测绘学报 ›› 2022, Vol. 51 ›› Issue (6): 983-995.doi: 10.11947/j.AGCS.2022.20220154
朱建军, 付海强, 汪长城
收稿日期:
2022-03-01
修回日期:
2022-04-15
发布日期:
2022-07-02
通讯作者:
付海强
E-mail:haiqiangfu@csu.edu.cn
作者简介:
朱建军(1962-),男,教授,博士生导师,研究方向为测量平差与InSAR数据处理。E-mail:zjj@csu.edu.cn
基金资助:
ZHU Jianjun, FU Haiqiang, WANG Changcheng
Received:
2022-03-01
Revised:
2022-04-15
Published:
2022-07-02
Supported by:
摘要: 传统光学遥感主要采集地表覆盖层表面几何信息及部分物理信息,难以对其厚度及内部结构属性信息进行全方位监测。极化干涉合成孔径雷达(PolInSAR)具备穿透地表覆盖层并记录内部结构与物理属性的能力,为解决上述问题带来了契机。因此,如何对地表覆盖层进行“穿透测绘”,全面采集地表覆盖层空间几何、内部结构属性及其动态变化过程已成为研究热点。本文首先尝试定义“穿透测绘”的基本内涵;然后,梳理了基于PolInSAR技术的穿透测绘在植被、冰雪、沙漠等自然地表覆盖层的应用进展;最后,分析总结了PolInSAR穿透测绘面临的挑战。
中图分类号:
朱建军, 付海强, 汪长城. 极化干涉SAR地表覆盖层“穿透测绘”技术进展[J]. 测绘学报, 2022, 51(6): 983-995.
ZHU Jianjun, FU Haiqiang, WANG Changcheng. Research progress of "penetration mapping" of earth surface by PolInSAR[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(6): 983-995.
[1] HORN R. The DLR airborne SAR project E-SAR[C]//Proceedings of 1996 International Geoscience and Remote Sensing Symposium. Lincoln, NE:IEEE, 1996:1624-1628. [2] HORN R, NOTTENSTEINER A, REIGBER A, et al. F-SAR-DLR's new multifrequency polarimetric airborne SAR[C]//Proceedings of 2009 IEEE International Geoscience and Remote Sensing Symposium. Cape Town:IEEE, 2009:Ⅱ-902-Ⅱ-905. [3] BRUYANT J P. SETHI flying lab:a tool for remote sensing applications[C]//Proceedings of the 11th International Radar Symposium. Vilnius, Lithuania:IEEE, 2010:1-4. [4] ROSEN P A, HENSLEY S, WHEELER K, et al. UAVSAR:a new NASA airborne SAR system for science and technology research[C]//Proceedings of 2006 IEEE Conference on Radar. Verona, NY, USA:IEEE, 2006:8. [5] QUEGAN S, LE TOAN T, CHAVE J, et al. The European Space Agency BIOMASS mission:measuring forest above-ground biomass from space[J]. Remote Sensing of Environment, 2019, 227:44-60. DOI:10.1016/j.rse.2019.03.032. [6] MOREIRA A, KRIEGER G, HAJNSEK I, et al. Tandem-L:a highly innovative bistatic SAR mission for global observation of dynamic processes on the Earth's surface[J]. IEEE Geoscience and Remote Sensing Magazine, 2015, 3(2):8-23. DOI:10.1109/MGRS.2015.2437353. [7] LEE J S, POTTIER E. Polarimetric radar imaging:from basics to applications[M]. Boca Raton:CRC Press, 2009. [8] FREEMAN A, DURDEN S L. A three-component scattering model for polarimetric SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(3):963-973. DOI:10.1109/36.673687. [9] PAPATHANASSIOU K P, CLOUDE S R. Single-baseline polarimetric SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2001, 39(11):2352-2363. DOI:10.1109/36.964971. [10] CLOUDE S R. Polarisation:applications in remote sensing[M]. London:Oxford University Press, 2009. [11] REIGBER A, MOREIRA A. First demonstration of airborne SAR tomography using multibaseline L-band data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(5):2142-2152. DOI:10.1109/36.868873. [12] TREUHAFT R N, MADSEN S N, MOGHADDAM M, et al. Vegetation characteristics and underlying topography from interferometric radar[J]. Radio Science, 1996, 31(6):1449-1485. DOI:10.1029/96RS01763. [13] DALL J. InSAR elevation bias caused by penetration into uniform volumes[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(7):2319-2324. DOI:10.1109/TGRS.2007.896613. [14] PAPATHANASSIOU K P, CLOUDE S R. The effect of temporal decorrelation on the inversion of forest parameters from Pol-InSAR data[C]//Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium. Toulouse, France:IEEE, 2003:1429-1431. [15] LEE S K, KUGLER F, PAPATHANASSIOU K P, et al. Quantification of temporal decorrelation effects at L-band for polarimetric SAR interferometry applications[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(3):1351-1367. DOI:10.1109/JSTARS.2013.2253448. [16] LAVALLE M, SIMARD M, HENSLEY S. A temporal decorrelation model for polarimetric radar interferometers[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(7):2880-2888. DOI:10.1109/TGRS.2011.2174367. [17] LU Hongxi, SUO Zhiyong, GUO Rui, et al. S-RVoG model for forest parameters inversion over underlying topography[J]. Electronics Letters, 2013, 49(9):618-620. DOI:10.1049/el.2012.4467. [18] XIE Qinghua, ZHU Jianjun, WANG Changcheng, et al. A modified dual-baseline PolInSAR method for forest height estimation[J]. Remote Sensing, 2017, 9(8):819. DOI:10.3390/rs9080819. [19] 解清华, 朱建军, 汪长城, 等. 基于S-RVoG模型的PolInSAR森林高度非线性复数最小二乘反演算法[J]. 测绘学报, 2020, 49(10):1303-1310. DOI:10.11947/j.AGCS.2020.20190081. XIE Qinghua, ZHU Jianjun, WANG Changcheng, et al. A S-RVoG model-based PolInSAR nonlinear complex least squares method for forest height inversion[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(10):1303-1310. DOI:10.11947/j.AGCS.2020.20190081. [20] LOPEZ-SANCHEZ J M, BALLESTER-BERMAN J D, MARQUEZ-MORENO Y. Model limitations and parameter-estimation methods for agricultural applications of polarimetric SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(11):3481-3493. DOI:10.1109/TGRS.2007.900690. [21] GARESTIER F, DUBOIS-FERNANDEZ P C, CHAMPION I. Forest height inversion using high-resolution P-band Pol-InSAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(11):3544-3559. DOI:10.1109/TGRS.2008.922032. [22] GARESTIER F, LE TOAN T. Forest modeling for height inversion using single-baseline InSAR/Pol-InSAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3):1528-1539. DOI:10.1109/TGRS.2009.2032538. [23] FU Wenxue, GUO Huadong, SONG Pengfei, et al. Combination of PolInSAR and LiDAR techniques for forest height estimation[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(8):1218-1222. DOI:10.1109/LGRS.2017.2703628. [24] ZHANG Bing, FU Haiqiang, ZHU Jianjun, et al. A multibaseline PolInSAR forest height inversion model based on Fourier-Legendre polynomials[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(4):687-691. DOI:10.1109/LGRS.2020.2984129. [25] ZOU Bin, ZHANG Lamei, WANG Wei, et al. Forest parameters inversion using PolInSAR data based on genetic algorithm[C]//Proceedings of 2006 IEEE International Symposium on Geoscience and Remote Sensing. Denver, CO, USA:IEEE, 2006:2651-2654. DOI:10.1109/IGARSS.2006.684. [26] 李廷伟, 梁甸农, 黄海风, 等. 一种基于BP神经网络的极化干涉SAR植被高度反演方法[J]. 国防科技大学学报, 2010, 32(3):60-64. LI Tingwei, LIANG Diannong, HUANG Haifeng, et al. A BP neural-network based method for vegetation height inversion of the polarimetric interferometric SAR[J]. Journal of National University of Defense Technology, 2010, 32(3):60-64. [27] CLOUDE S R, PAPATHANASSIOU K P. Three-stage inversion process for polarimetric SAR interferometry[J]. IEE Proceedings-Radar, Sonar and Navigation, 2003, 150(3):125-134. DOI:10.1049/ip-rsn:20030449. [28] CLOUDE S R. Robust parameter estimation using dual baseline polarimetric SAR interferometry[C]//Proceedings of 2002 IEEE International Geoscience and Remote Sensing Symposium. Toronto, Canada:IEEE, 2002:838-840. [29] HAJNSEK I, KUGLER F, LEE S K, et al. Tropical-forest-parameter estimation by means of Pol-InSAR:the INDREX-Ⅱ campaign[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(2):481-493. DOI:10.1109/TGRS.2008.2009437. [30] LEE S K, FATOYINBO T E, LAGOMASINO D, et al. Multibaseline TanDEM-X mangrove height estimation:the selection of the vertical wavenumber[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(10):3434-3442. DOI:10.1109/JSTARS.2018.2835647. [31] XIE Yanzhou, FU Haiqiang, ZHU Jianjun, et al. A LiDAR-aided multibaseline PolInSAR method for forest height estimation:with emphasis on dual-baseline selection[J]. IEEE Geoscience and Remote Sensing Letters, 2020, 17(10):1807-1811. DOI:10.1109/LGRS.2019.2951805. [32] 朱建军, 解清华, 左廷英, 等. 复数域最小二乘平差及其在PolInSAR植被高反演中的应用[J]. 测绘学报, 2014, 43(1):45-51. DOI:10.13485/j.cnki.11-2089.2014.0007. ZHU Jianjun, XIE Qinghua, ZUO Tingying, et al. Criterion of complex least squares adjustment and its application in tree height inversion with PolInSAR data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(1):45-51. DOI:10.13485/j.cnki.11-2089.2014.0007. [33] LOMBARDINI F, REIGBER A. Adaptive spectral estimation for multibaseline SAR tomography with airborne L-band data[C]//Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium. Toulouse, France:IEEE, 2003:2014-2016. [34] NANNINI M, SCHEIBER R, MOREIRA A. Estimation of the minimum number of tracks for SAR tomography[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(2):531-543. DOI:10.1109/TGRS.2008.2007846. [35] TEBALDINI S, GUARNIERI A M. On the role of phase stability in SAR multibaseline applications[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(7):2953-2966. DOI:10.1109/TGRS.2010.2043738. [36] HUANG Yue, FERRO-FAMIL L, REIGBER A. Under-foliage object imaging using SAR tomography and polarimetric spectral estimators[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(6):2213-2225. DOI:10.1109/TGRS.2011.2171494. [37] FERRO-FAMIL L, HUANG Yue, REIGBER A. High-Resolution SAR tomography using full rank Polarimetric spectral estimators[C]//Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany:IEEE, 2012:5194-5197. [38] CLOUDE S R. Polarization coherence tomography[J]. Radio Science, 2006, 41(4):RS4017. DOI:10.1029/2005RS003436. [39] TREUHAFT R N, CHAPMAN B D, DOS SANTOS J R, et al. Vegetation profiles in tropical forests from multibaseline interferometric synthetic aperture radar, field, and lidar measurements[J]. Journal of Geophysical Research:Atmospheres, 2009, 114(D23):D23110. DOI:10.1029/2008JD011674. [40] BRIGOT G, SIMARD M, COLIN-KOENIGUER E, et al. Retrieval of forest vertical structure from PolInSAR data by machine learning using LIDAR-derived features[J]. Remote Sensing, 2019, 11(4):381. DOI:10.3390/rs11040381. [41] LEE Y S, LEE S, BAEK W K, et al. Mapping forest vertical structure in Jeju island from optical and radar satellite images using artificial neural network[J]. Remote Sensing, 2020, 12(5):797. DOI:10.3390/rs12050797. [42] CAZCARRA-BES V, TELLO-ALONSO M, FISCHER R, et al. Monitoring of forest structure dynamics by means of L-band SAR tomography[J]. Remote Sensing, 2017, 9(12):1229. DOI:10.3390/rs9121229. [43] LE TOAN T, BEAUDOIN A, RIOM J, et al. Relating forest biomass to SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(2):403-411. DOI:10.1109/36.134089. [44] BEAUDOIN A, LE TOAN T, GOZE S, et al. Retrieval of forest biomass from SAR data[J]. International Journal of Remote Sensing, 1994, 15(14):2777-2796. [45] HOEKMAN D H, QUIÑONES M J. Land cover type and biomass classification using AirSAR data for evaluation of monitoring scenarios in the Colombian Amazon[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(2):685-696. DOI:10.1109/36.841998. [46] HARRELL P A, BOURGEAU-CHAVEZ L L, KASISCHKE E S, et al. Sensitivity of ERS-1 and JERS-1 radar data to biomass and stand structure in Alaskan boreal forest[J]. Remote Sensing of Environment, 1995, 54(3):247-260. DOI:10.1016/0034-4257(95)00127-1. [47] SANTOS J R, FREITAS C C, ARAUJO L S, et al. Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest[J]. Remote Sensing of Environment, 2003, 87(4):482-493. DOI:10.1016/j.rse.2002.12.001. [48] WAGNER W, LUCKMAN A, Vietmeier J, et al. Large-scale mapping of boreal forest in SIBERIA using ERS tandem coherence and JERS backscatter data[J]. Remote Sensing of Environment, 2003, 85(2):125-144. DOI:10.1016/S0034-4257(02)00198-0. [49] VILLARD L, LE TOAN T. Relating P-Band SAR intensity to biomass for tropical dense forests in hilly terrain: γ0 or t0?[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(1):214-223. DOI:10.1109/JSTARS.2014.2359231. [50] RIGNOT E, WAY J, WILLIAMS C, et al. Radar estimates of aboveground biomass in boreal forests of interior Alaska[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(5):1117-1124. DOI:10.1109/36.312903. [51] SOJA M J, SANDBERG G, ULANDER L M H. Regression-based retrieval of boreal forest biomass in sloping terrain using P-band SAR backscatter intensity data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(5):2646-2665. DOI:10.1109/TGRS.2012.2219538. [52] SANTORO M, ASKNE J, SMITH G, et al. Stem volume retrieval in boreal forests from ERS-1/2 interferometry[J]. Remote Sensing of Environment, 2002, 81(1):19-35. DOI:10.1016/S0034-4257(01)00329-7. [53] CARTUS O, SANTORO M, KELLNDORFER J. Mapping forest aboveground biomass in the northeastern United States with ALOS PALSAR dual-polarization L-band[J]. Remote Sensing of Environment, 2012, 124:466-478. DOI:10.1016/j.rse.2012.05.029. [54] METTE T, HAJNSEK I, PAPATHANASSIOU K. Height-biomass allometry in temperate forests performance accuracy of height-biomass allometry[C]//Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium. Toulouse, France:IEEE, 2003:1942-1944. DOI:10.1109/IGARSS.2003.1294300. [55] METTE T, PAPATHANASSIOU K, HAJNSEK I, et al. Applying a common allometric equation to convert forest height from Pol-InSAR data to forest biomass[C]//Proceedings of 2004 IEEE International Geoscience and Remote Sensing Symposium. Anchorage, AK, USA:IEEE, 2004:272. DOI:10.1109/IGARSS.2004.1369013. [56] CAICOYA A T, KUGLER F, PRETZSCH H, et al. Forest vertical structure characterization using ground inventory data for the estimation of forest aboveground biomass[J]. Canadian Journal of Forest Research, 2016, 46(1):25-38. DOI:10.1139/cjfr-2015-0052. [57] CAICOYA A T, PARDINI M, HAJNSEK I, et al. Forest above-ground biomass estimation from vertical reflectivity profiles at L-band[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(12):2379-2383. DOI:10.1109/LGRS.2015.2477858. [58] 朱建军, 付海强, 汪长城. InSAR林下地形测绘方法与研究进展[J]. 武汉大学学报(信息科学版), 2018, 43(12):2030-2038. DOI:10.13203/j.whugis20180266. ZHU Jianjun, FU Haiqiang, WANG Changcheng. Methods and research progress of underlying topography estimation over forest areas by InSAR[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):2030-2038. DOI:10.13203/j.whugis20180266. [59] LEI Yang, TREUHAFT R, GONÇALVES F. Automated estimation of forest height and underlying topography over a Brazilian tropical forest with single-baseline single-polarization TanDEM-X SAR interferometry[J]. Remote Sensing of Environment, 2021, 252:112132. DOI:10.1016/j.rse.2020.112132. [60] WANG Huiqiang, FU Haiqiang, ZHU Jianjun, et al. Estimation of subcanopy topography based on single-baseline TanDEM-X InSAR data[J]. Journal of Geodesy, 2021, 95(7):84. DOI:10.1007/s00190-021-01519-3. [61] ROTT H, SCHEIBLAUER S, WUITE J, et al. Penetration of interferometric radar signals in Antarctic snow[J]. The Cryosphere, 2021, 15(9):4399-4419. DOI:10.5194/tc-15-4399-2021. [62] HUANG Lanqing, HAJNSEK I. Polarimetric behavior for the derivation of sea ice topographic height from TanDEM-X interferometric SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 14:1095-1110. DOI:10.1109/JSTARS.2020.3036395. [63] SHARMA J J, HAJNSEK I, PAPATHANASSIOU K P, et al. Polarimetric decomposition over glacier ice using long-wavelength airborne PolSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(1):519-535. DOI:10.1109/TGRS.2010.2056692. [64] SHARMA J J, HAJNSEK I, PAPATHANASSIOU K P, et al. Estimation of glacier ice extinction using long-wavelength airborne Pol-InSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(6):3715-3732. DOI:10.1109/TGRS.2012.2220855. [65] FISCHER G, PAPATHANASSIOU K P, HAJNSEK I. Modeling and compensation of the penetration bias in InSAR DEMs of ice sheets at different frequencies[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13:2698-2707. DOI:10.1109/JSTARS.2020.2992530. [66] SHI J, DOZIER J. Estimation of snow water equivalence using SIR-C/X-SAR. I. Inferring snow density and subsurface properties[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(6):2465-2474. DOI:10.1109/36.885195. [67] SHI J, DOZIER J. Estimation of snow water equivalence using SIR-C/X-SAR. Ⅱ. Inferring snow depth and particle size[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(6):2475-2488. DOI:10.1109/36.885196. [68] ROTT H, CLINE D, DUGUAY C, et al. Scientific preparations for CoRe-H2O, a dual Frequency SAR mission for snow and ice observations[C]//Proceedings of 2008 IEEE International Geoscience and Remote Sensing Symposium. Boston, MA, USA:IEEE, 2008:Ⅲ-31-Ⅲ-34. DOI:10.1109/IGARSS.2008.4779275. [69] SHARMA J J, HAJNSEK I, PAPATHANASSIOU K P. Vertical profile reconstruction with Pol-InSAR data of a subpolar glacier[C]//Proceedings of 2007 IEEE International Geoscience and Remote Sensing Symposium. Barcelona, Spain:IEEE, 2007:1147-1150. DOI:10.1109/IGARSS.2007.4423006. [70] TEBALDINI S, FERRO-FAMIL L. High resolution three-dimensional imaging of a snowpack from ground-based SAR data acquired at X and Ku band[C]//Proceedings of 2013 IEEE International Geoscience and Remote Sensing Symposium. Melbourne, VIC, Australia:IEEE, 2013:77-80. DOI:10.1109/IGARSS.2013.6721096. [71] BANDA F, DALL J, TEBALDINI S. Single and multipolarimetric P-band SAR tomography of subsurface ice structure[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(5):2832-2845. DOI:10.1109/TGRS.2015.2506399. [72] TEBALDINI S, NAGLER T, ROTT H, et al. Imaging the internal structure of an alpine glacier via L-band airborne SAR tomography[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(12):7197-7209. DOI:10.1109/TGRS.2016.2597361. [73] FISCHER G, JÄGER M, PAPATHANASSIOU K P, et al. Modeling the vertical backscattering distribution in the percolation zone of the Greenland ice sheet with SAR tomography[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, 12(11):4389-4405. DOI:10.1109/JSTARS.2019.2951026. [74] SCHABER G G, MCCAULEY J F, BREED C S. The use of multifrequency and polarimetric SIR-C/X-SAR data in geologic studies of Bir Safsaf, Egypt[J]. Remote Sensing of Environment, 1997, 59(2):337-363. DOI:10.1016/S0034-4257(96)00143-5. [75] 郭华东, 刘浩, 王心源, 等. 航天成像雷达对阿拉善高原次地表古水系探测与古环境分析[J]. 中国科学(D辑), 2000, 30(1):88-96. GUO Huadong, LIU Hao, WANG Xinyuan, et al. Subsurface old drainage detection and paleoenvironment analysis using spaceborne radar images in Alxa Plateau[J]. Science in China Series D:Earth Sciences, 2000, 30(1):88-96. [76] ELSHERBINI A, SARABANDI K. Mapping of sand layer thickness in deserts using SAR interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(9):3550-3559. DOI:10.1109/TGRS.2010.2047110. [77] XIONG Siting, MULLER J P, LI Gang. The application of ALOS/PALSAR InSAR to measure subsurface penetration depths in deserts[J]. Remote Sensing, 2017, 9(6):638. DOI:10.3390/rs9060638. [78] LIU Guanxin, FU Haiqiang, ZHU Jianjun, et al. Penetration depth inversion in Hyperarid desert from L-Band insar data based on a coherence scattering model[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(11):1981-1985. DOI:10.1109/LGRS.2020.3011706. [79] FUNG A K, LI Zongqian, CHEN Kunshan. Backscattering from a randomly rough dielectric surface[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(2):356-369. DOI:10.1109/36.134085. [80] 王驰. 基于极化SAR的沙地土壤含水量反演方法研究[D]. 呼和浩特:内蒙古工业大学, 2017. WANG Chi. Study on inversion method of sandy land soil moisture based on polarimetric SAR[D]. Hohhot:Inner Mongolia University of Technology, 2017. [81] HAJNSEK I, POTTIER E, CLOUDE S R. Inversion of surface parameters from polarimetric SAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(4):727-744. DOI:10.1109/TGRS.2003.810702. [82] IODICE A, NATALE A, RICCIO D. Polarimetric two-scale model for soil moisture retrieval via dual-pol HH-VV SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6(3):1163-1171. DOI:10.1109/JSTARS.2013.2238893. [83] NATALE A, ESPOSITO C, BERARDINO P, et al. Retrieval of soil surface parameters via helicopter-borne P-band polarimetric SAR data acquired along antiparallel flight tracks[C]//Proceedings of 2019 IEEE International Geoscience and Remote Sensing Symposium. Yokohama, Japan:IEEE, 2019:7002-7005. DOI:10.1109/IGARSS.2019.8898168. [84] SCHABER G G. SAR studies in the Yuma Desert, Arizona:sand penetration, geology, and the detection of military ordnance debris[J]. Remote Sensing of Environment, 1999, 67(3):320-347. DOI:10.1016/S0034-4257(98)00093-5. [85] 陈其芬. 雷达探测干燥土壤中的地雷[J]. 电波与天线, 1996(4):22-27. CHEN Qifen. Radar detects ground in dry soil[J]. GNSS World of China, 1996(4):22-27. [86] GABER A, KOCH M, GRIESH M H, et al. SAR remote sensing of buried faults:implications for groundwater exploration in the western desert of egypt[J]. Sensing and Imaging:An International Journal, 2011, 12(3-4):133-151. DOI:10.1007/s11220-011-0066-1. [87] MCCAULEY J F, SCHABER G G, BREED C S, et al. Subsurface valleys and geoarcheology of the eastern Sahara revealed by shuttle radar[J]. Science, 1982, 218(4576):1004-1020. DOI:10.1126/science.218.4576.1004. [88] PAILLOU P, SCHUSTER M, TOOTH S, et al. Mapping of a major paleodrainage system in eastern Libya using orbital imaging radar:the Kufrah River[J]. Earth and Planetary Science Letters, 2009, 277(3-4):327-333. DOI:10.1016/j.epsl.2008.10.029. [89] GABER A, KOCH M, GRIESH M H, et al. Near-surface imaging of a buried foundation in the Western Desert, Egypt, using space-borne and ground penetrating radar[J]. Journal of Archaeological Science, 2013, 40(4):1946-1955. DOI:10.1016/j.jas.2012.12.019. |
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