Spaceborne optical remote sensing provides a novel approach for the accurate detection, positioning, and identification of flying aircraft. Due to the lack of techniques for extracting altitude information of flying aircraft from hyperspectral images, obtaining precise spectral reflectance of flying aircraft remains challenging, which hinders the analysis and recognition of their spectral characteristics. This thesis proposes a method for retrieving the altitude and spectral reflectance of flying aircraft from hyperspectral images based on contrails. By constructing a geometric model of contrails and their shadows, the altitude of flying aircraft is accurately retrieved. Furthermore, the spectral reflectance is retrieved through a radiative transfer model that couples the flying aircraft with the background environment. Experiments were conducted using GF-5 hyperspectral images in typical scenarios such as land, sea, and coastal backgrounds. The proposed method was validated by comparing the results with aircraft type and altitude information from Flightradar24, the FLAASH method for land surface spectral reflectance retrieval, and spectral reflectance data of parked/gliding aircraft in EnMAP hyperspectral images from typical international airports. The results demonstrate that the altitude retrieval accuracy for wide-body airliners in flight can reach ±100 m, and the spectral reflectance retrieval accuracy for flying aircraft is significantly improved compared to classical surface spectral reflectance retrieval methods. This study provides important support for the application of hyperspectral remote sensing images in the detection, positioning, and identification of flying aircraft.
[1]WU Q, SUN H, SUN X, et al.Aircraft recognition in high-resolution optical satellite remote sensing images[J].IEEE Geosci. Remote Sens. Lett., 2015, 12(1):112-116
[2]LI K, WAN G, CHENG G, et al.Object detection in optical remote sensing images: a survey and a new benchmark[J].ISPRS J. Photogramm. Remote Sens., 2020, 159:296-307
[3]ZHAO F, XIA L, KYLLING A.Mapping global flying aircraft activities using Landsat 8 and cloud computing[J].ISPRS J. Photogramm. Remote Sens., 2022, 184:19-30
[4]LIU Y, XU B, ZHI W.Space eye on flying aircraft: from Sentinel-2 MSI parallax to hybrid computing[J].Remote Sens. Environ., 2020, 246:Article 111867-
[5]LI L, ZHOU X, HU Z, et al.On-orbit monitoring flying aircraft day and night based on SDGSAT-1 thermal infrared dataset[J].Remote Sens. Environ., 2023, 298:Article 113840.-
[6]杨利峰, 冯彦卿, 王建宇.基于航迹云提议的高光谱遥感空管监视方法[J].红外与毫米波学报, 2025, 44(2):217-225
[7]ZHOU X, LI L, YU J, L, et al.Multimodal aircraft flight altitude inversion from SDGSAT-1 thermal infrared data[J].Remote Sens. Environ., 2024, 308:Article 114178-
[8]杨利峰, 陈卓, 陈凡胜等.基于热红外多通道特征匹配的航空器高度估计方法[J].红外与毫米波学报, 2025, 44(02):258-264
[9] LIU, Y N, et al.The advanced hyperspectral imager: Aboard China' s GaoFen-5 satellite[J]. IEEE Geoscience and Remote Sensing Magazine 7.4 (2019): 23-32.
[10] TANG, H Z, et al.Radiometric Calibration of GF5-02 Advanced Hyperspectral Imager Based on RadCalNet Baotou Site[J]. Remote Sensing 15.9 (2023): 2233.
[11] LIU, Y N, et al.Development of advanced visible and short-wave infrared hyperspectral imager onboard ZY-1-02D satellite[J]. Spacecraft. Engineering 29.06 (2020): 85-92.
[12] TANG, H Z, et al.On-Orbit vicarious radiometric calibration and validation of ZY1-02E thermal infrared sensor[J]. Remote Sensing 15.4 (2023): 994.
[13]朱嘉诚, 赵知诚, 刘全, 等.静止轨道全谱段宽覆盖成像光谱仪光学系统设计与高保真分光系统研制[J].光学学报, 2023, 43(08):304-320
[14]LI J, ZHAO H, GU X, et al.Analysis of Space-Based Observed Infrared Characteristics of Aircraft in the Air[J].Remote Sensing, 2023, 15(2):535-
[15] KARCHER B.Formation and radiative forcing of contrail cirrus[J]. Nat Commun 9, 1824 (2018).
[16]HEYMSFIELD A, BAUMGARDNER D, DEMOTT P, et al.Contrail microphysics[J].Bulletin of the American Meteorological Society, 2010, 91(4):465-472
[17]张敬林, 张国宇, 杨全等.飞机尾迹云识别及其辐射强迫的研究进展[J].大气科学学报, 2018, 41(05):577-584
[18] ANDERSON, GAIL P, et al.MODTRAN4-based atmospheric correction algorithm: FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes)[J]. Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery VIII. Vol. 4725. SPIE, 2002.
[19] L.Guanter et al., The ENMAP Spaceborne Imaging Spectroscopy Mis-sion for Earth Observation[J]. Remote Sensing, vol. 7, no. 7, pp. 8830–8857, Jul. 2015, doi: 10.3390/rs70708830.
[20] MANNSTEIN H, MEYER R, WENGLING P.Operational detection of contrails from NOAA-AVHRR-data[J]. International Journal of Remote Sensing, 1999, 20: 1641-1660.
[21] VAZQUEZ-NAVARRO M, MANNSTEIN H, MAYER B.An automatic contrail tracking algorithm[J]. Atmospheric Measurement Techniques, 2010, 3: 1089-1101.
[22] ZHANG G Y, ZHANG J L, SHANG J.Contrail recognition with convolutional neural network and contrail parameterizations evaluation[J]. SOLA, 2018, 14: 132-137.
[23]HOFFMAN J P, RAHMES T F, WIMMERS A J, et al.The Application of a Convolutional Neural Network for the Detection of Contrails in Satellite Imagery[J].Remote Sensing, 2023, 15(11):2854-
[24] DEKOUTSIDIS G, FEIDAS H, BUGLIARO L.Contrail detection on SEVIRI images and 1-year study of their physical properties and the atmospheric conditions favoring their formation over Europe[J]. Theoretical and Applied Climatology, 2023, 151: 1931-1948.
[25] LI Z, SHEN H, WENG Q, et al.Cloud and cloud shadow detection for optical satellite imagery: Features, algorithms, validation, and prospects[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 188: 89-108.
[26] TSAI V J D.A comparative study on shadow compensation of color aerial images in invariant color models[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, vol. 44, no. 6: 1661-1671.
[27] ZHU Z, WOODCOCK C E.Object-based cloud and cloud shadow detection in Landsat imagery[J]. Remote Sensing of Environment, 2012, 118: 83-94.
[28] ZHU Z, WANG S, WOODCOCK C E.Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images[J]. Remote Sensing of Environment, 2015, 159: 269-277.
[29] ZEKOLL V, DE LOS REYES R, RICHTER R.A Newly Developed Algorithm for Cloud Shadow Detection—TIP Method[J]. Remote Sensing. 2022, 14: 2922.
[30] BERK A, et al.MODTRAN? 6: A major upgrade of the MODTRAN? radiative transfer code[R]. 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2014.
[31] GAO B C, KAUFMAN Y J.Selection of the 1.375-μm MODIS channel for remote sensing of cirrus clouds and stratospheric aerosols from space[J]. J. Atmos. Sci., 52 (23) (1995), pp. 4231-4237.
[32] MA H, QIN Q, SHEN X.Shadow Segmentation and Compensation in High Resolution Satellite Images[C]. IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, USA, 2008, pp. II-1036-II-1039.
[33] JIA, G R, et al.Spectral super-resolution reflectance retrieval from remotely sensed imaging spectrometer data[J]. Optics Express 24.17 (2016): 19905-19919.
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