Review on the development of natural resources monitoring technology and equipment in China

doi:10.6046/gtzyyg.2020.03.02

Abstract
Figures/Tables
References
Related Articles
Metrics

Download: PDF(676 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Technical equipment development is an important part of natural resources monitoring. According to the different delivery platforms, the monitoring technology and equipment of natural resources are classified into three categories: satellite-borne, airborne and ground-based, and their details are described in this paper. The authors briefly analyzed the problems and challenges faced by the current development and, at the same time, put forward some suggestions for development which is based on the actual situation of China: To carry out inventory and assessment of natural resources and equipment; to emphasize the importance of infrastructure construction and resource integration of technological equipment, to make technical equipment development plan, and to adopt some other measures.

Keywords natural resources monitoring technical equipment remote sensing

TP79

Issue Date: 09 October 2020

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	Chaomang ZHANG
	Yuanzhi YE
	Yi DENG
	Jianbang WANG

Cite this article:

Chaomang ZHANG,Yuanzhi YE,Yi DENG, et al. Review on the development of natural resources monitoring technology and equipment in China[J]. Remote Sensing for Land & Resources, 2020, 32(3): 8-14.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.03.02 OR https://www.gtzyyg.com/EN/Y2020/V32/I3/8

卫星系列			发射时间	遥感载荷与监测能力
卫星系列			发射时间	传感器	光谱范围	分辨率/m
地球资源卫星	资源一号	CBERS-01 CBERS-02	1999年10月 2003年10月	CCD相机	可见光、红外	19.5
				宽视场成像仪	可见光、红外	258
				红外多光谱扫描仪	可见光、红外	78/156
		CBERS-02B	2007年9月	CCD相机	可见光、红外	20
				高分辨率相机	可见光、红外	2.36
				宽视场成像仪	可见光、红外	258
		ZY-1 02C	2011年12月	全色多光谱相机	可见光、红外	5/10
		ZY-1 02C	2011年12月	全色高分辨率相机	可见光、红外	2.36
		CBERS-04	2014年12月	全色多光谱相机	可见光、红外	5/10
				多光谱相机	可见光、红外	20
				红外相机	可见光、红外	40/80
				宽视场成像仪	可见光、红外	73
	资源三号	ZY3-01 ZY3-02	2012年1月 2016年5月	前视相机	可见光、红外	3.5/2.5
				后视相机	可见光、红外	3.5/2.5
				正视相机	可见光、红外	2.1/2.1
				多光谱相机	可见光、红外	5.8/5.8
	高分一号		2013年4月	全色多光谱相机	可见光、红外	2/8
	高分一号		2013年4月	多光谱相机	可见光、红外	16
	高分二号		2014年8月	全色多光谱相机	可见光、红外	1/4
	高分三号		2016年8月	C-SAR合成孔径雷达	微波	1
	高分四号		2015年12月	凝视相机	可见光、红外	50/400
海洋卫星	海洋一号	HY-1A HY-1B	2002年5月 2007年4月	海洋水色水温扫描仪	可见光、红外	1 100
		HY-1A HY-1B	2002年5月 2007年4月	海岸带成像仪	可见光、红外	250
		HY-1C	2018年7月	海洋水色水温扫描仪	可见光、红外	—
				海岸带成像仪	可见光、红外	50
				紫外成像仪	紫外	500
	海洋二号	HY-2 HY-2B	2011年8月 2018年10月	微波散射计	微波	—
				扫描微波辐射计	微波	—
				校正微波辐射计	微波	—
环境减灾卫星	HJ-1A		2008年9月	CCD相机	可见光、红外	30
	HJ-1A		2008年9月	高光谱成像仪	可见光、红外	100
	HJ-1B		2008年9月	CCD相机	可见光、红外	30
	HJ-1B		2008年9月	红外多光谱相机	红外	150
	HJ-1C		2012年11月	S-SAR合成孔径雷达	微波	5(单视) 20(四视)

Tab.1 Major natural resources satellite and their payloads of China

[1]	Satellite Industry Association. The 2019 state of the satellite industry report[R]. Washington:Satellite 2019,2019.
[2]	姚崇斌, 徐红新, 赵锋, 等. 微波无源遥感有效载荷现状与发展[J]. 上海航天, 2018,35(2):1-12.
[2]	Yao C B, Xu H X, Zhao F, et al. Current status and future development of microwave radiometer[J]. Aerospace Shanghai, 2018,35(2):1-12.
[3]	张淳民, 穆廷魁, 颜廷昱, 等. 高光谱遥感技术发展与展望[J]. 航天返回与遥感, 2018,39(3):104-114.
[3]	Zhang C M, Mu T K, Yan T Y, et al. Overview of hyperspectral remote sensing technology[J]. Spacecraft Recovery & Remote Sensing, 2018,39(3):104-114.
[4]	刘畅, 白强, 唐高, 等. 中国海洋遥感技术进展[J]. 船舶与海洋工程, 2018,34(1):1-6.
[4]	Liu C, Bai Q, Tang G, et al. Development of marine remote sensing technology in China[J]. Naval Architecture and Ocean Engineering, 2018,34(1):1-6.
[5]	张庆君, 韩晓磊, 刘杰. 星载合成孔径雷达遥感技术进展及发展趋势[J]. 航天器工程, 2017,26(6):1-8.
[5]	Zhang Q J, Han X L, Liu J. Technology progress and development trend of spaceborne synthetic aperture Radar remote sensing[J]. Spacecraft Engineering, 2017,26(6):1-8.
[6]	李硕, 唐元贵, 黄琰, 等. 深海技术装备研制现状与展望[J]. 中国科学院院刊, 2016,31(12):1316-1325.
[6]	Li S, Tang Y G, Huang Y, et al. Review and prospect for Chinese deep-sea technology and equipment[J]. Bulletin of the Chinese Academy of Sciences, 2016,31(12):1316-1325.
[7]	胡君, 王栋, 孙天宇. 现代航天光学成像遥感器的应用与发展[J]. 中国光学与应用光学, 2010,3(6):519-533.
[7]	Hu J, Wang D, Sun T Y. Application and development of recent space optical imaging remote sensors[J]. Chinese Journal of Optics and Applied Optics, 2010,3(6):519-533.
[8]	李颖虹, 王凡, 任小波. 海洋观测能力建设的现状、趋势与对策思考[J]. 地球科学进展, 2010,25(7):715-722.
[8]	Li Y H, Wang F, Ren X B. Development trend and strategy of ocean observing capability[J]. Advances in Earth Science, 2010,25(7):715-722.
[9]	李建平, 张柏, 张泠, 等. 湿地遥感监测研究现状与展望[J].地理科学进展, 2007(1):33-43.
[9]	Li J P, Zhang B, Zhang L, et al. Current status and prospect of researches on wetland monitoring based on remote sensing[J].Progress in Geography 2007(1):33-43.
[10]	肖志辉, 张祖荫, 郭伟. 地基、空基、星基微波辐射计定标技术概览[J].遥感技术与应用, 2000(2):113-120.
[10]	Xiao Z H, Zhang Z Y, Guo W. A review:The calibration of ground-based,airborne and satellite-borne microwave radiometers[J].Remote Sensing Technology and Application 2000(2):113-120.
[11]	曹海翊, 高洪涛, 赵晨光. 我国陆地定量遥感卫星技术发展[J]. 航天器工程, 2018,27(4):1-9.
[11]	Cao H Y, Gao H T, Zhao C G. Development of China land quantitative remote sensing satellite technology[J]. Spacecraft Engineering, 2018,27(4):1-9.
[12]	武佳丽, 余涛, 顾行发, 等. 中国资源卫星现状与应用趋势概述[J].遥感信息, 2008(6):96-101.
[12]	Wu J L, Yu T, Gu X F, et al. Status and application trend of Chinese earth resource satellites[J].Remote Sensing Information 2008(6):96-101.
[13]	岳涛, 黄宇民, 刘品雄, 等. 未来中国卫星遥感器的发展分析[J].航天器工程, 2008(4):77-82.
[13]	Yue T, Huang Y M, Liu P X, et al. Analysis of China’s future satellite remote sensor development[J].Spacecraft Engineering 2008(4):77-82.
[14]	孙振亚. 高集成度模块化CCD成像系统关键技术研究[D].长春:中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2019.
[14]	Sun Z Y. Research on key technologies of high integration modular CCD imaging system[D].Changchun:University of Chinese Academy of Sciences(Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences), 2019.
[15]	王涛, 张艳, 张永生, 等. 国产机载大视场三线阵CCD相机GNSS偏心矢量和IMU视轴偏心角标定技术[J]. 测绘学报, 2018,47(11):1474-1486.
[15]	Wang T, Zhang Y, Zhang Y S, et al. Investigation on GNSS lever arms and IMU boresight misalignment calibration of domestic airborne wide-field three CCD camera[J]. Acta Geodaetica et Cartographica Sinica, 2018,47(11):1474-1486.
[16]	王密, 杨博, 李德仁, 等. 资源三号全国无控制整体区域网平差关键技术及应用[J]. 武汉大学学报(信息科学版), 2017,42(4):427-433.
[16]	Wang M, Yang B, Li D R, et al. Technologies and applications of block adjustment without control for ZY-3 images covering China[J]. Geomatics and Information Science of Wuhan University, 2017,42(4):427-433.
[17]	马文坡. 航天光学遥感技术[M]. 北京: 中国科学技术出版社, 2011.
[17]	Ma W P. Space optical remote sensing technology[M]. Beijing: Science and Technology of China Press, 2011.
[18]	向世明, 樊学武, 何娜, 等. 微光遥感成像技术研发动态评述[J]. 激光与光电子学进展, 2018,55(2):89-100.
[18]	Xiang S M, Fan X W, He N, et al. Review on low light level remote sensing imaging technology[J]. Laser & Optoelectronics Progress, 2018,55(2):89-100.
[19]	孙武. 推扫式航天遥感相机动态范围拓展方法研究[D].长春:中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2018.
[19]	Sun W. Dynamic range extending method for push-broom space remote sensing cameras[D].Changchun:University of Chinese Academy of Sciences(Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences), 2018.
[20]	丁蕾, 袁银麟, 郑小兵, 等. 高光谱遥感器现场光谱定标精度验证方法研究[J]. 应用光学, 2017,38(3):463-468.
[20]	Ding L, Yuan Y L, Zheng X B, et al. Verification method of spectral calibration accuracy for hyperspectral remote sensors[J]. Journal of Applied Optics, 2017,38(3):463-468.
[21]	方煜. 成像光谱仪光学系统设计与像质评价研究[D].(西安:中国科学院研究生院西安光学精密机械研究所),2013.
[21]	Fang Y. Optical design of imaging spectrometer and research on the assessment of image quality[D].Xi’an:Chinese Academy of Sciences(Xi’an Institute of Optics and Precision Mechanics), 2013.
[22]	冯蕾, 魏立冬, 杨雷, 等. 双通道曲面棱镜高光谱成像系统设计[J]. 光学学报, 2019,39(5):149-154.
[22]	Feng L, Wei L D, Yang L, et al. Design of double-channel hyperspectral imaging system based on curved prism[J]. Acta Optica Sinica, 2019,39(5):149-154.
[23]	刘扬阳, 吕群波, 曾晓茹, 等. 静态计算光谱成像仪图谱反演的关键数据处理技术[J]. 物理学报, 2013,62(6):25-32.
[23]	Liu Y Y, Lyu Q B, Zeng X R, et al. Critical data processing technology for spectral image inversion in a static computational spectral imager[J]. Acta Physica Sinica, 2013,62(6):25-32.
[24]	郑鸿瑞, 徐志刚, 甘乐, 等. 合成孔径雷达遥感地质应用综述[J]. 国土资源遥感, 2018,30(2):12-20.doi: 10.6046/gtzyyg.2018.02.03.
[24]	Zheng H R, Xu Z G, Gan L, et al. Synthetic aperture Radar remote sensing technology in geological application:A review[J]. Remote Sensing for Land and Resources, 2018,30(2):12-20.doi: 10.6046/gtzyyg.2018.02.03.
[25]	李晓芳, 王娜, 史德杰. 雷达卫星遥感的发展及应用现状[J].卫星应用, 2013(5):44-50.
[25]	Li X F, Wang N, Shi D J. Development and application of Radar satellite remote sensing[J].Satellite Application 2013(5):44-50.
[26]	孙宏海, 何舒文, 吴培, 等. 高动态科学级CMOS相机设计与成像分析[J]. 液晶与显示, 2017,32(3):240-248.
[26]	Sun H H, He S W, Wu P, et al. Design and imaging analysis of high dynamics scientific CMOS camera[J]. Chinese Journal of Liquid Crystals and Displays, 2017,32(3):240-248.
[27]	曹旗磊, 赵明, 董丽丽, 等. 航天遥感相机及参数优化方法[J]. 激光与光电子学进展, 2017,54(3):295-301.
[27]	Cao Q L, Zhao M, D L L, et al. Optimization of remote sensing camera and its parameters[J]. Laser & Optoelectronics Progress, 2017,54(3):295-301.
[28]	龚学艺. 空间大面阵凝视成像若干关键技术研究[D].上海:中国科学院研究生院上海技术物理研究所,2014.
[28]	Gong X Y. The key technology research of space staring imaging with a large area array image sensor[D].Shanghai:Chinese Academy of Sciences(Shanghai Institute of Technical Physics), 2014.
[29]	杨秀彬, 姜丽, 金光. 数字域时间延迟积分时间CMOS相机高分“凝视”成像设计分析[J]. 光学学报, 2012,32(9):103-109.
[29]	Yang X B, Jiang L, Jin G. Design and analysis of CMOS camera based on TDI in digital domain to realize high-resolution staring imaging[J]. Acta Optica Sinica, 2012,32(9):103-109.
[30]	曹松. 科学卫星引领颠覆性空间技术创新[J]. 中国光学, 2019,12(3):421-424.
[30]	Cao S. Space science satellites lead to disruptive space technologies innovation[J]. Chinese Optics, 2019,12(3):421-424.
[31]	陈世平. 航天遥感科学技术的发展[J]. 航天器工程, 2009,18(2):1-7.
[31]	Chen S P. Development of space remote sensing science and technology[J]. Spacecraft Engineering, 2009,18(2):1-7.
[32]	张熠天, 高伟, 谭龙. 地球资源卫星产品服务质量评价体系设计[J].科研管理, 2015(s1):528-536.
[32]	Zhang Y T, Gao W, Tan L. A research on the evaluation index system for the products of earth resource satellites[J].Science Research Management 2015(s1):528-536.
[33]	云菲. 中国遥感卫星地面站简介[J].卫星应用, 2015(5):49-50.
[33]	Yun F. Brief introduction of China remote sensing ground station[J].Satellite Application 2015(5):49-50.
[34]	李德仁, 李明. 无人机遥感系统的研究进展与应用前景[J]. 武汉大学学报(信息科学版), 2014,39(5):505-513,540. doi: 10.13203/j.whugis20140045 url: http://ch.whu.edu.cn/CN/abstract/abstract2977.shtml
[34]	Li D R, Li M. Research advance and application prospect of unmanned aerial vehicle remote sensing system[J]. Geomatics and Information Science of Wuhan University, 2014,39(5):505-513,540. doi: 10.13203/j.whugis20140045 url: http://ch.whu.edu.cn/CN/abstract/abstract2977.shtml
[35]	郎城. 无人机在区域土地利用动态监测中的应用[D]. 西安:西安科技大学, 2011.
[35]	Lang C. Application of unmanned aerial vehicle(UAV) in the dynamic monitoring of regional land use[D]. Xi’an:Xi’An University of Science and Technology, 2011.
[36]	周前飞, 刘晶红, 李刚. 面阵CCD航空相机斜视图像几何畸变校正误差分析[J]. 仪器仪表学报, 2014,35(s1):1-8.
[36]	Zhou Q F, Liu J H, Li G. Error analysis of geometric distortion correction of oblique images for array CCD aerial cameras[J]. Chinese Journal of Scientific Instrument, 2014,35(s1):1-8.
[37]	李德仁, 赵双明, 陆宇红, 等. 机载三线阵传感器影像区域网联合平差[J].测绘学报, 2007(3):245-250.
[37]	Li D R, Zhao S M, Lu Y H, et al. Combined block adjustment for airborne three-line CCD scanner images[J].Acta Geodaetica et Cartographica Sinica 2007(3):245-250.
[38]	陈敬业, 时尧成. 固态激光雷达研究进展[J]. 光电工程, 2019,46(7):47-57.
[38]	Chen J Y, Shi Y C. Research progress in solid-state LiDAR[J]. Opto-Electronic Engineering, 2019,46(7):47-57.
[39]	吴诚, 邢文革, 夏凌昊. 光纤阵列编码成像激光雷达系统[J]. 现代雷达, 2019,41(1):5-8.
[39]	Wu C, Xing W G, Xia L H. Coded imaging IiDAR system based on fiber array[J]. Modern Radar, 2019,41(1):5-8.
[40]	吴曼青. 数字阵列雷达及其进展[J].中国电子科学研究院学报, 2006(1):11-16.
[40]	Wu M Q. The development of digital array Radar[J].Journal of China Academy of Electronics and Information Technology 2006(1):11-16.
[41]	桂德竹, 张成成, 洪志刚. 我国航空遥感发展现状及若干建议[J]. 遥感信息, 2013,28(1):119-122,48.
[41]	Gui D Z, Zhang C C, Hong Z G. Development status and industrialization recommendation of aerial remote sensing technology in China[J]. Remote Sensing Information, 2013,28(1):119-122,48.
[42]	沈汀, 耿俊杰, 孙瑞宝. 机载双天线InSAR基线的工程设计与验证技术研究[J]. 高技术通讯, 2013,23(8):773-780.
[42]	Shen T, Geng J J, Sun R B. Engineering design and verification of the baseline for airborne dual-antenna InSAR[J]. High Technology Letters, 2013,23(8):773-780.
[43]	杨博. 基于光子晶体光纤的谐振式陀螺关键技术研究[D]. 哈尔滨:哈尔滨工程大学, 2014.
[43]	Yang B. Research on key technologies of photonic crystal fiber resonator optic gryroscope[D]. Harbin:Harbin Engineering University, 2014.
[44]	胡正伟. 分析航测遥感装备与技术的发展[J].江西建材, 2014(1):219-220.
[44]	Hu Z W. Analysis of aerial survey and remote sensing equipment and technology development[J].Jiangxi Building Materials 2014(1):219-220.
[45]	王红闯, 王敏. 河南省引进首台自然资源移动监测车[J].资源导刊, 2018(6):37.
[45]	Wang H C, Wang M. Introduction of the first natural resources mobile monitoring vehicle in Henan Province[J].Resources Herald 2018(6):37.
[46]	李忠强, 张洪欣, 马龙. 海监技术装备保障支撑系统建设与管理[J]. 海洋开发与管理, 2013,30(5):48-50.
[46]	Li Z Q, Zhang H X, Ma L. Construction and management of support system for marine supervision technical equipment[J]. Ocean Development and Management, 2013,30(5):48-50.
[47]	王占宏, 白穆, 李宏建. 地理空间大数据服务自然资源调查监测的方向分析[J]. 地理信息世界, 2019,26(1):1-5.
[47]	Wang Z H, Bai M, Li H J. Direction analysis on service for natural resource investigation and monitoring using geospatial big data[J]. Geomatics World, 2019,26(1):1-5.
[48]	张微微, 金媛, 包吉明, 等. 中国海洋生态环境监测发展历程与思考[J].世界环境, 2019(3):30-32.
[48]	Zhang W W, Jin Y, Bao J M, et al. The development history of and thinking on marine ecological environment monitoring in China[J].World Environment 2019(3):30-32.
[49]	张衍毓, 高秉博, 郭旭东, 等. 国土空间监测网络布局优化方法研究[J]. 中国土地科学, 2018,32(1):11-19.
[49]	Zhang Y Y, Gao B B, Guo X D, et al. Spatial optimized distribution method for China land monitoring network[J]. China Land Science, 2018,32(1):11-19.
[50]	高春东, 何洪林. 野外科学观测研究站发展潜力大应予高度重视[J]. 中国科学院院刊, 2019,34(3):344-348.
[50]	Gao C D, He H L. Great importance should be attached to development potential of field scientific observation and research[J]. Bulletin of the Chinese Academy of Sciences, 2019,34(3):344-348.

[1]	LI Weiguang, HOU Meiting. A review of reconstruction methods for remote-sensing-based time series data of vegetation and some examples[J]. Remote Sensing for Natural Resources, 2022, 34(1): 1-9.
[2]	DING Bo, LI Wei, HU Ke. Inversion of total suspended matter concentration in Maowei Sea and its estuary, Southwest China using contemporaneous optical data and GF SAR data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 10-17.
[3]	GAO Qi, WANG Yuzhen, FENG Chunhui, MA Ziqiang, LIU Weiyang, PENG Jie, JI Yanzhen. Remote sensing inversion of desert soil moisture based on improved spectral indices[J]. Remote Sensing for Natural Resources, 2022, 34(1): 142-150.
[4]	QIN Dahui, YANG Ling, CHEN Lunchao, DUAN Yunfei, JIA Hongliang, LI Zhenpei, MA Jianqin. A study on the characteristics and model of drought in Xinjiang based on multi-source data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 151-157.
[5]	YANG Wang, HE Yi, ZHANG Lifeng, WANG Wenhui, CHEN Youdong, CHEN Yi. InSAR monitoring of 3D surface deformation in Jinchuan mining area, Gansu Province[J]. Remote Sensing for Natural Resources, 2022, 34(1): 177-188.
[6]	LIU Mingxing, LIU Jianhong, MA Minfei, JIANG Ya, ZENG Jingchao. Monitoring of Zanthoxylum bungeanum Maxim planting using GF-2 PMS images and the random forest algorithm: A case study of Linxia, Gansu Province[J]. Remote Sensing for Natural Resources, 2022, 34(1): 218-229.
[7]	ZHANG Qinrui, ZHAO Liangjun, LIN Guojun, WAN Honglin. Ecological environment assessment of three-river confluence in Yibin City using improved remote sensing ecological index[J]. Remote Sensing for Natural Resources, 2022, 34(1): 230-237.
[8]	HE Peng, TONG Liqiang, GUO Zhaocheng, TU Jienan, WANG Genhou. A study on hidden risks of glacial lake outburst floods based on relief amplitude: A case study of eastern Shishapangma[J]. Remote Sensing for Natural Resources, 2022, 34(1): 257-264.
[9]	LIU Wen, WANG Meng, SONG Ban, YU Tianbin, HUANG Xichao, JIANG Yu, SUN Yujiang. Surveys and chain structure study of potential hazards of ice avalanches based on optical remote sensing technology: A case study of southeast Tibet[J]. Remote Sensing for Natural Resources, 2022, 34(1): 265-276.
[10]	WANG Qian, REN Guangli. Application of hyperspectral remote sensing data-based anomaly extraction in copper-gold prospecting in the Solake area in the Altyn metallogenic belt, Xinjiang[J]. Remote Sensing for Natural Resources, 2022, 34(1): 277-285.
[11]	LYU Pin, XIONG Liyuan, XU Zhengqiang, ZHOU Xuecheng. FME-based method for attribute consistency checking of vector data of mines obtained from remote sensing monitoring[J]. Remote Sensing for Natural Resources, 2022, 34(1): 293-298.
[12]	ZHANG Daming, ZHANG Xueyong, LI Lu, LIU Huayong. Remote sensing image segmentation based on Parzen window density estimation of super-pixels[J]. Remote Sensing for Natural Resources, 2022, 34(1): 53-60.
[13]	XUE Bai, WANG Yizhe, LIU Shuhan, YUE Mingyu, WANG Yiying, ZHAO Shihu. Change detection of high-resolution remote sensing images based on Siamese network[J]. Remote Sensing for Natural Resources, 2022, 34(1): 61-66.
[14]	SONG Renbo, ZHU Yuxin, GUO Renjie, ZHAO Pengfei, ZHAO Kexin, ZHU Jie, CHEN Ying. A method for 3D modeling of urban buildings based on multi-source data integration[J]. Remote Sensing for Natural Resources, 2022, 34(1): 93-105.
[15]	LI Mengmeng, FAN Xueting, CHEN Chao, LI Qiannan, YANG Jin. Monitoring and interpretation of land subsidence in mining areas in Xuzhou City during 2016—2018[J]. Remote Sensing for Natural Resources, 2021, 33(4): 43-54.

Viewed

Full text

Abstract

Cited

Shared

Discussed