[1] CARTUS O, SANTORO M, WEGMÜLLER U, et al. Benchmarking the retrieval of biomass in boreal forests using P band SAR backscatter with multi-temporal C- and L-band observations[J/OL]. Remote Sensing, 2019, 11(14): 1695 [2022-01-01]. doi: 10.3390/rs11141695.
[2] SANTI E, PALOSCIA S, PETTINATO S, et al. Machine-learning applications for the retrieval of forest biomass from airborne P band SAR data[J/OL]. Remote Sensing, 2020, 12(5): 804 [2022-01-05]. doi: 10.3390/rs12050804.
[3] LIAO Zhanmang, HE Binbin, QUAN Xingwen. Potential of texture from SAR tomographic images for forest aboveground biomass estimation[J/OL]. Int J Appl Earth Obs Geoinf, 2020, 88: 102049 [2022-01-05]. doi: 10.1016/j.jag.2020.102049.
[4] QUAN Xingwen, HE Binbin, YEBRA M, et al. A radiative transfer model-based method for the estimation of grassland aboveground biomass [J]. Int J Appl Earth Obs Geoinf, 2017, 54: 159 − 168.
[5] JI Yongjie, XU Kunpeng, ZENG Peng, et al. GA-SVR algorithm for improving forest above ground biomass estimation using SAR data [J]. IEEE J Selected Top Appl Earth Obs Remote Sensing, 2021, 14: 6585 − 6595.
[6] LIU Y Y, DIJK A, RAMD J, et al. Recent reversal in loss of global terrestrial biomass [J]. Nat Clim Change, 2015, 5(5): 470 − 474.
[7] BOUDREAU J, NELSON R F, MARGOLIS H A, et al. Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec [J]. Remote Sensing Environ, 2008, 112(10): 3876 − 3890.
[8] JI Yongjie, HUANG Jimao, JU Yilin, et al. Forest structure dependency analysis of L-band SAR backscatter[J/OL]. PeerJ, 2020, 8: e10055 [2022-01-05]. doi: 10.7717/PEERJ.10055.
[9] 李增元, 赵磊, 李堃, 等. 合成孔径雷达森林资源监测技术研究综述[J]. 南京信息工程大学学报(自然科学版), 2020, 12(2): 150 − 158.

LI Zengyuan, ZHAO Lei, LI Kun, et al. A survey of developments on forest resources monitoring technology of synthetic aperture radar [J]. J Nanjing Univ Inf Sci Technol Nat Sci Ed, 2020, 12(2): 150 − 158.
[10] 冯琦, 陈尔学, 李增元, 等. 基于机载P波段全极化SAR数据的复杂地形森林地上生物量估测方法[J]. 林业科学, 2016, 52(3): 10 − 22.

FENG Qi, CHEN Erxue, LI Zengyuan, et al. Forest above-ground biomass estimation method for rugged terrain based on airborne P-band PolSAR data [J]. Sci Silv Sin, 2016, 52(3): 10 − 22.
[11]

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.
[12]

TOAN T L, BEAUDOIN A, RIOM J, et al. Relating forest biomass to SAR data [J]. IEEE Trans Geosci Remote Sensing, 1992, 30(2): 403 − 411.
[13]

TOAN T L, QUEGAN S, WOODWARD I, et al. Relating radar remote sensing of biomass to modelling of forest carbon budgets [J]. Clim Change, 2004, 67(2): 379 − 402.
[14]

LIAO Zhanmang, HE Binbin, QUAN Xingwen, et al. Biomass estimation in dense tropical forest using multiple information from single-baseline P band PolInSAR data [J]. Remote Sensing Environ, 2019, 221: 489 − 507.
[15] 黄国满. 机载多波段多极化干涉SAR测图系统——CASMSAR[J]. 测绘科学, 2014, 39(8): 111 − 115.

HUANG Guoman. An airborne interferometric SAR mapping system with multi-band and multi-polarization: CASMSAR [J]. Sci Surv Mapp, 2014, 39(8): 111 − 115.
[16]

ZHAO Lei, CHEN Erxue, LI Zengyuan, et al. Three-step semi-empirical radiometric terrain correction approach for PolSAR data applied to forested areas[J/OL]. Remote Sensing, 2017, 9(3): 269 [2022-01-05]. doi: 10.3390/rs9030269.
[17] 穆喜云. 森林地上生物量遥感估测方法研究[D]. 呼和浩特: 内蒙古农业大学, 2015.

MU Xiyun. A Study on the Estimating Method of Forest Above Ground Biomass Based on Remote Sensing Data[D]. Huhhot: Inner Mongolia Agricultural University, 2015.
[18] 陈传国. 东北主要林木生物量手册[M]. 北京: 中国林业出版社, 1989.

CHEN Chuanguo. Woody Biomass Manual of Typical Species in the Northeast of China[M]. Beijing: China Forestry Publishing House, 1989.
[19]

CLOUDE S R, POTTIER E. A review of target decomposition theorems in radar polarimetry [J]. IEEE Trans Geosci Remote Sensing, 1996, 34(2): 498 − 518.
[20] 张王菲, 姬永杰. 极化与干涉SAR植被参数反演[M]. 北京: 中国林业出版社, 2019.

ZHANG Wangfei, JI Yongjie. Retrieval of Vegetation Parameters from Polarimetric and Interferometric SAR[M]. Beijing: China Forestry Publishing House, 2019.
[21] 姬永杰. 多频极化SAR技术森林地上生物量反演研究[D]. 昆明: 西南林业大学, 2021.

JI Yongjie. Retrieval of Forest above Ground Biomass Using Multi-frequency Polarimetric SAR[D]. Kunming: Southwest Forestry University, 2021.
[22] 郭颖. 森林地上生物量的非参数化遥感估测方法优化[D]. 北京: 中国林业科学研究院, 2011.

GUO Ying. Optimum Non-Parametric Method for Forest Above Ground Biomass Estimation Based on Remote Sensing Data[D]. Beijing: Chinese Academy of Forestry, 2011.
[23]

TIAN Xin, SU Zhongbo, CHEN Erxue, et al. Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area [J]. Int J Appl Earth Obs Geoinf, 2011, 17: 102 − 110.
[24]

LU Dengsheng, CHEN Qi, WANG Guangxing, et al. A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems [J]. Int J Digital Earth, 2016, 9(1): 63 − 105.
[25] 韩宗涛, 江洪, 王威, 等. 基于多源遥感的森林地上生物量KNN-FIFS估测[J]. 林业科学, 2018, 54(9): 70 − 79.

HAN Zongtao, JIANG Hong, WANG Wei, et al. Forest above-ground biomass estimation using KNN-FIFS method based on multi-source remote sensing data [J]. Sci Silv Sin, 2018, 54(9): 70 − 79.
[26] 方匡南, 吴见彬, 朱建平, 等. 随机森林方法研究综述[J]. 统计与信息论坛, 2011, 26(3): 32 − 38.

FANG Kuangnan, WU Jianbin, ZHU Jianping, et al. A review of technologies on random forests [J]. Stat Inf Forum, 2011, 26(3): 32 − 38.
[27] 魏晶昱, 范文义, 于颖, 等. GF-3全极化SAR数据极化分解估算人工林冠层生物量[J]. 林业科学, 2020, 56(9): 174 − 183.

WEI Jingyu, FAN Wenyi, YU Ying, et al. Polarimetric decomposition parameters for artificial forest canopy biomass estimation using GF-3 fully polarimetric SAR data [J]. Sci Silv Sin, 2020, 56(9): 174 − 183.
[28]

SAATCHI S, MARLIER M, CHAZDON R L, et al. Impact of spatial variability of tropical forest structure on radar estimation of aboveground biomass [J]. Remote Sensing Environ, 2011, 115(11): 2836 − 2849.
[29]

TOAN T L, QUEGAN S, DAVIDSON M W J, et al. The BIOMASS mission: mapping global forest biomass to better understand the terrestrial carbon cycle [J]. Remote Sensing Environ, 2011, 115(11): 2850 − 2860.
[30]

NEUMANN M, SAATCHI S S, ULANDER L M H, et al. Assessing performance of L and P band polarimetric interferometric SAR data in estimating boreal forest above-ground biomass [J]. IEEE Trans Geosci Remote Sensing, 2012, 50(3): 714 − 726.
[31]

KASISCHKE E S, CHRISTENSEN N L, BOURGEAU-CHAVEZ L L. Correlating radar backscatter with components of biomass in loblolly pine forests [J]. IEEE Trans Geosci Remote Sensing, 1995, 33(3): 643 − 659.
[32]

RODRÍGUEZ-VEIGA P, QUEGAN S, CARREIRAS J, et al. Forest biomass retrieval approaches from earth observation in different biomes [J]. Int J Appl Earth Obs Geoinf, 2019, 77: 53 − 68.
[33]

GOLSHANI P, MAGHSOUDI Y, SOHRABI H. Relating ALOS-2 PALSAR-2 parameters to biomass and structure of temperate broadleaf Hyrcanian forests [J]. J Ind Soc Remote Sensing, 2019, 47(5): 749 − 761.
[34]

ENGLHART S, KEUCK V, SIEGERT F. Modeling aboveground biomass in tropical forests using multi-frequency SAR data: a comparison of methods [J]. IEEE J Selected Top Appl Earth Obs Remote Sensing, 2012, 5(1): 298 − 306.