收稿：2016-06-13，
录用：2016-12-28，
纸质出版：2017-05
移动端阅览
利用GNSS-R(Global Navigation Satellite System-Reflectometry)技术探测土壤水分是近年来一个新兴的研究方向。目前GNSS-R遥感观测中反射信号的接收与处理方式包括单天线与多天线两种模式，面向实际应用需求，GNSS-R遥感正在实现从最初的地基观测向空基、星载观测的转变。在推进GNSS-R土壤水分遥感技术业务化应用的过程中，必须首先进行适宜性分析，确定该技术探测的地理位置、空间分辨率与探测深度，然而目前对此尚未有系统、全面、定量的论述。本文针对适宜性分析中的3个关键因子分别进行理论分析与公式推导，明确相关概念的定义，并实现定量化描述，最终通过实际应用分析进一步诠释其应用价值。对于单天线模式地基观测，以美国板块边界观测计划PBO (Plate Boundary Observatory)土壤水分产品为例，分析镜面反射点的相对位置、第一级Fresnel反射椭圆簇的面积与时间序列土壤水分所代表的探测深度；对于多天线模式，以郑州上街区农田空基观测试验为例，得到基于航迹的栅格土壤水分空间分布并探讨其探测深度。本文能够为未来两种观测模式下地基、空基和星载GNSS-R遥感观测、北斗反射信号遥感，以及GNSS-R在农业、水文、生态等领域的实际应用提供理论指导。
Soil moisture measurements are important to hydrology
climatology
and agriculture. Global Navigation Satellite System reflectometry (GNSS-R) is a new and powerful tool for sensing soil moisture. Different methods have been proposed for the reception and processing of reflected signals
such as multiantenna and single-antenna patterns. Considerable efforts have been made on ground-based and airborne observations. Meanwhile
a number of space-borne missions have also been implemented. During the suitability analysis of soil moisture remote sensing via GNSS-R technique
three key factors have to be determined—the specular reflection point
spatial pixel size
and sensing depth in the soil—regardless of the extraction methods of the reflected signals or the types of the observation platform. However
no relatively comprehensive explanations are available in the current literature. Theoretical analysis and formula derivation are conducted to systematically and quantitatively determine the extent of soil detection in three dimensions from the abovementioned aspects. First
the geographical position of the specular reflection point on the WGS84 ellipsoid surface is determined with an iterative algorithm. The effect of elevation between the real ground surface and the ellipsoid is discussed. Second
the first Fresnel zone is defined as the spatial pixel of the GNSS-R technique. The size of the pixel is regarded as the spatial resolution based on the concept of the equi-delay ellipse. Thirdly
the penetration distance of GNSS signals in soil is expressed. The concept of sensing depth is proposed on penetration distance and is based on the theory of microwave remote sensing. This concept makes soil moisture detection more describable and comparable. To further analyze the feasibility of soil moisture remote sensing with GNSS-R
the results of two application scenarios are shown: (1) A ground-based GPS measurement was performed in Marshall
Colorado
US
from the Plate Boundary Observatory. This measurement corresponds to the single-antenna pattern. The relative location of the specular reflection points
average area of the first Fresnel ellipse clusters
and sensing depth of the time-series soil moisture are analyzed. (2)An airborne GNSS-R experiment was conducted in Zhengzhou to obtain soil moisture content. This measurement corresponds to the multiantenna pattern. The spatial distribution of estimated soil moisture with a certain resolution based on flight tracks and relevant sensing depth are manifested. The results of the ground-based GPS measurement and airborne GNSS-R experiment are reasonable and convincing. Given that this study determined the extent of detected soil in three dimensions
this work provides theoretical basis for the precision evaluation of retrieved soil moisture. BeiDou mainly differs from GPS in the carrier frequency for remote sensing using GNSS reflected signals. Therefore
the results of this study provide references for future development of the BeiDou-R technique in China.
Alonso-Arroyo A, Forte G, Camps A, Park H, Pascual D, Onrubia R and Jove-Casulleras R. 2013. Soil Moisture mapping using forward scattered GPS L1 signals // Proceedings of 2013 IEEE International Geoscience and Remote Sensing Symposium. Melbourne, VIC: IEEE: 354–357
Alonso-Arroyo A, Camps A, Monerris A, Rüdiger C, Walker J P, Forte G, Pascual D, Park H and Onrubia R. 2014. The light airborne reflectometer for GNSS-R observations (LARGO) instrument: initial results from airborne and Rover field campaigns // Proceedings of 2014 IEEE International Geoscience and Remote Sensing Symposium. Quebec City, QC: IEEE: 4054–4057
Alonso-Arroyo A, Torrecilla S, Querol J, Camps A, Pascual D, Park H and Onrubia R. 2015. Two dedicated soil moisture experiments using the scatterometric properties of GNSS-reflectometry // Proceedings of 2015 IEEE International Geoscience and Remote Sensing Symposium. Milan: IEEE: 3921–3924
敖敏思, 朱建军, 胡友健, 曾云, 刘亚东. 2015. 利用SNR观测值进行GPS土壤湿度监测. 武汉大学学报(信息科学版), 40(1): 117–120, 127
Ao M S, Zhu J J, Hu Y J, Zeng Y and Liu Y D. 2015. Comparative experiments on soil moisture monitoring with GPS SNR observations. Geomatics and Information Science of Wuhan University, 40(1): 117–120, 127
Chew C, Shah R, Zuffada C, Hajj G, Masters D and Mannucci A J. 2016. Demonstrating soil moisture remote sensing with observations from the UK TechDemoSat-1 satellite mission. Geophysical Research Letters, 43(7): 3317–3324
Egido A, Caparrini M, Ruffini G, Paloscia S, Santi E, Guerriero L, Pierdicca N and Floury N. 2012. Global navigation satellite systems reflectometry as a remote sensing tool for agriculture. Remote Sensing, 4(8): 2356–2372
Egido A, Paloscia S, Motte E, Guerriero L, Pierdicca N, Caparrini M, Santi E, Fontanelli G and Floury N. 2014. Airborne GNSS-R polarimetric measurements for soil moisture and above-ground biomass estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(5): 1522–1532
Garrison J L, Cardellach E, Gleason S and Katzberg S. 2014. Foreword to special issue on reflectometry using global navigation satellite systems and other signals of opportunity (GNSS+R). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(5): 1412–1415
Gleason S. 2006. Detecting bistatically reflected GPS signals from low earth orbit over land surfaces // Proceedings of 2006 IEEE International Symposium on Geoscience and Remote Sensing. Denver, CO, USA: IEEE: 3069–3072 [DOI: 10.1109/IGARSS.2006.792]
关止, 赵凯, 宋冬生. 2006. 利用反射GPS信号遥感土壤湿度. 地球科学进展, 21(7): 747–750
Guan Z, Zhao K and Song D S. 2006. Measuring soil moisture using reflected GPS signals. Advances in Earth Science, 21(7): 747–750
Hallikainen M T, Ulaby F T, Dobson M C, EL-Rayes M A and Wu L K. 1985. Microwave dielectric behavior of wet soil-part 1: empirical models and experimental observations. IEEE Transactions on Geoscience and Remote Sensing, GE-23(1): 25–34
Jales P and Unwin M. 2015. Mission Description-GNSS Reflectometry on TDS-1 with the SGR-ReSI. Guildford, UK: Surrey Satellite Technology Ltd
Jin S G, Feng G P and Gleason S. 2011. Remote sensing using GNSS signals: current status and future directions. Advances in Space Research, 47(10): 1645–1653
Jin S G and Komjathy A. 2010. GNSS reflectometry and remote sensing: new objectives and results. Advances in Space Research, 46(2): 111–117
Kaplan E and Hegarty C. 2005. Understanding GPS: Principles and Applications. 2nd ed. Norwood: Artech House: 32–34
Katzberg S J and Garrison J L. 1996. Utilizing GPS to Determine Ionospheric Delay over the Ocean. [s.l.]: National Aeronautics and Space Administration Langley Research Center: 1–16
Katzberg S J, Torres O, Grant M S and Masters D. 2006. Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: results from SMEX02. Remote Sensing of Environment, 100(1): 17–28
Larson K M, Braun J J, Small E E, Zavorotny V U, Gutmann E D and Bilich A L. 2010. GPS multipath and its relation to near-surface soil moisture content. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(1): 91–99
李黄, 夏青, 尹聪, 万玮. 2013. 我国GNSS-R遥感技术的研究现状与未来发展趋势. 雷达学报, 2(4): 389–399
Li H, Xia Q, Yin C and Wan W. 2013. The current status of research on GNSS-R remote sensing technology in China and future development. Journal of Radars, 2(4): 389–399
刘经南, 邵连军, 张训械. 2007. GNSS-R研究进展及其关键技术. 武汉大学学报(信息科学版), 32(11): 955–960
Liu J N, Shao L J and Zhang X X. 2007. Advances in GNSS-R studies and key technologies. Geomatics and Information Science of Wuhan University, 32(11): 955–960
毛克彪, 王建明, 张孟阳, 唐华俊, 周清波. 2009. 基于AIEM和实地观测数据对GNSS-R反演土壤水分的研究. 高技术通讯, 19(3): 295–301
Mao K B, Wang J M, Zhang M Y, Tang H J and Zhou Q B. 2009. The study of soil moisture retrieval from GNSS-R signals based on AIEM model and experiment data. Chinese High Technology Letters, 19(3): 295–301
Martín-Neira M, D’Addio S, Buck C, Floury N and Prieto-Cerdeira R. 2011. The PARIS ocean altimeter in-orbit demonstrator. IEEE Transactions on Geoscience and Remote Sensing, 49(6): 2209–2237
Masters D, Axelrad P and Katzberg S. 2004. Initial results of land-reflected GPS bistatic radar measurements in SMEX02. Remote Sensing of Environment, 92(4): 507–520
Rodriguez-Alvarez N, Bosch-Lluis X, Camps A, Vall-Llossera M, Valencia E, Marchan-Hernandez J F and Ramos-Perez I. 2009. Soil moisture retrieval using GNSS-R techniques: experimental results over a bare soil field. IEEE Transactions on Geoscience and Remote Sensing, 47(11): 3616–3624
宋学忠, 徐爱功, 杨东凯, 马小东. 2013. GNSS反射信号在土壤湿度测量中的应用. 测绘通报, (11): 61–64
Song X Z, Xu A G, Yang D K and Ma X D. 2013. Details of soil moisture measuring utilizing GNSS reflected signals. Bulletin of Surveying and Mapping, (11): 61–64
Torres O. 2004. Analysis of Reflected Global Positioning System Signals as a Method for the Determination of Soil Moisture. El Paso: University of Texas at El Paso: 6–33
Troglia Gamba M, Marucco G, Pini M, Ugazio S, Falletti E and Lo Presti L. 2015. Prototyping a GNSS-based passive radar for uavs: an instrument to classify the water content feature of lands. Sensors, 15(11): 28287–28313
Ulaby F T, Moore R K and Fung A K. 1981. Microwave Remote Sensing: Active and Passive, Volume 1: Microwave Remote Sensing Fundamentals and Radiometry. Norwood: Artech House: 40–60
Ulaby F T, Moore R K and Fung A K. 1986a. Microwave Remote Sensing: Active and Passive, Volume II: Radar Remote Sensing and Surface Scattering and Emission Theory. Norwood: Artech House: 844–847
Ulaby F T, Moore R K and Fung A K. 1986b. Microwave Remote Sensing: Active and Passive Volume III: From Theory to Applications. Norwood: Artech House: 1523–1524
Wan W, Bai W H, Zhao L M, Long D, Sun Y Q, Meng X G, Chen H, Cui X and Hong Y. 2015. Initial results of China’s GNSS-R airborne campaign: soil moisture retrievals. Science Bulletin, 60(10): 964–971
万玮, 李黄, 洪阳, 陈秀万, 彭学峰. 2015. GNSS-R遥感观测模式及陆面应用. 遥感学报, 19(6): 882–893
Wan W, Li H, Hong Y, Chen X W and Peng X F. 2015. Toward the patterns of GNSS-R observations: definition and application. Journal of Remote Sensing, 19(6): 882–893
Wickert J, Andersen O B, Beyerle G, Chapron B, Cardellach E, D’Addio S, Foerste C, Gommenginger C, Gruber T, Helm A, Hess M, Hoeg P, Jaeggi A, Jakowski N, Kern M, Lee T, Martin-Neira M, Montenbruck O, Pierdicca N, Rius A, Rothacher M, Shum C and Zuffada C. 2013. GEROS-ISS: innovative GNSS reflectometry/ occultation payload onboard the International Space Station for the Global Geodetic Observing System //Proceedings of 2013 AGU Fall Meeting Abstracts. [s.l.]: AGU: 0871
严颂华, 龚健雅, 张训械, 李冻秀. 2011. GNSS-R测量地表土壤湿度的地基实验. 地球物理学报, 54(11): 2735–2744
Yan S H, Gong J Y, Zhang X X and Li D X. 2011. Ground based GNSS-R observations for soil moisture. Chinese Journal of Geophysics, 54(11): 2735–2744
杨磊, 吴秋兰, 张波, 梁勇, 洪学宝, 邹文博. 2016. SVRM辅助的北斗GEO卫星反射信号土壤湿度反演方法. 北京航空航天大学学报, 42(6): 1134–1141
Yang L, Wu Q L, Zhang B, Liang Y, Hong X B and Zou W B. 2016. SVRM-assisted soil moisture retrieval method using reflected signal from BeiDou GEO satellites. Journal of Beijing University of Aeronautics and Astronautics, 42(6): 1134–1141
张晓娟, 张文吉, 路晓荣, 康高健, 方广有. 2007. 双频多极化SAR测量深层土壤湿度. 电子与信息学报, 29(11): 2711–2714
Zhang X J, Zhang W J, Lu X R, Kang G J and Fang G Y. 2007. Dual-frequency synthetic aperture radar for deep soil moisture estimation. Journal of Electronics & Information Technology, 29(11): 2711–2714
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