Précédent|Prochain

BRDF feature observation method and modeling of desert site based on UAV platform

  • role： First author第一作者
  • Affiliation：

    Henan Polytechnic University, School of Surveying and Land Information Engineering, Jiaozuo 454003, China

  • Email：cometcn2015@outlook.com
  • Introduction：陶炳成，1995年生，男，硕士研究生，研究方向为卫星遥感定标理论及技术方法。E-mail： cometcn2015@outlook.com
TAO Bingcheng1,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

  • Email：huxq@cma.cn
  • Introduction：胡秀清，1973年生，男，研究员，研究方向为卫星遥感定标理论及技术方法。E-mail： huxq@cma.cn
HU Xiuqing2*,  
  • Affiliation：

    Henan Polytechnic University, School of Surveying and Land Information Engineering, Jiaozuo 454003, China

YANG Leiku1,  
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

ZHANG Lu2,  
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

CHEN Lin2,  
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

XU Na2,  
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

WANG Ling2,  
  • Affiliation：

    Beijing AZUP International, Beijing 100081, China

WU Ruiqiang3,  
  • Affiliation：

    Beijing AZUP International, Beijing 100081, China

ZHANG Dufeng3,  
  • Affiliation：

    National Satellite Meteorology Center, Beijing 100081, China

ZHANG Peng2

résumé

The Bidirectional Reflectance Distribution Function (BRDF) is not only a key geophysical parameter for land surface remote sensing, but also an important parameter for radiation correction of the spaceborne optical remote sensing instruments. Observation equipment used for traditional field object multiangle measurement is generally relatively complex and heavy, and the transportation and assembly processes are cumbersome. Observing targets is easy restricted by terrain and traffic, and efficient and rapid field measurements are difficult to perform. In recent years, UAVs can be used as new observation platforms in current remote sensing experiments due to their advantages, such as simple operation of equipment, flexible transportation, and observation methods.A ground surface BRDF measurement device, observation scheme, and data processing flow based on a UAV platform are innovatively designed. Using a combination of a multirotor low-altitude drone and a gimbal, equipped with a portable ground object spectrometer and a follow-up camera, can provide high-precision positioning and angle control for multiangle observation of ground targets, thereby achieving multiazimuth and sky for fixed targets. This design scheme and observation process are adopted to carry out multiple multiangle spectral observation experiments of stable and uniform desert targets in the Dunhuang radiation correction field, and the experimental observation data are used to estimate the site BRDF model parameters based on the Ross-Li nuclear driving model, and MODIS. Land surface BRDF product (MCD43C1) and reflectivity product (MOD/MYD09) are compared and verified.Field experiments have verified the reliability of this new equipment. At the same time, the analysis results of observation data show that the BRDF parameters of Dunhuang surface measured by the proposed device have good consistency with MODIS remote sensing products, and the relative deviation of each band is within 5%.This study shows that the BRDF observation system based on multirotor drones provides a new and flexible observation method for the reflection characteristics of ground objects in the direction of the target. It can greatly reduce the investment of manpower and material resources while ensuring the accuracy of observation, which is worthy of widespread promotion and application.

mots-clés

UAV;desert;bidirectional reflectance distribution function;directional reflectance;calibration field

References

  1. 1.
    Cosnefroy H, Briottet X, Leroy M, Lecomte P and Santer R. 1997. A field experiment in Saharan Algeria for the calibration of optical satellite sensors. International Journal of Remote Sensing, 18(16): 3337-3359
  2. 2.
    Doctor K Z, Bachmann C M, Gray D J, Montes M J and Fusina R A. 2015. Wavelength dependence of the bidirectional reflectance distribution function (BRDF) of beach sands. Applied Optics, 54(31): F243-F255
  3. 3.
    Grenzdörffer G J and Niemeyer F. 2012. UAV based BRDF-measurements of agricultural surfaces with PFIFFikus. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 3822(1): 229-234
  4. 4.
    Gu X F. 2013. Principles and Methods of Radiation Calibration for Aerospace Optical Remote Sensor. Beijing: Science Press
  5. 5.
    Hakala T, Suomalainen J and Peltoniemi J. 2010. Acquisition of bidirectional reflectance factor dataset using a micro unmanned aerial vehicle and a consumer camera. Remote Sensing, 2(3): 819-832
  6. 6.
    Hu X Q, Liu J J, Sun L, Rong Z G, Li Y, Zhang Y, Zheng Z J, Wu R H, Zhang L J and Gu X F. 2010. Characterization of CRCS Dunhuang test site and vicarious calibration utilization for Fengyun (FY) series sensors. Canadian Journal of Remote Sensing, 36(5): 566-582
  7. 7.
    Liang S L, Li X W and Wang J D. 2013. Quantitative Remote Sensing: Ideas and Algorithms. Beijing: Science Press
  8. 8.
    Pan Z Q, Zhang H P, Min X J and Xu Z P. 2020. Vicarious calibration correction of large FOV sensor using BRDF model based on UAV angular spectrum measurements. Journal of Applied Remote Sensing, 14(2): 027501
  9. 9.
    Roujean J L, Leroy M and Deschamps P Y. 1992. A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data. Journal of Geophysical Research, 97(D18): 20455-20468
  10. 10.
    Song F N. 2006. Method of Acquiring BRDF of Field Objects. Beijing: China Agricultural University
  11. 11.
    Sun L, Guo M H, Xu N, Zhang L J, Liu J J, Hu X Q, Li Y, Rong Z G and Zhao Z H. 2012. On-orbit response variation analysis of FY-3 MERSI reflective solar bands based on Dunhuang site calibration. Spectroscopy and Spectral Analysis, 32(7): 1869-1877
  12. 12.
    Wanner W, Strahler A H, Hu B, Lewis P, Muller J P, Li X, Schaaf C L B and Barnsley M J. 1997. Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: theory and algorithm. Journal of Geophysical Research, 102(D14): 17143-17161
  13. 13.
    Wang L, Hu X Q and Chen L. 2017. Wide dynamic nonlinear radiometric calibration of optical satellite sensors using multiple stable earth targets. Journal of Remote Sensing, 21(6): 892-906
  14. 14.
    Wierzbicki D, Kedzierski M, Fryskowska A and Jasinski J. 2018. Quality assessment of the bidirectional reflectance distribution function for NIR imagery sequences from UAV. Remote Sensing, 10(9): 1348
  15. 15.
    Wu R H, Zhang P, Yang Z D, Hu X Q, Ding L and Chen L. 2016. Monitor the radiance calibration of the remote sensing instrument by using the reflectec lunar irradiance. Journal of Remote Sensing, 20(02): 278-289
  16. 16.
    Yu T Q, Wei W, Zhang Y N, Zhang Y J, Li X, Zheng X B and Sun L. 2018. Analysis of the BRDF characteristics of Dunhuang radiometric calibration site in the spring. Acta Photonica Sinica, 47(6): 0612004
  17. 17.
    Yu T Q. 2018. Control Software Design of BRDF Measurement System and Processing and Analyzing Measured Data of Dunhuang Test Site. Hefei: University of Science and Technology of China
  18. 18.
    Zhao C Y, Wei W, Zhang Y N, Zhang M, Li X and Zheng X B. 2019. Long time series radiometric calibration of Suomi-NPP VIIRS based on surface hyperspectral BRDF model. Acta Optica Sinica, 39(8): 0828001

Lire l'article complet

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