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Technology system for product validation and algorithm test of GF common products and an application example

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academic 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 Jianguang12,  
  • role： Corresponding author通信作者
  • Affiliation：

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

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

  • Email：xiaoqing@aircas.ac.cn
  • Introduction：肖青， 研究方向为定量遥感机理和模型。E-mail： xiaoqing@aircas.ac.cn
XIAO Qing12*,  
  • Affiliation：

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

ZHONG Shouyi1,  
  • Affiliation：

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

TANG Yong1,  
  • Affiliation：

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

CHEN Xi1,  
  • Affiliation：

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

WEI Qiufang1,  
  • Affiliation：

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

WU Xiaodan3,  
  • Affiliation：

    College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

LIN Xingwen4,  
  • Affiliation：

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

OUYANG Xiaoying1,  
  • Affiliation：

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

YOU Dongqin1,  
  • Affiliation：

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

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

LIU Qinhuo12

Resümee

Given the development of China’s high-resolution earth observation system (referred to as GF), common products, standard products, and specific products play an important role in remote sensing applications of GF data. In particular, the common products promote remote sensing applications as the bridge between the GF standard products and specific products. However, GF common products are derived by retrieval algorithms. Inevitable errors bring great uncertainty to the followed-up remote sensing applications. Thus, the retrieval algorithms of GF common products should be tested. Moreover, the products should be validated to ensure the quality of GF common products.This study expounds on the relationship between the algorithm test and product validation and that between the test and validation technology system. Algorithm test and product validation are at the two ends of a common product-generating process. A complete algorithm test process of common products mainly includes the establishment of the algorithm test index system, the construction of the index calculation method, the preparation of the test dataset, the algorithm running and index calculation, and finally, the writing of the algorithm test report. All the generated common products should be validated using the referenced truth data through suitable methods. Thus, a service platform of GF common product validation and algorithm test is implemented to achieve these two functions.The test index system of the GF common product algorithm is constructed with four primary indexes and 10 secondary indexes through literature research, expert consultation, and questionnaire investigation. For example, the land surface albedo retrieval algorithm is tested to show the feasibility of the algorithm test in the service platform. The results show that it can support the validation and algorithm test of Gaofen common products in China.Algorithm test and the product validation technology system and its service platform are important for quality control in the generating of GF common products. The validation and algorithm test of GF common products is a systematic project that requires the cooperation of multiple communities to collect the sample data and reference data through continuous field observation. This field observation is an important foundation of validation and algorithm tests for common products.

Schlüsselwort

remote sensing;GF satellite;common product;algorithm test;product validation;land surface albedo

References

  1. 1.
    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. 2018b. A web-based land surface remote sensing products validation system (LAPVAS): application to albedo product. International Journal of Digital Earth, 11(3): 308-328
  2. 2.
    Morisette J T, Baret F, Privette J L, Myneni R B, Nickeson J E, Garrigues S, Shabanov N V, Weiss M, Fernandes R A, Leblanc S G, Kalacska M, Sanchez-Azofeifa G A, Chubey M, Rivard B, Stenberg P, Rautiainen M, Voipio P, Manninen T, Pilant A N, Lewis T E, Iiames J S, Colombo R, Meroni M, Busetto L, Cohen W B, Turner D P, Warner E D, Petersen G W, Seufert G and Cook R. 2006. Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup. IEEE Transactions on Geoscience and Remote Sensing, 44(7): 1804-1817
  3. 3.
    Saaty T L. 1978. Modeling unstructured decision problems-THE theory of analytical hierarchies. Mathematics and Computers in Simulation, 20(3): 147-158
  4. 4.
    State Administration for Market Regulation and 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
  5. 5.
    State Administration for Market Regulation and 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
  6. 6.
    State Administration for Market Regulation and Standardization Administration of the People’s Republic of China. 2021. GB/T 40038-2021 Validation of vegetation index remote sensing products. Beijing: Standards Press of China
  7. 7.
    Tong X D. 2016. Development of China high-resolution earth observation system. Journal of Remote Sensing, 20(5): 775-780
  8. 8.
    Wu X D, Wen J G, Xiao Q, Li X, Liu Q, Tang Y, Dou B C, Peng J J, You D Q and Li X W. 2015. Advances in validation methods for remote sensing products of land surface parameters. Journal of Remote Sensing, 19(1): 75-92
  9. 9.
    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
  10. 10.
    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
  11. 11.
    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, 4: 8193-8207
  12. 12.
    Wu X D, Xiao Q, Wen J G, Liu Q, Peng J J and Li X W. 2014. Advances in uncertainty analysis for the validation of remote sensing products: take leaf area index for example. Journal of Remote Sensing, 18(5): 1011-1023
  13. 13.
    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
  14. 14.
    You D Q, Wen J G, Xiao Q, Liu Q, Liu Q H, Tang Y, Dou B C and Peng J J. 2015. Development of a high resolution BRDF/albedo product by fusing airborne CASI reflectance with MODIS daily reflectance in the oasis area of the Heihe river basin, China. Remote Sensing, 7(6): 6784-6807
  15. 15.
    Zhang R H, Tian J, Li Z L, Su H B and Chen S H. 2010. Principles and methods for the validation of quantitative remote sensing products. Science China Earth Sciences, 53(5): 741-751
  16. 16.
    2018 China satellite application report of high-resolution earth observation system(common products). 2018. State administration of science, technology and industry for national defence (2018中国高分卫星应用报告(共性产品卷). 2018. 国家国防科技工业局)

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