne data using image characteristics[J]. Periodical of Ocean University of China, 2005,35(4):687-690.
[4]
刘茜, David G R . 基于高光谱数据和MODIS影像的鄱阳湖悬浮泥沙浓度估算[J]. 遥感技术与应用, 2008,23(1):7-11.
Liu Q, David G R . Estimation on suspended sedimentation concentration of Poyang Lake using MODIS and hyperspectral data[J]. Remote Sensing Technology and Application, 2008,23(1):7-11.
Wang Y P, Li Y C, Xue Y L , et al. Experinental investigation and application of ADS40 photogrammetry system[J]. Science of Surveying and Mapping, 2007,32(1):119-121.
[6]
Kocaman S, Casella V, Franzini M , et al. The triangulation accuracy of ADS40 imagery over the Pavia test site[C]// 2007 Conference of the Remote Sensing and Photogrammetry Society,Knala Lumpur: 2007.
Xu M Z, Tu X R . Geometric calibration of ADS40 system based on test field[J]. Geomatics and Information Science of Wuhan University, 2011,36(7):771-775.
Wang T, Zhang Y S, Zhang Y , et al. Airborne linear CCD sensor geometric calibration based on self-calibration[J]. Acta Geodaetica et Cartographica Sinica, 2012,41(3):393-400.
Zhu F, Ou S Y, Zhang S H , et al. MODIS images-based retrieval and analysis of spatial-temporal change of superficial suspended sediment concentration in the Pearl River estuary[J]. Journal of Sediment Research, 2015(2):67-73.
Qiao X J, He B Y, Zhang W , et al. MODIS-based retrieval and change analysis of sediment concentration in middle yangtze suspended river[J]. Resources and Environment in the Yangtze Basin, 2013,22(8):1090-1095.
Diao S J, Liu C L, Zhang T , et al. Extraction of remote sensing information for lake salinity level based on SVM:A case from Badain Jaran desert in Inner Mongolia[J]. Remote Sensing for Land and Resources, 2016,28(4):114-118.doi: 10.6046/gtzyyg.2016.04.18.