"谱遥感"与地球体检计划

李志忠; 汪大明; 王建华; 孙萍萍; 柳波; 陈江; 汤晓君; 帅琴; 杨日红; 刘拓; 赵英俊; 戴慧敏; 韩海辉; 段星星; 赵君

doi:10.3799/dqkx.2020.349

Volume 46 Issue 9

Oct. 2021

Turn off MathJax

Article Contents

Article Navigation > Earth Science > 2021 > 46(9): 3352-3364

Li Zhizhong, Wang Daming, Wang Jianhua, Sun Pingping, Liu Bo, Chen Jiang, Tang Xiaojun, Shuai Qin, Yang Rihong, Liu Tuo, Zhao Yingjun, Dai Huimin, Han Haihui, Duan Xingxing, Zhao Jun, 2021. Application of Spectral Remote Sensing Technology in Inspection of the Earth. Earth Science, 46(9): 3352-3364. doi: 10.3799/dqkx.2020.349

Citation:

Li Zhizhong, Wang Daming, Wang Jianhua, Sun Pingping, Liu Bo, Chen Jiang, Tang Xiaojun, Shuai Qin, Yang Rihong, Liu Tuo, Zhao Yingjun, Dai Huimin, Han Haihui, Duan Xingxing, Zhao Jun, 2021. Application of Spectral Remote Sensing Technology in Inspection of the Earth. Earth Science, 46(9): 3352-3364. doi: 10.3799/dqkx.2020.349

Citation:

Li Zhizhong, Wang Daming, Wang Jianhua, Sun Pingping, Liu Bo, Chen Jiang, Tang Xiaojun, Shuai Qin, Yang Rihong, Liu Tuo, Zhao Yingjun, Dai Huimin, Han Haihui, Duan Xingxing, Zhao Jun, 2021. Application of Spectral Remote Sensing Technology in Inspection of the Earth. Earth Science, 46(9): 3352-3364. doi: 10.3799/dqkx.2020.349

PDF( 2960 KB)

Application of Spectral Remote Sensing Technology in Inspection of the Earth

doi: 10.3799/dqkx.2020.349

1.
Xi'an Center, China Geological Survey, Xi'an 710054, China
2.
Tianjin Center, China Geological Survey, Tianjin 300170, China
3.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
4.
School of Earth Sciences, Northeast Petroleum University, Daqing 163318, China
5.
Shenyang Center, China Geological Survey, Shenyang 110000, China
6.
School of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, China
7.
Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, China
8.
Beijing Zhonghaiyun Gold Mining Consulting Co., Ltd., Beijing 100101, China
9.
Beijing Research Institute of Uranium Geology, Beijing 100029, China

Received Date: 2020-11-04
Available Online: 2021-10-14
Publish Date: 2021-10-14

Abstract

Abstract

The increasing human activities have gradually brought negative effect to the health of the Earth. In order to grasp comprehensively the health status of the Earth, an integrated inspection of the Earth is needed to be performed. Due to its advantages of dynamic monitoring, rapid inspection and wide range of application, spectral remote sensing technology has been one of the best means of monitoring and analyzing the status of resources, environment, and ecology. In this paper, the definition, research contents and key technologies of spectral remote sensing are presented. The application requirements of spectral remote sensing to realize a healthy Earth are summarized. In addition, the construction method of the integrated spectral remote sensing platform from space, air and ground is introduced. The technical system to improve the effect of the Earth physical examination is discussed. Finally, the principles and prospects for carrying out the Earth physical examination using spectral remote sensing technology are proposed.
- spectral remote sensing,
- health of the Earth,
- inspection of the Earth,
- ground-air-space integration,
- dynamic monitoring,
- geophysics

FullText(HTML)

References(67)

References

Birkett, S., 2019. Sixth Global Environment Outlook GEO-6. United Nations Environment Programme, Cambridge.

Bruzzone, L., Casadio, S., Cossu, R., et al., 2003. A System for Monitoring NO₂ Emissions from Biomass Burning by Using GOME and ATSR-2 Data. International Journal of Remote Sensing, 24(8): 1709-1721. https://doi.org/10.1080/01431160210144714

Cao, C. X., Chen, W., Huang, X. Y., et al., 2017. Index System for Diagnosis of Environmental Health by Remote Sensing. Science Press, Beijing (in Chinese).

Che, Y.F., Zhao, Y.J., Ye, F.W., 2017. Extraction and Analysis of Hyperspectral Remote Sensing Alteration Mineral Based on Spectral Characteristic Parameters. Geological Review, 63(S1): 197-198 (in Chinese with English abstract).

Chikhaoui, M., Bonn, F., Bokoye, A. I., et al., 2005. A Spectral Index for Land Degradation Mapping Using ASTER Data: Application to a Semi-Arid Mediterranean Catchment. International Journal of Applied Earth Observation and Geoinformation, 7(2): 140-153. https://doi.org/10.1016/j.jag.2005.01.002

Clark, R. N., Swayze, G. A., Livo, K. E., et al., 2003. Imaging Spectroscopy: Earth and Planetary Remote Sensing with the USGS Tetracorder and Expert Systems. Journal of Geophysical Research: Planets, 108(E12): 5131. https://doi.org/10.1029/2002je001847

Corradini, S., Pugnaghi, S., Teggi, S., et al., 2003. Will ASTER See the Etna SO₂ Plume?. International Journal of Remote Sensing, 24(6): 1207-1218. https://doi.org/10.1080/01431160210153084

Duro, D. C., Coops, N. C., Wulder, M. A., et al., 2007. Development of a Large Area Biodiversity Monitoring System Driven by Remote Sensing. Progress in Physical Geography: Earth and Environment, 31(3): 235-260. https://doi.org/10.1177/0309133307079054

Feng, Y. L., Yang, J. J., Wang, X. G., 2018. Research Progress of Quantitative Evaluation on Water and Soil Loss by Remote Sensing Based on Gis. Geology and Resources, 27(3): 279-283 (in Chinese with English abstract).

Goetz, A. F. H., Vane, G., Solomon, J. E., et al., 1985. Imaging Spectrometry for Earth Remote Sensing. Science, 228(4704): 1147-1153. https://doi.org/10.1126/science.228.4704.1147

He, C., Feng, Z. K., Yuan, J. J., et al., 2012. Advances in the Research on Hyperspectral Remote Sensing in Biodiversity and Conservation. Spectroscopy and Spectral Analysis, 32(6): 1628-1632 (in Chinese with English abstract). http://www.ncbi.nlm.nih.gov/pubmed/22870654

Hou, Z. Q., 2020. Promote Basic Research with Strategic Thinking. China Natural Resources News, Beijing (in Chinese).

Hunt, G. R., 1977. Spectral Signatures of Particulate Minerals in the Visible and near Infrared. Geophysics, 42(3): 501-513. https://doi.org/10.1190/1.1440721

Ji, H. Y., Zhao, B. Y., 2008. Summarization of Remote Sensing Technology on Environmental Monitoring. Environmental Science Survey, 27(2): 21-24 (in Chinese with English abstract).

Li, S. J., Wang, X. J., 2002. The Spectral Features Analysis and Quantitative Remote Sensing Advances of Inland Water Quality Parameters. Geography and Territorial Research, 18(2): 26-30 (in Chinese with English abstract). http://search.cnki.net/down/default.aspx?filename=DLGT200202007&dbcode=CJFD&year=2002&dflag=pdfdown

Li, Z. Z., 2020. Selenium-Enriched Soil Mapping Using Airborne SASI Images. Geoderma, 363: 114133. https://doi.org/10.1016/j.geoderma.2019.114133

Li, Z. Z., Wang, D. M., Liu, D. C., et al., 2015. Hyperspectral Remote Sensing Technology and Its Progress in Resources Exploration. Earth Science, 40(8): 1287-1294 (in Chinese with English abstract).

Li, Z. Z., Yang, R. H., Dang, F. X., et al., 2009. The Hyperspectral Remote Sensing Technology and Its Application. Geological Bulletin of China, 28(Z1): 270-277 (in Chinese with English abstract).

Lin, H., 2011. Research on Forest Tree Species with the Hyperspectral Remote Sensing Technology. China Forestry Publishing House, Beijing (in Chinese).

Lu, D. H., Zhao, Y. J., Zhang, D. H., et al., 2017. Analysis of the Role of Multi-Source Remote Sensing Data in Geological Environment Stability Assessment. Geological Review, 63(S1): 399-400 (in Chinese with English abstract).

Marco, L., 2018. Living Planet Report. World Wildlife Fund, Washington, D.C. .

Pu, R. L., Gong, P., 2000. Hyperspectral Remote Sensing and Its Application. Higher Education Press, Beijing (in Chinese).

Qin, K., Chen, J. P., Zhao, Y. J., et al., 2015. Study on Lithological Identification Method Based on Airborne Hyper-Spectral Data. Mineral Exploration, 6(5): 594-600 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-YSJS201505014.htm

Rencz, A. N., 1999. Remote Sensing for the Earth Sciences: Manual of Remote Sensing (3rd Edition). John Wiley and Sons, Toronto.

Shu, X. Z., Yin, Q., Kuang, D. B., 2000. Relationship between Algal Chlorophyll Concentration and Spectral Reflectance of Inland Water. Journal of Remote Sensing, 4(1): 41-45 (in Chinese with English abstract).

Tong, Q. X., 2008. Development of Hyperspectral Remote Sensing in China. China Survey and Mapping News, Beijing (in Chinese)

Wang, J. N., Li, Z. Z., Zhang, L. F., et al., 2012. "Spectral Crust" Project: Research on New Mineral Exploration Technology. Journal of Geo-Information Science, 14(3): 344-351 (in Chinese with English abstract). doi: 10.3724/SP.J.1047.2012.00344

Wang, J. N., Zhang, B., Liu, J. G., et al., 1999. Hyperspectral Data Mining: Toward Target Recognition and Classification. Journal of Image and Graphics, 4(11): 957-964 (in Chinese with English abstract)

Wang, Y. X., 2020. Innovative Development of Medical Geology: A One Health Perspective. Earth Science, 45(4): 1093-1102 (in Chinese with English abstract).

Wu, C. S., Xiang, Y. Q., Zheng, L. F., et al., 2000. Estimating Chlorophyll Density of Crop Canopies by Using Hyperspectral Data. Journal of Remote Sensing, 4(3): 228-232 (in Chinese with English abstract).

Wu, J., Peng, D. L., 2011. Advances in Researches on Hyperspectral Remote Sensing Forestry Information-Extracting Technology. Spectroscopy and Spectral Analysis, 31(9): 2305-2312 (in Chinese with English abstract). http://www.ncbi.nlm.nih.gov/pubmed/22097816/

Yang, J. J., Bai, L., Wu, S., 2019. Study on the Erosion in Typical Black Soil Areas of Heilongjiang Province by Remote Sensing Monitoring Technology. Geology and Resources, 28(2): 193-199 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTotal-GJSD201902013.htm

Ye, F. W., Liu, D. C., Zhao, Y. J., 2011. Airborne Hyper-Spectral Survey System CASI/SASI and Its Preliminary Application in Uranium Exploration. World Nuclear Geoscience, 28(4): 231-236 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-GWYD201104010.htm

Zhang, C. F., Hao, L. N., Wang, S. J., et al., 2020. Geological Units Classification with Texture-Spectral Synergy of Multi-Sourced Remote Sensing Images. Earth Science, 45(5): 1844-1854 (in Chinese with English abstract).

Zhang, D. H., Zhao, Y. J., Qin, K., 2018a. Design and Construction of the Typical Ground Target Spectral Information System. Remote Sensing for Land & Resources, 30(4): 206-211 (in Chinese with English abstract). http://www.zhangqiaokeyan.com/academic-journal-cn_remote-sensing-land-resources_thesis/0201270245203.html

Zhang, D. H., Zhao, Y. J., Qin, K., et al., 2018b. A Review of Hyperspectral Multivariate Information Extraction Models for Soils. Soil and Fertilizer Sciences in China, (2): 22-28 (in Chinese with English abstract). http://www.zhangqiaokeyan.com/academic-journal-cn_soil-fertilizer-sciences-china_thesis/0201257078546.html

Zhao, D. Z., 1999. Research on Monitoring System of Marine Environmental Pollution Based on Satellite Remote Sensing Technique. Remote Sensing Information, 14(2): 22-25 (in Chinese with English abstract).

Zheng, L. F., Wang, J. N., 1992. A Study on Imaging Spectrometry and Its Extraction of Image Spectral Information. Remote Sensing of Environmental China, 7(1): 49-58 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTOTAL-YGXB199201006.htm

Zhong, Y., 2016. Remote Sensing Estimation of Heavy Metal Cd and Pb in Cultivated Soil Based on HSI Hyperspectral Data (Dissertation). Sichuan Agriculture University, Ya'an (in Chinese with English abstract).

曹春香, 陈伟, 黄晓勇, 等, 2017. 环境健康遥感诊断指标体系. 北京: 科学出版社.

车永飞, 赵英俊, 叶发旺, 2017. 基于光谱特征参量的高光谱遥感蚀变矿物提取与分析. 地质论评, 63(S1): 197-198. https://www.cnki.com.cn/Article/CJFDTOTAL-DZLP2017S1096.htm

冯雨林, 杨佳佳, 王晓光, 2018. 基于GIS技术的水土流失遥感定量评价研究进展. 地质与资源, 27(3): 279-283. doi: 10.3969/j.issn.1671-1947.2018.03.011

何诚, 冯仲科, 袁进军, 等, 2012. 高光谱遥感技术在生物多样性保护中的应用研究进展. 光谱学与光谱分析, 32(6): 1628-1632. doi: 10.3964/j.issn.1000-0593(2012)06-1628-05

侯增谦, 2020. 用战略思维推动基础研究. 北京: 中国自然资源报.

季惠颖, 赵碧云, 2008. 遥感技术在环境监测中的应用综述. 环境科学导刊, 27(2): 21-24 doi: 10.3969/j.issn.1673-9655.2008.02.006

李素菊, 王学军, 2002. 内陆水体水质参数光谱特征与定量遥感. 地理学与国土研究, 18(2): 26-30. doi: 10.3969/j.issn.1672-0504.2002.02.008

李志忠, 汪大明, 刘德长, 等, 2015. 高光谱遥感技术及资源勘查应用进展. 地球科学, 40(8): 1287-1294. doi: 10.3799/dqkx.2015.108

李志忠, 杨日红, 党福星, 等, 2009. 高光谱遥感卫星技术及其地质应用. 地质通报, 28(Z1): 270-277. https://www.cnki.com.cn/Article/CJFDTOTAL-ZQYD2009Z1021.htm

林辉, 2011. 森林树种高光谱遥感研究. 北京: 中国林业出版社.

陆冬华, 赵英俊, 张东辉, 等, 2017. 多元遥感数据在地质环境稳定性评价的作用分析. 地质论评, 63(S1): 399-400. https://www.cnki.com.cn/Article/CJFDTOTAL-DZLP2017S1192.htm

浦瑞良, 宫鹏, 2000. 高光谱遥感及其应用. 北京: 高等教育出版社.

秦凯, 陈建平, 赵英俊, 等, 2015. 基于航空高光谱遥感岩性识别技术研究. 矿产勘查, 6(5): 594-600. doi: 10.3969/j.issn.1674-7801.2015.05.014

疏小舟, 尹球, 匡定波, 2000. 内陆水体藻类叶绿素浓度与反射光谱特征的关系. 遥感学报, 4(1): 41-45. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB200001007.htm

童庆禧, 2008. 我国高光谱遥感的发展. 北京: 中国测绘报.

王晋年, 李志忠, 张立福, 等, 2012. "光谱地壳"计划: 探索新一代矿产勘查技术. 地球信息科学学报, 14(3): 344-351. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXX201203010.htm

王晋年, 张兵, 刘建贵, 等, 1999. 以地物识别和分类为目标的高光谱数据挖掘. 中国图象图形学报, 4(11): 957-964. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB199911012.htm

王焰新, 2020. "同一健康"视角下医学地质学的创新发展. 地球科学, 45(4): 1093-1102. doi: 10.3799/dqkx.2020.060

吴长山, 项月琴, 郑兰芬, 等, 2000. 利用高光谱数据对作物群体叶绿素密度估算的研究. 遥感学报, 4(3): 228-232. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB200003012.htm

吴见, 彭道黎, 2011. 高光谱遥感林业信息提取技术研究进展. 光谱学与光谱分析, 31(9): 2305-2312. https://www.cnki.com.cn/Article/CJFDTOTAL-GUAN201109000.htm

杨佳佳, 白磊, 吴嵩, 2019. 黑龙江典型黑土区土壤侵蚀遥感监测技术研究. 地质与资源, 28(2): 193-199. doi: 10.3969/j.issn.1671-1947.2019.02.012

叶发旺, 刘德长, 赵英俊, 2011. CASI/SASI航空高光谱遥感测量系统及其在铀矿勘查中的初步应用. 世界核地质科学, 28(4): 231-236. doi: 10.3969/j.issn.1672-0636.2011.04.008

张翠芬, 郝利娜, 王少军, 等, 2020. 多源遥感数据图谱协同岩石单元分类方法. 地球科学, 45(5): 1844-1854. doi: 10.3799/dqkx.2019.168

张东辉, 赵英俊, 秦凯, 2018a. 典型目标地面光谱信息系统设计与实现. 国土资源遥感, 30(4): 206-211. https://www.cnki.com.cn/Article/CJFDTOTAL-GTYG201804031.htm

张东辉, 赵英俊, 秦凯, 等, 2018b. 高光谱土壤多元信息提取模型综述. 中国土壤与肥料, (2): 22-28. https://www.cnki.com.cn/Article/CJFDTOTAL-TRFL201802004.htm

赵冬至, 1999. 海洋环境污染与灾害卫星遥感业务化监测系统研究. 遥感信息, 14(2): 22-25. doi: 10.3969/j.issn.1000-3177.1999.02.009

郑兰芬, 王晋年, 1992. 成像光谱遥感技术及其图像光谱信息提取的分析研究. 环境遥感, 7(1): 49-58. https://www.cnki.com.cn/Article/CJFDTOTAL-YGXB199201006.htm

钟燕, 2016. 基于HSI高光谱数据的耕地土壤重金属镉、铅含量遥感反演(硕士学位论文). 雅安: 四川农业大学.

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(6) / Tables(3)

Get Citation

PDF

XML

Article views (1758) PDF downloads(73)

Application of Spectral Remote Sensing Technology in Inspection of the Earth

doi: 10.3799/dqkx.2020.349

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Proportional views

Export File

Citation

Format

Content