Anterior|Siguiente

A review of the development of remote sensing field experiments and product validation in China

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：wenjg@aircas.ac.cn
  • Introduction：闻建光，研究方向为定量遥感。E-mail： wenjg@aircas.ac.cn
WEN Jianguang110,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

LIU Qinhuo110,  
  • Affiliation：

    Research Institute of Forest Resource Information Techniques, Chinese Academy of Foresty, Beijing 100091, China

LI Zengyuan2,  
  • Affiliation：

    National Tibetan Plateau Data Center, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

LI Xin310,  
  • Affiliation：

    State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

LIU Shaomin4,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

XIAO Qing110,  
  • Affiliation：

    Research Institute of Forest Resource Information Techniques, Chinese Academy of Foresty, Beijing 100091, China

GAO Zhihai2,  
  • Affiliation：

    Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China

MA Mingguo5,  
  • Affiliation：

    Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

CHE Tao610,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

LIU Liangyun110,  
  • Affiliation：

    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

FANG Hongliang710,  
  • Affiliation：

    State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

YAN Guangjian4,  
  • Affiliation：

    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

GE Yong710,  
  • Affiliation：

    Research Institute of Forest Resource Information Techniques, Chinese Academy of Foresty, Beijing 100091, China

CHEN Erxue2,  
  • Affiliation：

    National Satellite Meteorological Centre, China Meteorological Administration, Beijing 100081,China

ZHANG Yong8,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

MA Linling110,  
  • Affiliation：

    College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China

WU Xiaodan9,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

CHEN Xi1

resumen

Remote sensing experiments and products validation have always played an important role in the development of remote sensing science and technology. As an important way of understanding the natural characteristics, remote sensing experiments have played an important role in remote sensing science and technology research. Remote sensing product validation is crucial to ensuring the high accuracy of remote sensing algorithms and improving the quality of remote sensing products. Remote sensing experiments are the basis of validation because the ground truth, which is derived from field experiments, is the core of the validation. However, obtaining the ground truth is a complex systematic process, including optimized sampling, field observation, scale transformation, and validation. Thus, reducing the error of each process is important in obtaining high-quality ground truth.On April 6, 2022, China held the “First Forum on Remote Sensing Field Experiments and Products Validation” where intense exchanges and discussions on the key topics occurred, including remote sensing experiments and validation theory and technology, ground field observation and uncertainty, validation practice and platform, and the future development of remote sensing experiments and validation. More than 1000 scholars and students from different domestic scientific research institutes and universities attended the event.On the basis of reviewing the main progress in the field of remote sensing experiments and validation in China, thus paper summarizes the opinions and suggestions of the Chinese scientists who attended the meeting and expounds on the problems and challenges faced by China in terms of remote sensing field experiments and products validation. The development process of remote sensing experiments and products validation in China has three main development stages, namely, the remote sensing application experiment stage from the year of 1978, the quantitative remote sensing mechanism experiment stage from the year of 1994, and the comprehensive experiment stage of the quantitative remote sensing mechanism and validation. Significant progress has been made in experimental technology, validation technology, national specifications of product validation, and the validation system platform.Five related topics of remote sensing experiments and product validation have been discussed by 80 scientists, namely, the theoretical framework and basic theory of remote sensing product validation, ground observation and standardized data processing, land surface heterogeneity and scale transformation, product validation and evaluation, and system platform and data sharing.It should be considered systematically from the entire link key process of obtaining ground truth for remote sensing experiment and validation to truly become an important basis in ensuring the quality of satellite remote sensing products. Finally, the prospect of remote sensing experiment and validation in China is discussed. Remote sensing experiment and validation should be implemented from the joint efforts of national and even global scientific researchers to achieve global implementation through international cooperation and improve the ability of remote sensing experiments and product validation.

palabra clave

remote sensing experiment;product validation;optimize sampling;scale transformation;ground truth

References

  1. 1.
    Chen X P and Zhou S G. 1986. A review of Teng Chong aerial remote sensing experiment. Remote Sensing Information, (2): 11-12
  2. 2.
    Fang H L. 2020. Development and Validation of satellite Leaf Area Index (LAI) products in China. Remote Sensing Technology and Application, 35(5): 990-1003
  3. 3.
    Ge Y, Jin Y, Stein A, Chen Y H, Wang J H, Wang J F, Cheng Q M, Bai H X, Liu M X and Atkinson P M. 2019. Principles and methods of scaling geospatial Earth science data. Earth-Science Reviews, 197: 102897
  4. 4.
    Ge Y, Wang J H, Heuvelink G B M, Jin R, Li X and Wang J F. 2015. Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the Babao River basin, China. International Journal of Geographical Information Science, 29(1): 92-110
  5. 5.
    Gu X F, Yu T, Tian G L, Zhou S Y, Wei C J, Li J, Yu Q, Liu D H, Wei Z, Meng Q Y, Xu H, Guo H, Zhou X, Wang C M, Zang W Q, Huang X Z, Gao H L, Zheng F J, Liu M, Wang D, Zhao Y M, Wei X Q, Sun Y, Li B, Liao J and Ren X Y. 2016. Up to the higher altitude—the new “three campaigns” for the development of China spaceborne remote sensing application. Journal of Remote Sensing, 20(5): 781-793
  6. 6.
    He M，Wen J G，You D Q，Tang Y，Wu S B，Hao D L，Lin X W and Gong Z R. 2022. Review of forest Leaf Area Index retrieval over rugged terrain based on remotely sensed data. National Remote Sensing Bulletin,26(12):2451-2472
  7. 7.
    Jia Z Z, Liu S M, Xu Z W, Chen Y J and Zhu M J. 2012. Validation of remotely sensed evapotranspiration over the Hai River Basin, China. Journal of Geophysical Research: Atmospheres, 117(D13): D13113
  8. 8.
    Jin R, Li X, Yan B P, Li X H, Luo W M, Ma M G, Guo J W, Kang J, Zhu Z L and Zhao S J. 2014. A nested ecohydrological wireless sensor network for capturing the surface heterogeneity in the midstream areas of the Heihe River Basin, China. IEEE Geoscience and Remote Sensing Letters, 11(11): 2015-2019
  9. 9.
    Li X, Cheng G D, Liu S M, Xiao Q, Ma M G, Jin R, Che T, Liu Q H, Wang W Z, Qi Y, Wen J G, Li H Y, Zhu G F, Guo J W, Ran Y H, Wang S G, Zhu Z L, Zhou J, Hu X L and Xu Z W. 2013. Heihe watershed allied telemetry experimental research (HiWATER): scientific objectives and experimental design. Bulletin of the American Meteorological Society, 94(8): 1145-1160
  10. 10.
    Li X, Li X W, Li Z Y, Ma M G, Wang J, Xiao Q, Liu Q, Che T, Chen E X, Yan G J, Hu Z Y, Zhang L X, Chu R Z, Su P X, Liu Q H, Liu S M, Wang J D, Niu Z, Chen Y, Jin R, Wang W Z, Ran Y H, Xin X Z and Ren H Z. 2009. Watershed allied telemetry experimental research. Journal of Geophysical Research: Atmospheres, 114(D22): D22103
  11. 11.
    Li X, Liu S M, Yang X F, Ma Y F, He X L, Xu Z W, Xu T R, Song L S, Zhang Y, Hu X, Ju Q and Zhang X D. 2021. Upscaling evapotranspiration from a single-site to satellite pixel scale. Remote Sensing, 13(20): 4072
  12. 12.
    Li X, Ma M G, Wang J, Liu Q, Che T, Hu Z Y, Xiao Q, Liu Q H, Su P X, Chu R Z, Jin R, Wang W Z and Ran Y H. 2008. Simultaneous remote sensing and ground-based experiment in the Heihe river basin: scientific objectives and experiment design. Advances in Earth Science, 23(9): 897-914
  13. 13.
    Li X W. 2006. Review of the project of quantitative remote sensing of major factors for spatial-temporal heterogeneity on the land surface. Advances in Earth Science, 21(8): 771-780
  14. 14.
    Li X W, Wang J F, Wang J D and Liu Q H. 2001. Multi-Angle and Thermal Infrared Remote Sensing. Beijing: Science Press
  15. 15.
    Lin X W, Wen J G, Tang Y, Ma M G, You D Q, Dou B C, Wu X D, Zhu X B, Xiao Q and Liu Q H. 2018. A web-based land surface remote sensing products validation system (LAPVAS): application to albedo product. International Journal of Digital Earth, 11(3): 308-328
  16. 16.
    Liu F, Zhao Z B and Li X. 2022. Quantifying the representativeness errors caused by scale transformation of remote sensing data in stochastic ensemble data assimilation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15: 1968-1980
  17. 17.
    Liu Q H, Li X W and Chen L F. 2002. Field campaign for quantitative remote sensing in Beijing//IEEE International Geoscience and Remote Sensing Symposium. Toronto, ON, Canada: IEEE: 3133-3135
  18. 18.
    Liu Q H, Yan G J, Jiao Z T, Xiao Q, Wen J G, Liang S L and Wang J D. 2019. Geometric-optical remote sensing modeling to quantitative remote sensing theory and methodology development: in memory of academician Li Xiaowen. Journal of Remote Sensing, 23(1): 1-10
  19. 19.
    Liu Q H, Wen J G, Zhou X, Zhao J, Li Z Y, Li X, Ma M G, Wang W Z, Liao X H, Liu S M, Fan W J, Xiao Q, Zhong B, Li J, Xin X Z, Li L, Jia L, Gao Z H, Jin J D, Liang S, Xin J, Liao C J and Wu Y R. 2023. Technique System of remote sensing products generation and validation of GF common products. National Remote Sensing Bulletin, 27(3): 544-562
  20. 20.
    Liu S M, Li X, Xu Z W, Che T, Xiao Q, Ma M G, Liu Q H, Jin R, Guo J W, Wang L X, Wang W Z, Qi Y, Li H Y, Xu T R, Ran Y H, Hu X L, Shi S J, Zhu Z L, Tan J L, Zhang Y and Ren Z G. 2018. The Heihe integrated observatory network: a basin-scale land surface processes observatory in China. Vadose Zone Journal, 17(1): 1-21
  21. 21.
    Liu S M, Xu Z W, Wang W Z, Jia Z Z, Zhu M J, Bai J and Wang J M. 2011. A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem. Hydrology and Earth System Sciences, 15(4): 1291-1306
  22. 22.
    Liu S M, Xu Z W, Song L S, Zhao Q Y, Ge Y, Xu T R, Ma Y F, Zhu Z L, Jia Z Z and Zhang F. 2016. Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 230-231: 97-113
  23. 23.
    Liu S M, Xu Z W, Zhu Z L, Jia Z Z and Zhu M J. 2013. Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. Journal of Hydrology, 487: 24-38
  24. 24.
    Ma M G, Che T, Li X, Xiao Q, Zhao K and Xin X P. 2015. A prototype network for remote sensing validation in China. Remote Sensing, 7(5): 5187-5202
  25. 25.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2018. GB/T 36296-2018 Guide for the validation of remote sensing products. Beijing: Standards Press of China
  26. 26.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2020. GB/T 39468-2020 General methods for the validation of terrestrial quantitative remote sensing products. Beijing: Standards Press of China
  27. 27.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2021a. GB/T 40033-2021 Validation of land surface evapotranspiration remote sensing products. Beijing: Standards Press of China
  28. 28.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2021b. GB/T 40034-2021 Validation of leaf area index remote sensing products. Beijing: Standards Press of China
  29. 29.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2021c. GB/T 40038-2021 Validation of vegetation index remote sensing products. Beijing: Standards Press of China
  30. 30.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2021d. GB/T 40039-2021 Validation of soil moisture remote sensing products. Beijing: Standards Press of China
  31. 31.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2022a. GB/T 41279-2022 Validation of albedo remote sensing products. Beijing: Standards Press of China
  32. 32.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2022b. GB/T 41281-2022 Validation of photosynthetically active radiation remote sensing products. Beijing: Standards Press of China
  33. 33.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2022c. GB/T 41282-2022 Validation of fractional vegetation cover remote sensing products. Beijing: Standards Press of China
  34. 34.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023a. GB/T 41535-2022 Validation of aerosol optical depth remote sensing products. Beijing: Standards Press of China
  35. 35.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023b. GB/T 41536-2022 Validation of land cover remote sensing products. Beijing: Standards Press of China
  36. 36.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023c. GB/T 41537-2022 Validation of snow cover area remote sensing products. Beijing: Standards Press of China
  37. 37.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023d. GB/T 41534-2022 Validation of surface temperature remote sensing products. Beijing: Standards Press of China
  38. 38.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023d. GB/T 41540-2022 Selection and arrangement of the surface observation field for the validation of terrestrial remote sensing products. Beijing: Standards Press of China
  39. 39.
    State Administration for Market Regulation, Standardization Administration of the People’s Republic of China. 2023e. GB/T 41538-2022 Validation of surface emissivity remote sensing products. Beijing: Standards Press of China
  40. 40.
    Tong Q X, Tang C and Li H G. 1999. A creative action: the second experiment of Teng Chong aerial remote sensing. Journal of Geo-Information Science, 1(1): 67-75
  41. 41.
    Wen J G, Liu Q, Liu Q H, Xiao Q and Li X W. 2015. Modeling Bidirectional Reflectance Distribution Function and Albedo Retrieval Over land Surface. Beijing: Science Press
  42. 42.
    Wen J G, Wu X D, Wang J P, Tang R Q, Ma D J, Zeng Q C, Gong B C and Xiao Q. 2022. Characterizing the effect of spatial heterogeneity and the deployment of sampled plots on the uncertainty of ground “Truth” on a coarse grid scale: case study for near-infrared (NIR) surface reflectance. Journal of Geophysical Research: Atmospheres, 127(11): e2022JD036779
  43. 43.
    Wen J G, Xiao Q, Zhong S Y, Tang Y, Chen X, Wei Q F, Wu X D, Lin X W, Ouyang X Y, You D Q and Liu Q H. 2023. Technology system for product validation and algorithm test of GF common products and an application example. National Remote Sensing Bulletin, 27(3): 780-789
  44. 44.
    Wu X D, Wen J G, Xiao Q, Liu Q, Peng J J, Dou B C, Li X H, You D Q, Tang Y and Liu Q H. 2016. Coarse scale in situ albedo observations over heterogeneous snow-free land surfaces and validation strategy: a case of MODIS albedo products preliminary validation over northern China. Remote Sensing of Environment, 184: 25-39
  45. 45.
    Wu X D, Wen J G, Xiao Q, You D Q, Wang J P, Ma D J and Lin X W. 2021. A multiscale nested sampling method for representative albedo observations at various pixel scales. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 8193-8207
  46. 46.
    Wu X D, Wen J G, Xiao Q and You D Q. 2020. Upscaling of single site-based measurements for validation of long-term coarse-pixel albedo products. IEEE Transactions on Geoscience and Remote Sensing, 58(5): 3411-3425
  47. 47.
    Wu X D, Xiao Q, Wen J G, You D Q and Hueni A. 2019. Advances in quantitative remote sensing product validation: overview and current status. Earth-Science Reviews, 196: 102875
  48. 48.
    Yan G J, Zhao T J, Mu X H, Wen J G, Pang Y, Jia L, Zhang Y G, Chen D Q, Yao C B, Cao Z Y, Lei Y H, Ji D B, Chen L F, Liu Q H, Lyu L Q, Chen J M and Shi J C. 2021. Comprehensive remote sensing experiment of carbon cycle, water cycle and energy balance in Luan River Basin. National Remote Sensing Bulletin, 25(4): 856-870
  49. 49.
    Zhang R H. 2009. Quantitative Thermal Infrared Remote Sensing Model and Ground Experiment Basis. Beijing: Science Press
  50. 50.
    Zhang Y, Liu S M, Song L S, Li X, Jia Z Z, Xu T R, Xu Z W, Ma Y F, Zhou J, Yang X F, He X L, Yao Y J and Hu G C. 2022. Integrated validation of coarse remotely sensed evapotranspiration products over heterogeneous land surfaces. Remote Sensing, 14(14): 3467
  51. 51.
    Zhang Y, Shi Y L, Choi S, Ni X L and Myneni R B. 2019. Mapping maximum tree height of the Great Khingan Mountain, Inner Mongolia using the Allometric scaling and resource limitations model. Forests, 10(5): 380
  52. 52.
    Zhao T J, Shi J C, Xu H X, Sun Y L, Chen D Q, Cui Q, Jia L, Huang S, Niu S D, Li X W, Yan G J, Chen L F, Liu Q H, Zhao K, Zheng X M, Zhao L M, Zheng C L, Ji D B, Xiong C, Wang T X, Li R, Pan J M, Wen J G, Mu X H, Yu C, Zheng Y M, Jiang L M, Chai L N, Lu H, Yao P P, Ma J W, Lyu H S, Wu J J, Zhao W, Yang N, Guo P, Li Y X, Hu L, Geng D Y, Zhang Z Q, Hu J F and Du A P. 2021. Comprehensive remote sensing experiment of water cycle and energy balance in the Shandian river basin. National Remote Sensing Bulletin, 25(4): 871-887
  53. 53.
    Zhong S Y, Xiao Q, Wen J G, Zheng X M, Ma M G, Qu Y H, Zheng K, Chi T H, Tang Y, You D Q, Hao D L, Cheng J, He M, Jiang T, Jin R, Yao X J and Zhao L J. 2020. Design and realization of ground object background spectral library for surveying and mapping. Journal of Remote Sensing, 24(6): 701-716

Leer el texto completo

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website