Based polarization orientation angle compensation for Pinus kesiya var. langbianensis forest aboveground biomass estimation

doi:10.12302/j.issn.1000-2006.202101016

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2021, Vol. 45 ›› Issue (6): 185-192.doi: 10.12302/j.issn.1000-2006.202101016

Previous Articles Next Articles

Based polarization orientation angle compensation for Pinus kesiya var. langbianensis forest aboveground biomass estimation

ZHANG Guofei(), YUE Cairong^*(), LUO Hongbin, GU Lei, ZHU Bodong

College of Forestry, Southwest Forestry University, Kunming 650224,China

Received:2021-01-14 Accepted:2021-03-23 Online:2021-11-30 Published:2021-12-02
Contact: YUE Cairong E-mail:info1979@163.com;1207709049@qq.com

Abstract

Abstract:

【Objective】Polarimetric synthetic aperture radars have been widely used in forest remote sensing monitoring. Owing to Faraday rotation, the polarization orientation angle (POA) of the electromagnetic wave is displaced, leading to ambiguity in the scattering characteristics. In this study, the effects of polarization orientation angle compensation on the volume scattering component and aboveground biomass (AGB) retrieval were analyzed.【Method】 The influence of Faraday rotation on SAR data was analyzed using ALOS PALSAR full polarimetric SAR images as the data source. Based on the L-band scattering characteristics and considering the dihedral scattering contribution between the ground and the tree trunk, an extended polarization water cloud model (EPWCM) was proposed. Based on the Yamaguchi four-component decomposition parameters and field survey data, the aboveground biomass of Pinus kesiya var. langbianensis forest was estimated by EPWCM.【Result】 Through the unitary transformation of the coherence matrix to compensate for the polarization orientation angle deviation, the overestimation of the volume scattering component was corrected, and the regression with aboveground biomass was improved (R ² increased from 0.214 to 0.332). The estimated aboveground biomass had a strong correlation with the observed AGB (R² = 0.644) and a relatively high accuracy (RMSE as 23.11 t/hm²). 【Conclusion】 Before polarimetric decomposition, SAR data should be compensated for polarimetric orientation angle correction to reduce the ambiguity of scattering characteristics and increase the retrieval accuracy of AGB. The semi-empirical model has a good potential for estimating forest aboveground biomass.

Key words: Pinus kesiya var. langbianensis forest, aboveground biomass (AGB), polarization orientation angle(POA), Faraday rotation, extended polarization water cloud model(EPWCM)

CLC Number:

S718
S711

ZHANG Guofei, YUE Cairong, LUO Hongbin, GU Lei, ZHU Bodong. Based polarization orientation angle compensation for Pinus kesiya var. langbianensis forest aboveground biomass estimation[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2021, 45(6): 185-192.

Figures/Tables 8

Table 1

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

References 39

[1]	SHI L, LIU S R. Methods of estimating forest biomass:a review[G]. Biomass Volume Estimation and Valorization for Energy. Rijeka Croatia: Intech, 2017. DOI: 10.5772/65733. doi: 10.5772/65733
[2]	MANOLIS E N, ZAGAS T D, PORAVOU C A, et al. Biomass assessment for sustainable bioenergy utilization in a mediterranean forest ecosystem in northwest Greece[J]. Ecol Eng, 2016, 91:537-544.DOI: 10.1016/j.ecoleng.2016.02.041. doi: 10.1016/j.ecoleng.2016.02.041
[3]	LE TOAN T, BEAUDOIN A, RIOM J, et al. Relating forest biomass to SAR data[J]. IEEE Trans Geosci Remote Sens, 1992, 30(2):403-411.DOI: 10.1109/36.134089. doi: 10.1109/36.134089
[4]	MITCHARD E T A, SAATCHI S S, WOODHOUSE I H, et al. Using satellite radar backscatter to predict above-ground woody biomass:a consistent relationship across four different African landscapes[J]. Geophys Res Lett, 2009, 36(23):L23401.DOI: 10.1029/2009GL040692. doi: 10.1029/2009GL040692
[5]	DOBSON M C, ULABY F T, LETOAN T, et al. Dependence of radar backscatter on coniferous forest biomass[J]. IEEE Trans Geosci Remote Sensing, 1992, 30(2):412-415.DOI: 10.1109/36.134090. doi: 10.1109/36.134090
[6]	SUZUKI R, KIM Y, ISHII R. Sensitivity of the backscatter intensity of ALOS/PALSAR to the above-ground biomass and other biophysical parameters of boreal forest in Alaska[J]. Polar Sci, 2013, 7(2):100-112.DOI: 10.1016/j.polar.2013.03.001. doi: 10.1016/j.polar.2013.03.001
[7]	潘磊, 孙玉军, 王轶夫, 等. 基于Sentinel-1和Sentinel-2数据的杉木林地上生物量估算[J]. 南京林业大学学报(自然科学版), 2020, 44(3):149-156.
	PAN L, SUN Y J, WANG Y F, et al. Estimation of aboveground biomass in a Chinese fir(Cunninghamia lanceolata)forest combining data of Sentinel-1 and Sentinel-2[J]. J Nanjing For Univ (Nat Sci Ed), 2020, 44(3):149-156.
[8]	ASKNE J I H, DAMMERT P B G, ULANDER L M H, et al. C-band repeat-pass interferometric SAR observations of the forest[J]. IEEE Trans Geosci Remote Sens, 1997, 35(1):25-35.DOI: 10.1109/36.551931. doi: 10.1109/36.551931
[9]	ASKNE J, SANTORO M. Multitemporal repeat pass SAR interferometry of boreal forests[J]. IEEE Trans Geosci Remote Sens, 2005, 43(6):1219-1228.DOI: 10.1109/TGRS.2005.846878. doi: 10.1109/TGRS.2005.846878
[10]	张伟伦, 张延成, 范文义, 等. 干涉水云模型对不同极化方式哨兵数据估测森林生物量的精度比较[J]. 东北林业大学学报, 2020, 48(11):27-32.
	ZHANG W L, ZHANG Y C, FAN W Y, et al. Comparison of biomass accuracy with different polarization data with interferometric water cloud model[J]. J Northeast For Univ, 2020, 48(11):27-32.DOI: 10.3969/j.issn.1000-5382.2020.11.005. doi: 10.3969/j.issn.1000-5382.2020.11.005
[11]	李兰, 陈尔学, 李增元, 等. 森林地上生物量的多基线InSAR层析估测方法[J]. 林业科学, 2017, 53(11):85-93.
	LI L, CHEN E X, LI Z Y, et al. Forest above-ground biomass estimation based on multi-baseline InSAR tomography[J]. Sci Silvae Sin, 2017, 53(11):85-93.DOI: 10.11707/j.1001-7488.20171110. doi: 10.11707/j.1001-7488.20171110
[12]	CLOUDE S R, PAPATHANASSIOU K P. Polarimetric SAR interferometry[J]. IEEE Trans Geosci Remote Sens, 1998, 36(5):1551-1565.DOI: 10.1109/36.718859. doi: 10.1109/36.718859
[13]	YAMAGUCHI Y, SATO A, BOERNER W M, et al. Four-component scattering power decomposition with rotation of coherency matrix[J]. IEEE Trans Geosci Remote Sens, 2011, 49(6):2251-2258.DOI: 10.1109/TGRS.2010.2099124. doi: 10.1109/TGRS.2010.2099124
[14]	徐一凡, 刘爱芳, 徐辉, 等. 基于改进三分量模型的全极化SAR图像分类[J]. 电子测量技术, 2017, 40(12):220-227.
	XU Y F, LIU A F, XU H, et al. Classification of fully polarimetric SAR image based on the improved three-component scattering model[J]. Electron Meas Technol, 2017, 40(12):220-227.
[15]	KUMAR S, GARG R D, GOVIL H, et al. PolSAR-decomposition-based extended water cloud modeling for forest aboveground biomass estimation[J]. Remote Sens, 2019, 11(19):2287.DOI: 10.3390/rs11192287. doi: 10.3390/rs11192287
[16]	SANTI E, PALOSCIA S, PETTINATO S, et al. The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas[J]. Remote Sens Environ, 2017, 200:63-73.DOI: 10.1016/j.rse.2017.07.038. doi: 10.1016/j.rse.2017.07.038
[17]	SATO A, YAMAGUCHI Y, SINGH G, et al. Four-component scattering power decomposition with extended volume scattering model[J]. IEEE Geosci Remote Sens Lett, 2012, 9(2):166-170.DOI: 10.1109/LGRS.2011.2162935. doi: 10.1109/LGRS.2011.2162935
[18]	YAMAGUCHI Y. Disaster monitoring by fully polarimetric SAR data acquired with ALOS-PALSAR[J]. Proceedings of the IEEE, 2012, 100(10):2851-2860. doi: 10.1109/JPROC.2012.2195469
[19]	LEE J S, AINSWORTH T L. The effect of orientation angle compensation on coherency matrix and polarimetric target decompositions[J]. IEEE Trans Geosci Remote Sens, 2011, 49(1):53-64.DOI: 10.1109/TGRS.2010.2048333. doi: 10.1109/TGRS.2010.2048333
[20]	LEE J S, POTTIER E. Polarimetric radar imaging: from basics to applications[M]. Boca Raton: CRC Press, 2009. DOI: 10.1201/9781420054989. doi: 10.1201/9781420054989
[21]	游彪, 杨健. 极化合成孔径雷达图像目标定向角[J]. 太赫兹科学与电子信息学报, 2014, 12(4):539-544.
	YOU B, YANG J. Orientation angle of target in polarimetric synthetic aperture radar images[J]. J Terahertz Sci Electron Inf Technol, 2014, 12(4):539-544.
[22]	黄龙, 刘爱芳, 徐辉, 等. 极化定向角补偿区域检测新方法[J]. 电子测量技术, 2018, 41(2):41-44.
	HUANG L, LIU A F, XU H, et al. New area detection method for polarization orientation angle compensation[J]. Electron Meas Technol, 2018, 41(2):41-44.DOI: 10.19651/j.cnki.emt.1701081. doi: 10.19651/j.cnki.emt.1701081
[23]	李江. 思茅松中幼龄人工林生物量和碳储量动态研究[D]. 北京:北京林业大学, 2011.
	LI J. Dynamics of biomass and carbon stock for young and middle aged plantation of Simao pine (Pinus kesiya var. langbianensis)[D]. Beijing:Beijing Forestry University, 2011.
[24]	LI H Z, LI Q Q, WU G F, et al. The impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas[J]. IEEE Trans Geosci Remote Sens, 2016, 54(9):5520-5532.DOI: 10.1109/TGRS.2016.2567421. doi: 10.1109/TGRS.2016.2567421
[25]	SOUISSI B, OUARZEDDINE M. Polarimetric SAR data correction and terrain topography measurement based on the radar target orientation angle[J]. J Indian Soc Remote Sens, 2016, 44(3):335-349.DOI: 10.1007/s12524-015-0493-x. doi: 10.1007/s12524-015-0493-x
[26]	KIMURA H. Calibration of polarimetric PALSAR imagery affected by faraday rotation using polarization orientation[J]. IEEE Trans Geosci Remote Sens, 2009, 47(12):3943-3950.DOI: 10.1109/TGRS.2009.2028692. doi: 10.1109/TGRS.2009.2028692
[27]	BABU A, KUMAR S, GOVIL H. Investigation on the effects of polarization orientation angle shift in the UAVSAR polarimetric decomposition[J]. J Indian Soc Remote Sens, 2021, 49(3):551-557.DOI: 10.1007/s12524-020-01234-0. doi: 10.1007/s12524-020-01234-0
[28]	ATTEMA E P W, ULABY F T. Vegetation modeled as a water cloud[J]. Radio Science, 1978, 13(2):357-364. doi: 10.1029/RS013i002p00357
[29]	BINDLISH R, BARROS A P. Parameterization of vegetation backscatter in radar-based,soil moisture estimation[J]. Remote Sens Environ, 2001, 76(1):130-137.DOI: 10.1016/S0034-4257(00)00200-5. doi: 10.1016/S0034-4257(00)00200-5
[30]	MORAN M S, VIDAL A, TROUFLEAU D, et al. Ku-and C-band SAR for discriminating agricultural crop and soil conditions[J]. IEEE Trans Geosci Remote Sens, 1998, 36(1):265-272.DOI: 10.1109/36.655335. doi: 10.1109/36.655335
[31]	SANTORO M, BEAUDOIN A, BEER C, et al. Forest growing stock volume of the northern hemisphere: spatially explicit estimates for 2010 derived from Envisat ASAR[J]. Remote Sens Environ, 2015, 168:316-334.DOI: 10.1016/j.rse.2015.07.005. doi: 10.1016/j.rse.2015.07.005
[32]	SAI BHARADWAJ P, KUMAR S, KUSHWAHA S P S, et al. Polarimetric scattering model for estimation of above ground biomass of multilayer vegetation using ALOS-PALSAR quad-pol data[J]. Phys Chem Earth Parts A/B/C, 2015, 83/84:187-195.DOI: 10.1016/j.pce.2015.09.003. doi: 10.1016/j.pce.2015.09.003
[33]	THIRION-LEFEVRE L, GUINVARC’H R, COLIN-KOENIGUER E. The combined effect of orientation angle and material on PolSAR images of urban areas[J]. Remote Sens, 2020, 12(10):1632.DOI: 10.3390/rs12101632. doi: 10.3390/rs12101632
[34]	范永东. 模型选择中的交叉验证方法综述[D]. 太原:山西大学, 2013.
	FAN Y D. A summary of cross-validation in model selection[D]. Taiyuan:Shanxi University, 2013.
[35]	岳锋, 杨斌. 思茅松林碳汇功能研究[J]. 江苏农业科学, 2011, 39(5):467-470.
	YUE F, YANG B. Study on carbon sink function of Pinus kesiya var. langbianensis[J]. Jiangsu Agric Sci, 2011, 39(5):467-470. DOI: 10.15889/j.issn.1002-1302.2011.05.202. doi: 10.15889/j.issn.1002-1302.2011.05.202
[36]	吴兆录, 党承林. 云南普洱地区思茅松林的生物量[J]. 云南大学学报(自然科学版), 1992, 14(2):119-127.
	WU Z L, DANG C L. The biomass of Pinus kesiya var. langbianensis stands in Puer District,Yunnan[J]. J Yunnan Univ (Nat Sci), 1992, 14(2):119-127.
[37]	陈庆, 郑征, 冯志立, 等. 云南普洱地区思茅松林生物量及碳储量研究[J]. 云南大学学报(自然科学版), 2014, 36(3):439-445.
	CHEN Q, ZHENG Z, FENG Z L, et al. Biomass and carbon storage of Pinus kesiya var. langbianensis in Puer,Yunnan[J]. J Yunnan Univ (Nat Sci Ed), 2014, 36(3):439-445.DOI: 10.7540/j.ynu.20130614. doi: 10.7540/j.ynu.20130614
[38]	MICHELAKIS D, STUART N, BROLLY M, et al. Estimation of woody biomass of pine savanna woodlands from ALOS PALSAR imagery[J]. IEEE J Sel Top Appl Earth Obs Remote Sens, 2015, 8(1):244-254.DOI: 10.1109/JSTARS.2014.2365253. doi: 10.1109/JSTARS.2014.2365253
[39]	PEREGON, YAMAGATA. The use of ALOS/PALSAR backscatter to estimate above-ground forest biomass: a case study in western Siberia[J]. Remote Sens Environ, 2013, 137:139-146. doi: 10.1016/j.rse.2013.06.012

Related Articles 15

[1]	CONG Mingzhu, LIU Qijing, SUN Zhen, DONG Chunchao, QIAN Nipeng. Interpretation of environmental factors affecting β diversity and its components in plant communities on the northern slope of Changbai Mountain [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 99-106.
[2]	CAO Lili, RUAN Honghua, LI Yuanyuan, NI Juanping, WANG Guobing, CAO Guohua, SHEN Caiqin, XU Yaming. Variations of surface soil macrofauna in different aged Metasequoia glyptostroboides plantations [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 91-98.
[3]	ZHANG Yiting, XIA Nianhe, LIN Shuyan, DING Yulong. Spatial distribution characteristics and influencing factors of Chimonobambusa in China [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 107-114.
[4]	HU Yanping, LIU Weidong, ZHANG Min, CHEN Minggao, CHENG Yong, WEI Zhiheng, PANG Wensheng, WU Jiyou. Study on leaf color parameters, pigment content and anatomical structure of Triadica cochinchinensis families [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 123-133.
[5]	WANG Yijie, WANG Lumian, DING Zhenhui, QIAN Cheng, CAO Jiajie. Effects of urban waterfront green space on summer microclimate [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 233-241.
[6]	ZHAO Guoyang, HONG Bo, GAO Junping, ZHAO Xin, HUANG Hongfeng, XU Yanjie. Chrysanthemum morifolium ‘Quehuan’:a new cultivar of Chrysanthemum [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 254-255.
[7]	REN Jiahui, GAO Handong, CHEN Zhenan, LI Hao, LIU Qiang, CHEN Pengjun. Growth and physiological response of Salix matsudana × alba to salt-flooding stress [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(2): 57-66.
[8]	DONG Yawen, CHEN Shuanglin, XIE Yanyan, GUO Ziwu, ZHANG Jingrun, WANG Sheping, XU Yonggan. Variations in the leaf construction cost of Phyllostachys edulis and other dominant tree species during understory vegetation succession [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 179-186.
[9]	XU Xinlu, KONG Shuxin, LYU Zhuo, JIANG Shuaijun, ZHAO Wanqi, LIN Shuyan. The relationship of appearance, structure and photosynthetic characteristics of different leaf color phenotypes of Sasaella glabra ‘Albostriata’ [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 145-154.
[10]	CAO Yonghui, CHEN Qingbiao, ZHOU Benzhi, GE Xiaogai, WANG Xiaoming. Effects of different drought periods on the spatiotemporal distribution of nitrogen content in the leaves of Phyllostachys edulis [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 155-161.
[11]	SUI Xiran, LI Jun, CHEN Juan, HUA Jun, SHEN Qian, YANG Hongsheng, HE Qiancheng, LI You, WANG Wei, PENG Ye, GE Zhiwin, ZHANG Zengxin. Species diversity changes of Platycladus orientalis community at different succession stages in Xuzhou City [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 171-178.
[12]	YIN Huakang, ZHANG Jindong, HUANG Jinyan, PU Guanhua, MAO Ze’en, ZHOU Caiquan, HUANG Yaohua, FU Liqiang. Spatial distribution of bamboo, the staple food of giant panda (Ailuropoda melanoleuca) in Mabian Dafengding Nature Reserve, Sichuan Province [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 187-193.
[13]	KONG Fanbin, JIN Chentao, XU Caiyao. Changes in the coupling coordination relationship between ecosystem services and residents’ well-being and its influencing factors in the Luoxiao Mountain area [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 245-254.
[14]	GONG Xia, WU Yinming, WANG Haifeng, ZENG Pan, TANG Ya, WEN Keng, JIAO Wenxian. ‘Shujiao Yihao’: a new cultivar of Zanthoxylum bungeanum [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 265-266.
[15]	WU Tong, WANG Xianrong, YI Xiangui, ZHOU Huajin, CHEN Jie, LI Meng, CHEN Xiangzhen, GAO Shucheng. Prunus dielsiana ‘Yanzhixue’ : a new cultivar of cherry blossom [J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2025, 49(1): 267-268.

Metrics

Comments

www.nldxb.njfu.edu.cn

Edited ＆ Published by Editorial Department of Nanjing Forestry University(Natural Sciences Edition)
Address： No.159 Longpan Road,Nanjing 210037 Jiangsu,P.R.China
E-mail ：xuebao@njfu.edu.cn , xuebao@njfu.com.cn
Telephone +86-25-85428247,85427076
Distributed by China International Book Trading Corporation P.O. Box 399, Beijing ,P.R. China

统计量 statistics	林分平均高/m stand mean height	胸径/cm average DBH	每公顷株数 number of plants per hectare	地上生物量/ (t·hm^-2) aboveground biomass
均值 mean	14.27	14.23	1 843	126
最大值 max.	17.25	17.39	3 724	282
最小值 min.	10.18	9.97	987	69

Based polarization orientation angle compensation for Pinus kesiya var. langbianensis forest aboveground biomass estimation

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 39

Related Articles 15

Recommended Articles

Metrics

Comments

Author

Reader

Reviewer