سابِق|تال

Comparison of global albedo products of MODIS V006 and V005 based on FLUXNET

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：fengzm@radi.ac.cn
  • Introduction：冯智明(1992—　)，男，硕士研究生，研究方向为遥感数据产品真实性检验。E-mail：fengzm@radi.ac.cn
Zhiming FENG12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

  • Email：wenjg@radi.ac.cn
  • Introduction：闻建光(1978—　)，男，副研究员，研究方向为遥感辐射传输建模与试验遥感。E-mail：wenjg@radi.ac.cn
Jianguang WEN1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Qing XIAO1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

Dongqin YOU1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Xingwen LIN12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

Xiaodan WU12

ملخص

Land surface albedos represent an important parameter in the Earth’s energy balance, and they play a crucial role in the global change and climate systems. Numerous global or regional land surface albedo products with various spatial resolutions and temporal frequencies have been released. Thus, the quality analysis of albedo products has become increasingly important. On the basis of the algorithm of a version 5 albedo product (MODIS V005), a new daily product version (MODIS V006) with a high temporal resolution is generated with MODLAND. The new albedo product requires urgent validation, and its accuracy should be known before extensive use. On the basis of sites with adequate spatial representativeness in the FLUXNET network, direct comparisons between different versions of albedo products and in situ albedos were conducted. To investigate the accuracy under various land cover type conditions of the two versions of albedo products, we divided the ground measurements into six classes and calculated several evaluation indicators. Two different versions of products were also compared using a cross-validation method under the prior knowledge that V005 has been extensively estimated and that the method achieves good performance in various validation works. At the same time, the Quality Control (QC) flag was investigated to analyze the stability of the new albedo products. The direct comparison results indicate that two versions of products show good consistency against the in situ albedos. However, V006 performs better than V005 during the same experimental time. For the accuracy under different land cover types, all the evaluation indicators briefly show that V006 products achieve a better match with in situalbedos than V005 products. As the V006 has a high temporal resolution, accurately capturing the rapid changes of land surface albedos is relatively easy, especially during snow-covered days. The comparison result obtained through the cross-validation method indicates that except for a few slightly high values, the V006 product effectively matches the V005 product. Although the percentage of QC flag indicating the good quality of the V006 product is lower than that of the V005 product, data show the stable performance of both products in the span of three years. The MODIS V006 product has a shorter temporal resolution and higher accuracy than the V005 product. The trends of the two albedo products over the time series highlight their good consistency. However, V006 performs better than MODIS V005 during snow-covered times. This finding is expected to play a significant role in many other research fields.

مفهوم

remote sensing;validation of albedo;MODIS;FLUXNET;quality control flag

References

  1. 1.
    Bacour C and Bréon F M. 2005. Variability of biome reflectance directional signatures as seen by POLDER. Remote Sensing of Environment, 98(1): 80–95
  2. 2.
    Cescatti A, Marcolla B, Vannan S K S, Pan J Y, Román M O, Yang X Y, Ciais P, Cook R B, Law B E, Matteucci G, Migliavacca M, Moors E, Richardson A D, Seufert G and Schaaf C B. 2012. Intercomparison of MODIS albedo retrievals and in situ measurements across the global FLUXNET network. Remote Sensing of Environment, 121: 323–334
  3. 3.
    Dickinson R E. 1983. Land surface processes and climate—Surface albedos and energy balance. Advances in Geophysics, 25: 305–353
  4. 4.
    Jiang X G, Li Z L, Xi X H, Li X B and Li Z Y. 2008. Basic frame of remote sensing validation system. Arid Land Geography, 31(4): 567–571 (
  5. 5.
    Jiao Z T, Wang J D, Xie L O, Zhang H, Yan G J, He L M and Li X W. 2005. Initial Validation of MODIS albedo product by using field measurements and airborne multiangular remote sensing observations. Journal of Remote Sensing, 9(1): 64–72 (
  6. 6.
    Justice C, Belward A, Morisette J, Lewis P, Privette J and Baret F. 2000. Developments in the ‘validation’ of satellite sensor products for the study of the land surface. International Journal of Remote Sensing, 21(17): 3383–3390
  7. 7.
    Leroy M, Deuzé J L, Bréon F M, Hautecoeur O, Herman M, Buriez J C, Tanré D, Bouffiès S, Chazette P and Roujean J L. 1997. Retrieval of atmospheric properties and surface bidirectional reflectances over land from POLDER/ADEOS. Journal of Geophysical Research: Atmospheres, 102(D14): 17023–17037
  8. 8.
    Lewis P, Brockmann C, Danne O, Fischer J, Guanter L, Heckel A, Krueger O, López G, Muller J and North P. 2011. GlobAlbedo algorithm theoretical basis document: version 3.0.
  9. 9.
    Lewis P, Guanter L, Saldana G L, Muller J P, Watson G, Shane N, Kennedy T, Fisher J, Domenech C, Preusker R, North P, Heckel A, Danne O, Krämer U, Zühlke M, Fomferra N, Brockmann C and Schaaf C. 2012. The ESA globAlbedo project: algorithm//2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany: IEEE [DOI: 10.1109/IGARSS.2012.6352306]
  10. 10.
    Liang S L. 2009. Quantitative remote sensing of land surfaces. Fan W J, trans. Beijing: Science Press.
  11. 11.
    Liang S L, Zhao X, Liu S H, Yuan W P, Cheng X, Xiao Z Q, Zhang X T, Liu Q, Cheng J, Tang H R, Qu Y H, Bo Y C, Qu Y, Ren H Z, Yu K and Townshend J. 2013. A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth, 6(S1): 5–33
  12. 12.
    Liu Q, Wang L Z, Qu Y, Liu N F, Liu S H, Tang H R and Liang S L. 2013. Preliminary evaluation of the long-term GLASS albedo product. International Journal of Digital Earth, 6(S1): 69–95
  13. 13.
    Lucht W, Schaaf C B and Strahler A H. 2000. An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Transactions on Geoscience and Remote Sensing, 38(2): 977–998
  14. 14.
    Privette J L, Eck T F and Deering D W. 1997. Estimating spectral albedo and nadir reflectance through inversion of simple BRDF models with AVHRR/MODIS-like data. Journal of Geophysical Research: Atmospheres, 102(D24): 29529–29542
  15. 15.
    Roman M O, Gatebe C K, Shuai Y M, Wang Z S, Gao F, Masek J G, He T, Liang S L and Schaaf C B. 2013. Use of in situ and airborne multiangle data to assess MODIS-and landsat-based estimates of directional reflectance and albedo. IEEE Transactions on Geoscience and Remote Sensing, 51(3): 1393–1404
  16. 16.
    Román M O, Schaaf C B, Woodcock C E, Strahler A H, Yang X Y, Braswell R H, Curtis P S, Davis K J, Dragoni D, Goulden M L, Gu L H, Hollinger D Y, Kolb T E, Meyers T P, Munger J W, Privette J L and Richardson A D. 2009. The MODIS (Collection V005) BRDF/albedo product: assessment of spatial representativeness over forested landscapes. Remote Sensing of Environment, 113(11): 2476–2498
  17. 17.
    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: Atmosphere, 97(D18): 20455–20468
  18. 18.
    Schaaf C B, Gao F, Strahler A H, Lucht W, Li X W, Tsang T, Strugnell N C, Zhang X Y, Jin Y F,Muller J P, Lewis P, Barnsley M, Hobson P, Disney M, Roberts G, Dunderdale M, Doll C, d’Entremont R P, Hu B X, Liang S L, Privette J L and Roy D. 2002. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83(1/2): 135–148
  19. 19.
    Wang K C, Liang S L, Schaaf C L and Strahler A H. 2010. Evaluation of Moderate Resolution Imaging Spectroradiometer land surface visible and shortwave albedo products at FLUXNET sites. Journal of Geophysical Research: Atmosphere, 115(D17): D17107
  20. 20.
    Wang Z S, Schaaf C B, Strahler A H, Chopping M J, Román M O, Shuai Y M, Woodcock C E, Hollinger D Y and Fitzjarrald D R. 2014. Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods. Remote Sensing of Environment, 140: 60–77
  21. 21.
    Wanner W, Li X and Strahler A H. 1995. On the derivation of kernels for kernel‐driven models of bidirectional reflectance. Journal of Geophysical Research: Atmospheres, 100(D10): 21077–21089
  22. 22.
    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: Atmospheres, 102(D14): 17143–17161
  23. 23.
    Wen J G, Liu Q, Liu Q H, Xiao Q and Li X W. 2015. Land surface bidirectional reflectance characteristics of remote sensing modeling and albedo inversion. Beijing: Science Press.
  24. 24.
    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 (
  25. 25.
    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 (
  26. 26.
    Zhang R H, Tian J, Li Z L, Su H B, Chen S H and Tang X Z. 2010. Principles and methods for the validation of quantitative remote sensing products. Science China Earth Sciences, 53(5): 741–751

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