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遥感技术与应用  2017, Vol. 32 Issue (6): 983-997    DOI: 10.11873/j.issn.1004-0323.2017.6.0983
综述     
干涉、极化干涉SAR技术森林高度估测算法研究进展
张王菲1,2,陈尔学1,李增元1,赵磊1,姬永杰2
(1.中国林业科学研究院资源信息研究所,北京 100091;
2.西南林业大学林学院,云南 昆明 650224)
Development of Forest Height Estimation Using InSAR/PolInSAR Technology
Zhang Wangfei1,2,Chen Erxue1,Li Zengyuan1,Zhao Lei1,Ji Yongjie2
(1.Institute of Forest Resources Information Technique,Chinese Academy of Forestry,Beijing 100091,China;
2.Forestry College, Southwest Forestry University,Kunming 650224,China)
 全文: PDF(1339 KB)  
  
摘要:
在干涉、极化干涉SAR森林高度估测中,估测算法对结果精度起着决定性作用。通过对现有森林高度干涉、极化干涉SAR研究的系统性分析,总结了现有研究中森林高度估测算法的基本原理、模型假设及其应用局限性,并对这些算法在区域和全球尺度森林高度反演中的潜力进行了分析。总结发现,基于干涉SAR技术的DSM\|DEM差分法在森林高度反演中精度较高,与极化干涉SAR算法相比,受到森林类型、结构的影响较小,在区域和全球尺度森林高度反演中具有很大潜力。但是其局限性在于是否能够获取大范围高精度的DEM;极化干涉SAR技术利用了森林的极化散射特点,不受DEM的限制,可以大范围地进行森林高度反演,但是在森林异质性大的区域,仍然需要进一步分析森林特征对不同波长相位及相干幅度的影响,根据森林的微波散射原理拓展微波散射模型,才能进一步提高估测结果和精度。此外,由于单基线干涉SAR、极化干涉SAR对森林垂直结构可见性差,因此,发展多维度、多基线SAR及其相应算法并朝这个方向拓展是未来采用干涉SAR、极化干涉SAR进行森林高度反演的主要方向。
关键词: 干涉SAR极化干涉SAR森林高度估测反演    
Abstract: Forest height estimation is one of the hottest research areas of InSAR/PolInSAR technology within its 30 years’ development.Estimation algorithms play an important role in the forest height assessment by InSAR/PolInSAR technologies.This paper systematically reviewed the basic theories,model assumptions and then summarized the limitation and potential of these algorithms applied in forest height estimation,especially performed in regional or global scale.It also deliberated the intrinsic characteristics of these algorithms like DEM difference method,three\|stage inversion process,coherence amplitude method and so on.Analysis showed that the estimation results of DEM difference method had higher accuracy and less influence from forest types and structure.So it had great potential for global and regional forest height assessment,however,it was limited by the requirement of high accuracy DEM data in those area.The result accuracy of algorithms based on PolInSAR depended more on forest types,structures and also the robust of forest scattering models.It had no restriction of DEM and could perform in global and regional scale,but for the forest area with great heterogeneous,model and algorithm suitability and robust need to further studying.Besides,for the poor penetration of single\|baseline InSAR/PolInSAR,we should focus more on multi\|dimension,multi\|baseline technique for InSAR/PolInSAR application development in the future.
Key words: InSAR    PolInSAR    Forest height    Estimation    Inversion
收稿日期: 2016-12-16 出版日期: 2018-03-08
:  TP 79  
基金资助: 国家973计划项目“复杂地表遥感信息动态分析与建模”(2013CB733400 )。

通讯作者: 李增元(1959-),男,内蒙古呼和浩特人,研究员,主要从事林业微波遥感研究。Email: zy@caf.ac.cn。   
作者简介: 张王菲(1979-),女,山西阳城人,副教授,主要从事SAR技术应用研究。Email:mewhff@163.com。
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引用本文:

张王菲,陈尔学,李增元,赵磊,姬永杰. 干涉、极化干涉SAR技术森林高度估测算法研究进展[J]. 遥感技术与应用, 2017, 32(6): 983-997.

Zhang Wangfei,Chen Erxue,Li Zengyuan,Zhao Lei,Ji Yongjie. Development of Forest Height Estimation Using InSAR/PolInSAR Technology. Remote Sensing Technology and Application, 2017, 32(6): 983-997.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2017.6.0983        http://www.rsta.ac.cn/CN/Y2017/V32/I6/983

[1]Liu Qingwang,Tan Bingxiang,Hu Kailong,et al.The Remote [HJ2mm]Sensing Experiment on Airborne LiDAR and Hyperspectral Integrated System for Subtropical Forest Estimation[J].High Technology Letters,2016,26(3):264-274.[刘清旺,谭炳香,胡凯龙,等.机载激光雷达和高光谱组合系统的亚热带森林估测遥感试验[J].高技术通讯,2016, 26(3):264-274.]
[2]Yin Weilun.Advances in the Relationship between Forest and Environment in the World[J].Journal of Forest and Environment,2015,(1):1-7.[尹伟伦.全球森林与环境关系研究进展[J].福建林学院学报,2015,(1):1-7.]
[3]Zhao Haifeng,Yan Yulin,Zhang Caihong,et al.Three Modes Involved in Forest Carbon Cycle:Mechanism and Selection[J].Scientia Silvae Sinicae, 2014, 50(10):134-139.[赵海凤,闫昱霖,张彩虹,等.森林参与碳循环的3种模式:机制与选择[J].林业科学,2014, 50(10):134-139.]
[4]Kugler F,Lee S K,Hajnsek I,et al.Forest Height Estimation by Means of Pol-InSAR Data Inversion:The Role of the Vertical Wavenumber[J].IEEE Transactions on Geoscience & Remote Sensing,2015,53 (10):5294-5311.
[5]Mu Xiyun,Zhang Qiuling,Liu Qingwang,et al.Typical Forest Height Mapping in Cold Temperate Zone Using Airborne LiDAR Data[J].Journal of Beijing Forestry University, 2015, 37(7):58-67.[穆喜云,张秋良,刘清旺,等.基于机载激光雷达的寒温带典型森林高度制图研究[J].北京林业大学学报,2015,37(7):58-67.]
[6]Luo Huanmin,Chen Erxue,Chen Jian,et al.Forest Height Estimation Methods Using Polarimetric SAR Interferometry[J].Journal of Remote Sensing,2010,14(4):806-821.[罗环敏,陈尔学,程建,等.极化干涉SAR森林高度反演方法研究[J].遥感学报,2010,14(4):806-821.]
[7]Feng Qi,Chen Erxue,Li Zengyuan,et al.Forest Height Estimation from Airborne X-band Single-pass InSAR Data[J].Remote Sensing Technology and Application,2016,31(3):551-557.[冯琦,陈尔学,李增元,等.机载X-波段双天线InSAR数据森林树高估测方法[J].遥感技术与应用,2016,31(3):551-557.]
[8]Luo Huanmin.Models and Methods of Extracting Forest Structure Information by Polarimetric SAR Interferometry[D].Chengdu: University of Electronic Science and Technology of China,2011 [罗环敏.基于极化干涉SAR的森林结构信息提取模型与方法[D].成都:电子科技大学,2011.]
[9]Balzter H,Luckman A,Skinner L C,et al.Observations of Forest Stand Top Height and Mean Height from Interferometric SAR and LiDAR over a Conifer Plantation at Thetford Forest,UK[J].International Journal of Remote Sensing,2007,28 (6):1173-1197.
[10]Kaasalainen S,Holopainen M,Karjalainen M,et al.Combining LiDAR and Synthetic Aperture Radar Data to Estimate Forest Biomass:Status and Prospects[J].Forests,2015,6(1):252-270.
[11]Wang Chao,Zhang Hong,Liu Zhi.Spaceborne Synthetic Aperture Radar Interferometry[M].Beijing:Science Press,2003.[王超,张红,刘智.星载合成孔径雷达干涉测量[M].北京:科学出版社,2003.]
[12]Cloude S R.Polarization Applications in Remote Sensing[M].New York:Oxford University Press,2009.
[13]Karamvasis K,Karathanassi V.Forest Canopy Height Estimation Using Double-frequency Repeat Pass Interferometry[C]//International Conference on Remote Sensing and Geoinformation of the Environment.Cyprus:2015.
[14]Kaasalainen S,Holopainen M,Karjalainen M,et al.Combining LiDAR and Synthetic Aperture Radar Data to Estimate Forest Biomass:Status and Prospects[J].Forests,2015,6(1):252-270.
[15]Neeff T,Dutra L V,Jrdos S,et al.Tropical Forest Measurement by Interferometric Height Modeling and P-Band Radar Backscatter[J].Forest Science,2006,51(6):585-594.
[16]Praks J,Antropov O,Hallikainen M T.LiDAR-Aided SAR Interferometry Studies in Boreal Forest:Scattering Phase Center and Extinction Coefficient at X- and L-band[J].IEEE Transactions on Geoscience & Remote Sensing,2012,50(10):3831-3843
[17]Kenyi L W,Dubayah R,Hofton M,et al.Comparative.Analysis of SRTM-Ned Vegetation Canopy Height to LiDAR-derived Vegetation Canopy Metrics[J].International Journal of Remote Sensing,2009,30(11):2797-2811.
[18]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.
[19]Papathanassiou K P,Cloude S R.Single-baseline Polarimetric SAR Interferometry[J].IEEE Transactions on Geoscience & Remote Sensing,2001,39(11): 2352-2363.
[20]Cloude S R,Papathanassiou K P.Polarimetric SAR Interferometry[J].IEEE Transactions on Geoscience & Remote Sensing,1998,36(5):1551-1565.
[21]Shane R.Cloude.Polarization Coherence Tomography[J].Radio Science,2006,41(4):495-507.
[22]Bamler R,Hartl P.Topical Review:Synthetic Aperture Radar Interferometry[J].Inverse Problems,1998,14 (4):333-382.
[23]Dammert P B,Ulander L M,Askne J.SARInterferometry for Detecting Forest Stands and Tree Heights.Satellite Remote Sensing II[J].Proceedings of the SPIE,1995,2584(4):384-390.
[24]Krieger G,Zink M,Bachmann M,et al.Tandem-X:A Radar Interferometer with Two Formation-flying Satellites [J].Acta Astronautica,2013,89 (8):83-98.
[25]Kugler F,et al.TanDEM-X Pol-InSAR Performance for Forest Height Estimation[J].IEEE Transactions on Geoscience & Remote Sensing 2014,52(10):6404-6422.
[26]Krieger M G,Fiedler A,et al.Tandem-X:A Satellite Formation for High-resolution SAR Interferometry [J].IEEE Transactions on Geoscience & Remote Sensing,2007,45(11):3317-3341.
[27]Ferro-Famil L,Huang Y,Pottier E.Principles and Applications of Polarimetric SAR Tomography for the Characterization of Complex Environments[M].New York:Springer International Publishing,2015.
[28]López-Martiínez C,Alonso A,Fàbregas X,et al.Ground Topography Estimation over Forests Considering Polarimetric SAR Interferometry[J].Recercat Principal,2010,38(1):3612-3615.
[29]Lopez-Martinez C,Papathanassiou P,Alonso A,et al.Separation of Scattering Contributions in Polarimetric SAR Interferometry[C]//Frascati:ESA POLInSAR Workshop,2011.
[30]Yamada H,Yamaguchi Y,Rodriguez E,et al.Polarimetric SAR Interferometry for Forest Canopy Analysis by Using the Super-resolution Method[C]//IEEE Geoscience and Remote Sensing Symposium,Sydney,2001.
[31]Yamada H,Sato K,Yamaguchi E,et al.Interferometric Phase and Coherence of Forest Estimated by ESPRIT-based polarimetric SAR interferometry[C]//IEEE Geoscience and Remote Sensing Symposium,Toronto,2002.
[32]Askne J,Santoro M.MultitemporalRepeat Pass SAR Interferometry of Boreal Forests[J].IEEE Transactions on Geoscience & Remote Sensing,2003,41(6):1540-1550.
[33]Askne J,Santoro M.Selection of Forest Stands for Stem Volume Retrieval from Stable ERS Tandem InSAR Observations[J].IEEE Geoscience & Remote Sensing Letters,2007,4(1):46-50.[JP]
[34]Yang Zhen.Studies on Synthetic Aperture Radar Interferometric and Polarimetric Interferometric Techniques[D].Beijing:Institute of Electrics,Chinese Academy of Sciences,2003.[杨震.合成孔径雷达干涉与极化干涉技术研究[D].北京:中国科学院电子学研究所,2003.]
[35]Li Xinwu,Guo Huadong,Liao Jingjuan,et al.Inversion of Vegetation Parameters Using Spaceborne Polarimetric SAR Interferometry[J].Journal of Remote Sensing,2002,6(6):424-429.[李新武,郭华东,廖静娟,等.航天飞机极化干涉雷达数据反演地表植被参数[J].遥感学报,2002,6(1):424-429.]
[36]Yu Dayang,Dong Guiwei,Yang Jian,et al.Forest Tree Height Estimates based on Polarimetric SAR Interferometry[J].Journal of Tsinghua University (Science and Technology),2005,45(3):334-336.[于大洋,董贵威,杨健,等.基于干涉极化SAR数据的森林树高反演[J].清华大学学报(自然科学版),2005,45(3):334-336.]
[37]Chen Xi,Zhang Hong,Wang Chao.The Inversion of Vegetation Structural Parameters Using Dual-baseline Polarimetric SAR Interferometry[J].Remote Sensing for Land & Resources,2009,21(4):49-52.[陈曦,张红,王超.极化干涉SAR反演植被垂直结构剖面研究[J].国土资源遥感,2009,21(4):49-52.]
[38]Ni W J,Guo Z F,Sun G Q,et al.Investigation of Forest Height Retrieval Using SRTM-Dem and Aster-GDEM[C]//IEEE Geoscience and Remote Sensing Symposium,Hawaii,2010.
[39]Sun G,Ranson K J,Kharuk V I.Forest Biomass Estimation in Western Sayani Mountains,Siberia from SAR Data[C]//IEEE Geoscience and Remote Sensing Symposium,Hawaii,2000.
[40]Li Zhe.Inversion of Mean Forest Height Using Polarimetric SAR Interferometry[D].Lanzhou:Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy of Science,2009.[李哲.基于极化干涉SAR的森林平均树高反演算法研究[D].兰州:中国科学院寒区旱区环境与工程研究所,2009.]
[41]Chen Erxue,Li Zengyuan,Pang Yong,et al.Polarimetric Synthetic Aperture Radar Interferometry based Mean Tree Height Extraction Technique[J].Scientia Silvae Sinicae,2007,43(4):66-70.[陈尔学,李增元,庞勇,等.基于极化合成孔径雷达干涉测量的平均树高提取技术[J].林业科学,2007,43(4):66-70.]
[42]Li Wenmei,Li Zengyuan,Chen Erxue,et al.Status and Development of Tomographic SAR for Forest Vertical Structural Parameters Inversion[J].Journal of Remote Sensing,2014,18(4):741-751.[李文梅,李增元,陈尔学,等.层析SAR反演森林垂直结构参数现状及发展趋势[J].遥感学报,2014,18(4):741-751.]
[43]Liu Qian,Yang Le,Liu Qinhuo,et al,Review of Forest above Ground Biomass Inversion Methods based on Remote Sensing Technology[J].Journal of Remote Sensing,2015,19(1):62-74.[刘茜,杨乐,柳钦火,等.森林地上生物量遥感反演方法综述[J].遥感学报,2015,19(1):62-74.]
[44]Balzter H,Rowland C S,Saich P.Forest Canopy Height and Carbon Estimation at Monks Wood National Nature Reserve,UK,Using Dual-wavelength SAR Interferometry[J].Remote Sensing of Environment,2007,108(3):224-239.
[45]Rignot E.Dual-frequency Interferometric SAR Observations of a Tropical Rain-forest[J].Geophysical Research Letters,1996,23(3):993-996.
[46]Pang Yong,Li Zengyuan,Chen Erxue,et al.InSAR Technology and Its Application to Estimate Stand Average Height[J].Journal of Remote Sensing,2003,7(1):8-13.[庞勇,李增元,陈尔学,等.干涉雷达技术用于林分高估测[J].遥感学报,2003,(1):8-13.]
[47]Rodriguez E,Ruiz P L,Michael S,et al.Mapping Height and Biomass of Mangrove Forests in Everglades National Park with SRTM Elevation Data[J].Photogrammetric Engineering & Remote Sensing,2006,72(3):299-311.
[48]Solberg S,Astrup R,Weydahl D J.Detection of Forest Clear-Cuts with Shuttle Radar Topography Mission (SRTM)and Tandem-X InSAR Data[J].Remote Sensing,2013,5(4):549-550.
[49]Garestier F,Dubois-Fernandez  P C,Champion I.Forest Height Inversion Using High-resolution P-band Pol-InSAR Data[J].IEEE Transactions on Geoscience & Remote Sensing,2008,46(11): 3544-3559.
[50]Cloude S  R,Papathanassiou K P.Polarimetric Optimisation in Radar Interferometry[J].Electronics Letters,1997,33(13):1176-1178.
[51]Romena R  T,Cloude S R.On the Role of Coherence Optimization in Polarimetric SAR Interferometry[M].Australia:Practice,2005.
[52]Colin E,Titin-Schnaider C,Tabbara W.Coherence Optimization Methods for Scattering Centers Separation in Polarimetric Interferometry[J].Journal of Electromagnetic Waves & Applications,2005,19(9):1237-1250.
[53]Colin E,Titin-Schnaider C,Tabbara W.AnInterferometric Coherence Optimization Method in Radar Polarimetry for High-Resolution Imagery[J].IEEE Transactions on Geoscience & Remote Sensing,2006,44(1):167-175.
[54]Tabb M,Carand R.RobustInversion of Vegetation Structure Parameters from Low-frequency[C]//IEEE Geoscience and Remote Sensing Symposium,Sydney,2001.
[55]Tabb M,Flynn T,Carande R.An Extended Model for Characterizing Vegetation Canopies Using Polarimetric SAR Interferometry[C]//IEEE Geoscience and Remote Sensing Symposium,Toronto,2002.
[56]Gomezdans J L,Quegan S.Constraining Coherence Optimisation in Polarimetric Interferometry of Layered Targets[C]//POLinSAR Workshop.Frascati:ESA Pub,2005.
[57]Carande M.Phase Diversity:A Decomposition for Vegetation Parameter Estimation Using Polarimetric SAR Interferometry[C]//Proceedings of 4th European Synthetic Aperture Radar Conference.Cologne:Proc. EUSAR,2002.
[58]Yamada H,Yamaguchi Y,Kim Y,et al.Polarimetric SAR Interferometry for Forest Analysis based on the Esprit Algorithm [J].IEEE Transactions on Electronics,2001,84(12):1917-1924.
[59]Treuhaft R N,Cloude S R.The Structure of Oriented Vegetation from Polarimetric Interferometry[J].IEEE Transactions on Geoscience & Remote Sensing,1999,37(5):2620-2624.[60]Kellndorfer J,Walker W,Pierce L,et al.Vegetation Height Estimation from Shuttle Radar Topography Mission and National Elevation Datasets[J].Remote Sensing of Environment,2004,93(3):339-358.
[61]Wu Yaqing,Zhu Jianjun,Fu Haiqiang,et al.Three-stage of Polarimetric Interferometric Coherence Optimizational Vegetation Height Inversion Process[J].Bulletin of Surveying and Mapping,2016,(5):32-35.[伍雅晴,朱建军,付海强,等.引入PD极化相干最优的三阶段植被高度反演算法[J].测绘通报,2016,(5):32-35.]
[62]Tan Lulu,Yang Libo,Yang Ruliang,et al.Investigation of Tree Height Retrieval with Polarimetric SAR Interferometry based on ESPRIT Algorithm[J].Acta Geodaetica et Cartographica Sinica,2011,40(3):296-300.[谈璐璐,杨立波,杨汝良.基于ESPRIT算法的极化干涉SAR植被高度反演研究[J].测绘学报,2011,40(3):296-300.]
[63]Fan Mingyi.Nghia.Research on Forest Height Estimation from Polarimetric SAR Interferometry Images[D].Harbin:Harbin Institute of Technology,2014.[范明义.极化干涉SAR图像森林高度估计算法研究[D].哈尔滨:哈尔滨工业大学,2014.][JP]
[64]Feng Qi.Forest Structure Parameters Estimation based on Airborne X-band Single-pass InSAR Data[D].Beijing:Chinese Academy of Forestry,2015.[冯琦.机载X-波段双天线干涉SAR森林结构参数估测方法[D].北京:中国林业科学研究院,2015.]
[65]Ji Yongjie,Yue Cairong,Zhao Lei,et al.Forest Height Estimation of TanDEM-X Data based on DEM Difference Method[J].Journal of Southwest Forestry University,2016,36(6):73-78.[姬永杰,岳彩荣,赵磊,等.基于DEM差分法的TanDEM-X数据森林高度估测[J].西南林业大学学报,2016,36(6):73-78.]
[66]Praks J,Kugler F,Papathanassiou K P,et al.Height Estimation of Boreal Forest:Interferometric Model-based Inversion at L- and X-band Versus Hutscat Profiling Scatterometer[J].IEEE Geoscience & Remote Sensing Letters,2007,4(3):466-470.
[67]Yang Lei,Zhao Yongjun,Wang Zhigang.Unitary ESPRIT-based Phase Estimation for Polarimetric SAR Interferometry[J].Science of Surveying and Mapping,2007,32(2):57-59.[杨磊,赵拥军,王志刚.基于酉ESPRIT算法的极化干涉相位估计[J].测绘科学,2007,32(2):57-59.]
[68]Song Guiping.Investigation of Vegetation Height Retrieval with Polarimetric Interferometry SAR[D].Changsha:Central South University,2013.[宋桂萍.极化干涉SAR植被高度反演算法研究[D].长沙:中南大学,2013.]
[69]Song Guiping, Wang Changcheng,Fu Haiqiang,et al.A Novel Vegetation Height Inversion Method based on Polarimetric Interferometric Covariance Matrix Decomposition[J].Acta Geodaetica et Cartographica Sinica,2014,43(6):613-619.[宋桂萍,汪长城,付海强,等.植被高度的极化干涉互协方差矩阵分解反演法[J].测绘学报,2014,43(6):613-619.]
[70]Yamazaki M,Yamada H.Accuracy Improvement of Forest Height Estimation with Esprit Algorithm Using Four-component Scattering-Model Decomposition[J],IEICE Technical Report Antennas & Propagation,2006,105(561):37-40.
[71]Zhang Lamei.Terrain Surface Parameters Inversion Using L Band POlInSAR Images[D].Harbin:Harbin Institute of Technology,2006.[张腊梅.L波段POLInSAR图像地表参数反演方法研究[D].哈尔滨:哈尔滨工业大学,2006.]
[72]Angiuli E,Del Frate F,Vecchia A D,et al.Inversion Algorithms Comparison Using L-band Simulated Polarimetric Interferometric Data for Forest Parameters Estimation[C]//IEEE Geoscience and Remote Sensing Symposium,Barcelona,2007.
[73]Zhou Guangyi,Xiong Tao,Zhang Weijie,et al.Forest Height Measurements based on Polarimetric SAR Interferometry[J].Journal of Tsinghua University (Science and Technology),2009,(4):510-513.[周广益,熊涛,张卫杰,等,基于极化干涉SAR数据的树高反演方法[J].清华大学学报(自然科学版),2009,(4):510-513.]
[74]Xu Liying,Li Shiqiang,Deng Yunkai,et al.Improved Three-stage Algorithm of Forest Height Retrieval with PolInSAR[J].Journal of Radars,2014,3(1):28-34.[许丽颖,李世强,邓云凯,等.基于极化干涉SAR反演植被高度的改进三阶段算法[J].雷达学报,2014,3(1):28-34.]
[75]Wayne S.Walker,Josef M,et al.Quality Assessment of SRTM C- and X-band Interferometric Data:Implications for the Retrieval of Vegetation Canopy Height[J].Remote Sensing of Environment,2007,106(4):428-448.
 
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