ICESat-2星载光子计数激光雷达数据处理与应用研究进展

朱笑笑; 王成; 习晓环; 聂胜; 杨学博; 黎东; 朱笑笑; 王成; 习晓环; 聂胜; 杨学博; 黎东

doi:10.3788/IRLA20200259

[1]

庞勇, 李增元, 陈博伟, 等. 星载激光雷达森林探测进展及趋势[J]. 上海航天, 2019, 36(3): 20-27.

Pang Yong, Li Zengyuan, Chen Bowei, et al. Status and development of spaceborne lidar application in forestry [J]. Aerospace Shanghai, 2019, 36(3): 20-27. (in Chinese

[2]

葛莉, 习晓环, 王成. ICESat-1/GLAS数据湖泊水位监测研究进展[J]. 遥感技术与应用, 2017, 32(1): 14-19.

Ge Li, Xi Xiaohuan, Wang Cheng, et al. Research progress of ICESat-1/GLAS in lake level monitoring [J]. Remote Sensing Technology and Application, 2017, 32(1): 14-19. (in Chinese

[3]

Wang X, Cheng X, Gong P, et al. Earth science applications of ICESat/GLAS: a review [J]. International Journal of Remote Sensing, 2011, 32(23): 8837-8864. doi: 10.1080/01431161.2010.547533

[4]

胥喆, 舒清态, 杨凯博, 等. 星载激光雷达在林业上的应用研究进展[J]. 福建林业科技, 2017, 44(1): 141-148.

Xu Zhe, Shu Qingtai, Yang Kaibo, et al. The Progress of forestry application based on spaceborne lidar [J]. Journal of Fujian Forestry Science and Technology, 2017, 44(1): 141-148. (in Chinese

[5]

Abshire J B, Sun X, Riris H, et al. Geoscience laser altimeter system (GLAS) on the ICESat mission: on‐orbit measurement performance [J]. Geophysical Research Letters, 2005, 32(21): L21S02.

[6]

Dubayah R, Blair J B, Goetz S, et al. The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography [J]. Science of Remote Sensing, 2020, 1: 100002. doi: 10.1016/j.srs.2020.100002

[7]

晓曲. 高分七号卫星[J]. 卫星应用, 2019(11): 22.

Xiao Qu. Gaofen-7 satellite [J]. Satellite Application, 2019(11): 22. (in Chinese

[8]

Markus T, Neumann T, Martino A, et al. The ice, cloud, and land elevation satellite-2 (ICESat-2): science requirements, concept, and implementation [J]. Remote Sensing of Environment, 2017, 190: 260-273. doi: 10.1016/j.rse.2016.12.029

[9]

Neumann T A, Martino A J, Markus T, et al. The ice, cloud, and land elevation satellite-2 mission: a global geolocated photon product derived from the advanced topographic laser altimeter system [J]. Remote Sensing of Environment, 2019, 233: 111325. doi: 10.1016/j.rse.2019.111325

[10]

Neuenschwander A, Pitts K. The ATL08 land and vegetation product for the ICESat-2 Mission [J]. Remote Sensing of Environment, 2019, 221: 247-259. doi: 10.1016/j.rse.2018.11.005

[11]

Moussavi M S, Abdalati W, Scambos T, et al. Applicability of an automatic surface detection approach to micro-pulse photon-counting lidar altimetry data: implications for canopy height retrieval from future ICESat-2 data [J]. International Journal of Remote Sensing, 2014, 35(13): 5263-5279. doi: 10.1080/01431161.2014.939780

[12]

McGill M, Markus T, Scott VS, et al. The multiple altimeter beam experimental lidar (MABEL): an airborne simulator for the ICESat-2 mission [J]. Journal of Atmospheric and Oceanic Technology, 2013, 30(2): 345-352. doi: 10.1175/JTECH-D-12-00076.1

[13]

Nie S, Wang C, Xi X, et al. Estimating the vegetation canopy height using micro-pulse photon-counting LiDAR data [J]. Optics Express, 2018, 26(10): A520-A540. doi: 10.1364/OE.26.00A520

[14]

Chen B, Pang Y. A denoising approach for detection of canopy and ground from ICESat-2's airborne simulator data in Maryland, USA [C]//Proceedings of the AOPC 2015: Advances in Laser Technology and Applications. International Society for Optics and Photonics, 2015.

[15]

Magruder L A, Wharton M E, Stout K D, et al. Noise filtering techniques for photon-counting ladar data [C]//Proceedings of the Laser Radar Technology and Applications XVII. International Society for Optics and Photonics, 2012.

[16]

Zhang J, Kerekes J, Csatho B, et al. A clustering approach for detection of ground in micropulse photon-counting lidar altimeter data [C]//Proceedings of the IEEE Geoscience and Remote Sensing Symposium, IGARSS 2014, 2014.

[17]

Huang J, Xing Y, You H, et al. Particle swarm optimization-based noise filtering algorithm for photon cloud data in forest area [J]. Remote Sensing, 2019, 11(8): 980. doi: 10.3390/rs11080980

[18]

Zhu X X, Nie S, Wang C, et al. A noise removal algorithm based on OPTICS for photon-counting LiDAR data [J]. IEEE Geoscience and Remote Sensing Letters, 2020. doi: 10.1109/LGRS.2020.3003191

[19]

Wang X, Pan Z, Glennie C. A novel noise filtering model for photon-counting laser altimeter data [J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(7): 947-951. doi: 10.1109/LGRS.2016.2555308

[20]

Popescu S C, Zhou T, Nelson R, et al. Photon counting LiDAR: An adaptive ground and canopy height retrieval algorithm for ICESat-2 data [J]. Remote Sensing of Environment, 2018, 208: 154-170. doi: 10.1016/j.rse.2018.02.019

[21]

Gwenzi D, Lefsky M A, Suchdeo V P, et al. Prospects of the ICESat-2 laser altimetry mission for savanna ecosystem structural studies based on airborne simulation data [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 118: 68-82. doi: 10.1016/j.isprsjprs.2016.04.009

[22]

谢锋, 杨贵, 舒嵘, 等. 方向自适应的光子计数激光雷达滤波方法[J]. 红外与毫米波学报, 2017, 36(1): 107-113. doi: 10.11972/j.issn.1001-9014.2017.01.019

Xie F, Yang G, Shu R, et al. An adaptive directional filter for photon counting Lidar point cloud data [J]. Journal of Infrared and Millimeter Waves, 2017, 36(1): 107-113. (in Chinese doi: 10.11972/j.issn.1001-9014.2017.01.019

[23]

Herzfeld U C, McDonald B W, Wallin B F, et al. Algorithm for detection of ground and canopy cover in micropulse photon-counting Lidar altimeter data in preparation for the ICESat-2 mission [J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(4): 2109-2125. doi: 10.1109/TGRS.2013.2258350

[24]

夏少波, 王成, 习晓环, 等. ICESat-2机载试验点云滤波及植被高度反演[J]. 遥感学报, 2014, 18(4): 1199-1207. doi: 10.11834/jrs.20144029

Xia Shaobo, Wang Cheng, Xi Xiaohuan, et al. Point cloud filtering and tree height estimation using airborne experiment data of ICESat-2 [J]. Journal of Remote Sensing, 2014, 18(4): 1199-1207. (in Chinese doi: 10.11834/jrs.20144029

[25]

Zhu X, Nie S, Wang C, et al. A ground elevation and vegetation height retrieval algorithm using micro-pulse photon-counting LiDAR data [J]. Remote Sensing, 2018, 10(12): 1962. doi: 10.3390/rs10121962

[26]

Smith B, Fricker H A, Holschuh N, et al. Land ice height-retrieval algorithm for NASA's ICESat-2 photon-counting laser altimeter [J]. Remote Sensing of Environment, 2019, 233: 111352. doi: 10.1016/j.rse.2019.111352

[27]

Brunt K M, Neumann T A, Smith B E. Assessment of ICESat-2 ice sheet surface heights, based on comparisons over the interior of the Antarctic ice sheet [J]. Geophysical Research Letters, 2019, 46(22): 13072-13078. doi: 10.1029/2019GL084886

[28]

Brunt K M, Neumann T A, Walsh K M, et al. Determination of local slope on the Greenland Ice Sheet using a multibeam photon-counting Lidar in preparation for the ICESat-2 Mission [J]. IEEE Geoscience and Remote Sensing Letters, 2013, 11(5): 935-939.

[29]

Smith B, Fricker H A, Gardner A S, et al. Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes [J]. Science, 2020, 368(6496): 1239-1242. doi: 10.1126/science.aaz5845

[30]

Li T, Dawson G J, Chuter S J, et al. Mapping the antarctic grounding zone from ICESat-2 laser altimetry [C]//The Cryosphere Discussions, 2020.

[31]

Kwok R, Markus T, Kurtz N T, et al. Surface height and sea ice freeboard of the Arctic Ocean from ICESat-2: Characteristics and early results [J]. Journal of Geophysical Research: Oceans, 2019, 124(10): 6942-6959. doi: 10.1029/2019JC015486

[32]

Kwok R, Kacimi S, Markus T, et al. ICESat-2 surface height and sea ice freeboard assessed with ATM lidar acquisitions from operation iceBridge [J]. Geophysical Research Letters, 2019, 46(20): 11228-11236. doi: 10.1029/2019GL084976

[33]

Petty A A, Kurtz N T, Kwok R, et al. Winter Arctic sea ice thickness from ICESat-2 freeboards [J]. Journal of Geophysical Research: Oceans, 2020, 125(5): e2019JC015764.

[34]

Kwok R, Kacimi S, Webster M A, et al. Arctic snow depth and sea ice thickness from ICESat-2 and CryoSat-2 freeboards: a first examination [J]. Journal of Geophysical Research: Oceans, 2020, 125(3): e2019JC016008.

[35]

Dandabathula G, Verma M, Sitiraju S R. Evaluation of best-fit terrain elevation of ICESat-2 ATL08 using DGPS surveyed points [J]. Journal of Applied Geodesy, 2020, 14(3): 285-293. doi: 10.1515/jag-2020-0003

[36]

Neuenschwander A L, Magruder L A. Canopy and terrain height retrievals with ICESat-2: A first look [J]. Remote Sensing, 2019, 11(14): 1721. doi: 10.3390/rs11141721

[37]

Wang C, Zhu X, Nie S, et al. Ground elevation accuracy verification of ICESat-2 data: a case study in Alaska, USA [J]. Optics Express, 2019, 27(26): 38168-38179. doi: 10.1364/OE.27.038168

[38]

Zhu X, Wang C, Nie S, et al. Mapping forest height using photon-counting LiDAR data and Landsat 8 OLI data: a case study in Virginia and North Carolina, USA [J]. Ecological Indicators, 2020, 114: 106287. doi: 10.1016/j.ecolind.2020.106287

[39]

Li W, Niu Z, Shang R, et al. High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data [J]. International Journal of Applied Earth Observation and Geoinformation, 2020, 92: 102163. doi: 10.1016/j.jag.2020.102163

[40]

Narine L L, Popescu S, Neuenschwander A, et al. Estimating aboveground biomass and forest canopy cover with simulated ICESat-2 data [J]. Remote Sensing of Environment, 2019, 224: 1-11. doi: 10.1016/j.rse.2019.01.037

[41]

Narine L L, Popescu S, Zhou T, et al. Mapping forest aboveground biomass with a simulated ICESat-2 vegetation canopy product and Landsat data [J]. Annals of Forest Research, 2019, 62(2): 69-86.

[42]

Narine L L, Popescu S C, Malambo L. Using ICESat-2 to estimate and map forest aboveground biomass: a first example [J]. Remote Sensing, 2020, 12(11): 1824. doi: 10.3390/rs12111824

[43]

Liu M, Popescu S, Malambo L. Feasibility of burned area mapping based on ICESAT-2 photon counting data [J]. Remote Sensing, 2020, 12(1): 24.

[44]

Yuan C, Gong P, Bai Y. Performance assessment of ICESat-2 laser altimeter data for water-level measurement over lakes and reservoirs in China [J]. Remote Sensing, 2020, 12(5): 770. doi: 10.3390/rs12050770

[45]

Zhang G, Chen W, Xie H. Tibetan Plateau's lake level and volume changes from NASA's ICESat/ICESat-2 and Landsat missions [J]. Geophysical Research Letters, 2019, 46(22): 13107-13118. doi: 10.1029/2019GL085032

[46]

Xu N, Ma Y, Zhang W, et al. Surface-water-level changes during 2003-2019 in Australia revealed by ICESat/ICESat-2 altimetry and landsat imagery [J]. IEEE Geoscience and Remote Sensing Letters, 2020: 10.1109/LGRS.2020.2996769.

[47]

Ma Y, Xu N, Sun J, et al. Estimating water levels and volumes of lakes dated back to the 1980s using Landsat imagery and photon-counting lidar datasets [J]. Remote Sensing of Environment, 2019, 232: 111287. doi: 10.1016/j.rse.2019.111287

[48]

Fair Z, Flanner M, Brunt K M, et al. Using ICESat-2 and Operation IceBridge altimetry for supraglacial lake depth retrievals [J]. The Cryosphere Discussions, 2020: 10.5194/tc-2020-136.

[49]

Parrish C E, Magruder L A, Neuenschwander A L, et al. Validation of ICESat-2 ATLAS bathymetry and analysis of ATLAS’s bathymetric mapping performance [J]. Remote Sensing, 2019, 11(14): 1634. doi: 10.3390/rs11141634

[50]

Albright A, Glennie C. Nearshore bathymetry from fusion of Sentinel-2 and ICESat-2 observations [J]. IEEE Geoscience and Remote Sensing Letters, 2020: 10.1109/LGRS.2020.2987778.

[51]

Klotz B W, Neuenschwander A, Magruder L A. High-resolution ocean wave and wind characteristics determined by the ICESat-2 land surface algorithm [J]. Geophysical Research Letters, 2020, 47(1): e2019GL085907.

[52]

Horvat C, Blanchard-Wrigglesworth E, Petty A. Observing waves in sea ice with ICESat-2 [J]. Geophysical Research Letters, 2020, 47(10): e2020GL087629.

[53]

Lu X, Hu Y, Yang Y. Ocean Subsurface study from ICESat-2 mission [C]//In Proceedings of Photonics & Electromagnetics Research Symposium-Fall. PIERS 2019, 2019.

[54]

Lu X, Hu Y, Yang Y, et al. Antarctic spring ice-edge blooms observed from space by ICESat-2 [J]. Remote Sensing of Environment, 2020, 245: 111827. doi: 10.1016/j.rse.2020.111827