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Automated Retrieval of Snow/Ice Surface Broadband Albedo in Beas River Basin, India Using Landsat-8 Satellite Images and Validation with Wireless Sensor Network Data

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Abstract

This paper proposed an algorithm for automated retrieval of snow/ice surface albedo using Landsat-8 satellite images and validation with wireless senor network data in Beas River basin, India. Cloud-free Landsat-8 images of winter season 2016–2017 have been used to estimate snow/ice broadband albedo. Albedo maps generated using satellite images have been compared and validated with in situ recorded albedo values at wireless sensor network stations. Root-mean-square error of 0.053, R-square (R2) of 0.96, bias of − 0.034 and mean absolute percentage error of ~ 3.5% have been observed. Existing global albedo model for Landsat ETM+ was also used to estimate albedo in the study area using Landsat-8 images. Algorithm proposed in this paper for Landsat-8 has shown comparatively better results. Simultaneously, albedo values for snow/ice class have also been estimated using MODIS images. High correlation has been observed between the albedo values estimated from Landsat-8 and MODIS images. Proposed algorithm appears to be the first to estimate broadband albedo of snow/ice class from narrowband reflectances using Landsat-8 images for Indian Himalaya.

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References

  • Allen, R. G., Tasumi, M., & Trezza, R. (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC): Model. Journal of Irrigation and Drainage Engineering, 133, 380–394.

    Article  Google Scholar 

  • Allen, R. G., Trezza, R., & Tasumi, M. (2002). Surface energy balance algorithms for land. Advance training and user’s manual, version 1.0. Kimberly: The Idaho Department of Water Resources.

    Google Scholar 

  • Anderson, G. P., Pukall, B., Allred, C. L., Jeong, L. S., Hoke, M., Chetwynd, J. H., & Matthew, M. W. (1999). FLAASH and MODTRAN4: State-of-the-art atmospheric correction for hyperspectral data. In IEEE aerospace conference. Proceedings (Cat. No.99TH8403). https://doi.org/10.1109/AERO.1999.792088.

  • Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., & Holslag, A. A. M. A. (1998). Remote sensing surface energy balance algorithm for land (SEBAL): Formulation. Journal of Hydrology, 212, 198–212.

    Article  Google Scholar 

  • Bolch, T., Kulkarni, A., Kääb, A., Huggel, C., Paul, F., Cogley, J. G., et al. (2012). The state and fate of Himalayan glaciers. Science, 336, 310–314.

    Article  Google Scholar 

  • Chander, G., & Markhan, B. (2003). Revised Landsat 5-TM radiometric calibration procedures and post calibration dynamic ranges. IEEE Transactions on Geosciences and Remote Sensing, 41, 2674–2677.

    Article  Google Scholar 

  • Civco, D. L. (1989). Topographic normalization of Landsat Thematic Mapper digital imagery. Photogrammetric Engineering and Remote Sensing, 55, 1303–1309.

    Google Scholar 

  • Colby, J. D. (1991). Topographic normalization in rugged terrain. Photogrammetric Engineering and Remote Sensing, 57, 531–537.

    Google Scholar 

  • Cooley, T., Anderson, G. P., Felde, G. W., Hoke, M. L., Ratkowski, A. J., Chetwynd, J. H., Gardner, J. A., Adler-Golden, S. M., Matthew, M. W., Berk, A., Bernstein, L. S., Acharya, P. K., Miller, D., & Lewis, P. (2002). FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation. In 2002 IEEE international geoscience and remote sensing symposium, 2002. IGARSS’02. https://doi.org/10.1109/igarss.2002.1026134.

  • EXELIS Inc. (2013). ENVI ® 5.1 fast line-of-sight atmospheric analysis of hypercubes (FLAASH). Boulder, CO, USA: EXELIS Inc.

    Google Scholar 

  • Flanner, M. G., Zender, C. S., Randerson, J. T., & Rasch, P. J. (2007). Present-day climate forcing and response from black carbon in snow. Journal of Geophysical Research Atmospheres, 112, D11202.

    Article  Google Scholar 

  • Gusain, H. S., Mishra, V. D., & Arora, M. K. (2014). Estimation of net shortwave radiation flux of western Himalayan snow cover during clear sky days using remote sensing and meteorological data. Remote Sensing Letters, 5, 83–92.

    Article  Google Scholar 

  • Gusain, H. S., Singh, A., Ganju, A., & Singh, D. (2004). Characteristics of the seasonal snow cover of Pir Panjal and Great Himalayan ranges in Indian Himalaya. In Proceedings international symposium on snow monitoring and avalanches (ISSMA)-2004, Manali, India (pp. 97–102).

  • Hall, D. K., Riggs, G. A., & Salomonson, V. V. (1995). Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer (MODIS) data. Remote Sensing of Environment, 54, 127–140.

    Article  Google Scholar 

  • He, T., Liang, S., & Song, D. X. (2014). Analysis of global land surface albedo climatology and spatial–temporal variation during 1981–2010 from multiple satellite products. Journal of Geophysical Research. https://doi.org/10.1002/2014JD021667.

    Google Scholar 

  • He, T., Liang, S., Wang, D., Cao, Y., Gao, F., Yu, Y., et al. (2018). Evaluating land surface albedo estimation from Landsat MSS, TM, ETM+, and OLI data based on the unified direct estimation approach. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2017.10.031.

    Google Scholar 

  • Key, J., Wang, X., Stroeve, J., & Fowler, C. (2001). Estimating the cloudy sky albedo of sea ice and snow from space. Journal of Geophysical Research, 106, 12489–12497.

    Article  Google Scholar 

  • Ku, X., & Hall, A. (2007). What controls the strength of snow-albedo feedback? Journal of Climate, 20, 3971–3981.

    Article  Google Scholar 

  • Kumar, V., Singh, P., & Singh, V. (2007). Snow and glacier melt contribution in the Beas River at Pandoh Dam, Himachal Pradesh, India. Hydrological Sciences Journal. https://doi.org/10.1623/hysj.52.2.376.

    Google Scholar 

  • Li, Z., & Garand, L. (1994). Estimation of surface albedo from space: A parameterization for global application. Journal of Geophysical Research. https://doi.org/10.1029/94JD00225.

    Google Scholar 

  • Liang, S. (2000). Narrowband to broadband conversions of land surface albedo I: Algorithms. Remote Sensing of Environment, 76, 213–238.

    Article  Google Scholar 

  • Liang, S., Shuey, C. J., Russ, A. L., Fang, H., Chen, M., Walthall, C. L., et al. (2002). Narrowband to broadband conversions of land surface albedo: II. Validation. Remote Sensing of Environment, 84, 25–41.

    Article  Google Scholar 

  • Liang, S., Strahler, A., & Walthall, C. (1999). Retrieval of land surface albedo from satellite observations: A simulation study. Journal of Applied Meteorology, 38, 712–725.

    Article  Google Scholar 

  • Liang, S. L., Zhao, X., Liu, S., Yuan, W., Cheng, X., Xiao, Z., et al. (2013). A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth. https://doi.org/10.1080/17538947.2013.805262.

    Google Scholar 

  • Martonchik, J. V., Diner, D. J., Pinty, B., Verstraete, M. M., Myneni, R. B., Knyazikhin, Y., et al. (1998). Determination of land and ocean reflective, radiative, and biophysical properties using multiangle imaging. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/36.701077.

    Google Scholar 

  • Mishra, V. D., Gusain, H. S., & Arora, M. K. (2012). Algorithm to derive narrow band to broad band albedo for snow using AWiFS and MODIS imagery of western Himalaya: Validation. International Journal of Remote Sensing Applications, 2, 52–62.

    Google Scholar 

  • Mishra, V. D., Sharma, J. K., Singh, K. K., Thakur, N. K., & Kumar, M. (2009). Assessment of different topographic corrections in AWiFS satellite imagery of Himalaya terrain. Journal of Earth System Science. https://doi.org/10.1007/s12040-009-0002-0.

    Google Scholar 

  • Muller, J. P., López, G., Watson, G., Shane, N., Kennedy, T., Yuen, P., Lewis, P., Fischer, J., Guanter, L., Domench, C., Preusker, R., North, P., Heckel, A., Danne, O., Kramer, U., Zuhlke, M., Brockmann, C., & Pinnock, S. (2012). The ESA GlobAlbedo project for mapping the Earth’s land surface albedo for 15 years from European sensors. In IEEE geoscience and remote sensing symposium (IGARSS). Munich: IEEE.

  • Negi, H. S., Datt, P., Thakur, N. K., Ganju, A., Bhatia, V. K., & Kumar, V. (2016). Observed spatio-temporal changes of winter snow albedo over the north-west Himalaya. International Journal of Climatology. https://doi.org/10.1002/joc.4846.

    Google Scholar 

  • Negi, H. S., Jassar, H. S., Saravana, G., Thakur, N. K., Snehmani, & Ganju, A. (2013). Snow-cover characteristics using Hyperion data for the Himalayan region. International Journal of Remote Sensing. https://doi.org/10.1080/01431161.2012.742213.

    Google Scholar 

  • Negi, H. S., & Kokhanovsky, A. (2011). Retrieval of snow grain size and albedo of western Himalayan snow cover using satellite data. The Cryosphere, 5, 831–847.

    Article  Google Scholar 

  • Nichol, J., Hang, L. K., & Sing, W. M. (2006). Empirical correction of low Sun angle images in steeply sloping terrain: A slope-matching technique. International Journal of Remote Sensing. https://doi.org/10.1080/02781070500293414.

    Google Scholar 

  • Pinty, B., Roveda, F., Verstraete, M. M., Gobron, N., Govaerts, Y., Martonchik, J. V., et al. (2000). Surface albedo retrieval from Meteosat 1. Theory. Journal of Geophysical Research Atmospheres. https://doi.org/10.1029/2000JD900113.

    Google Scholar 

  • Popp, C., Wang, P., Brunner, D., Stammes, P., Zhou, Y., & Grzegorski, M. (2011). MERIS albedo climatology for FRESCO+ O2 A-band cloud retrieval. Atmospheric Measurement Techniques. https://doi.org/10.5194/amt-4-463-2011.

    Google Scholar 

  • Riihelä, A., Manninen, T., Laine, V., Andersson, K., & Kaspar, F. (2013). CLARA-SAL: A global 28 yr time series of Earth’s black-sky surface albedo. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-13-3743-2013.

    Google Scholar 

  • Roman, M. O., Gatebe, C. K., Shuai, Y., Wang, Z., Gao, F., Masek, J. G., et al. (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. https://doi.org/10.1109/TGRS.2013.2243457.

    Google Scholar 

  • Roman, M. O., Schaaf, C. B., Lewis, P., Gao, F., Anderson, G. P., Privette, J. L., et al. (2010). Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2009.11.014.

    Google Scholar 

  • Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., et al. (2002). First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment. https://doi.org/10.1016/S0034-4257(02)00091-3.

    Google Scholar 

  • Schramm, J. L., Holland, M. M., Curry, J. A., & Ebert, E. E. (1997). Modeling the thermodynamics of a sea ice thickness distribution: 1. Sensitivity to ice thickness resolution. Journal of Geophysical Research, 102, 23079–23092.

    Article  Google Scholar 

  • Shuai, Y., Masek, J. G., Gao, F., & Schaaf, C. B. (2011). An algorithm for the retrieval of 30-m snow-free albedo from Landsat surface reflectance and MODIS BRDF. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2011.04.019.

    Google Scholar 

  • Shuai, Y., Masek, J. G., Gao, F., Schaaf, C. B., & He, T. (2014). An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2014.07.009.

    Google Scholar 

  • Silva, B. B., Braga, A. C., & Braga, C. C. (2016). Procedures for calculation of the albedo with OLI-Landsat 8 images: Application to the Brazilian semi-arid. Revista Brasileira de Engenharia Agrícola e Ambiental, 20, 3–8.

    Article  Google Scholar 

  • Song, J., & Gao, W. (1999). An improved method to derive surface albedo from narrowband AVHRR satellite data: Narrowband to broadband conversion. Journal of Applied Meteorology, 38, 239–249.

    Article  Google Scholar 

  • Şorman, A. Ü., Akyürek, Z., Şensoy, A., Şorman, A. A., & Tekeli, A. E. (2007). Commentary on comparison of MODIS snow cover and albedo products with ground observations over the mountainous terrain of Turkey, Hydrol. Earth System Science, 11, 1353–1360. https://doi.org/10.5194/hess-11-1353-2007.

    Article  Google Scholar 

  • Stroeve, J. (2001). Assessment of Greenland albedo variability from the advanced very high resolution radiometer Polar Pathfinder data set. Journal of Geophysical Research, 106, 33989–34006.

    Article  Google Scholar 

  • Stroeve, J., & Nolin, A. (2002). Comparison of MODIS and MISR derived surface albedo with in situ measurements in Greenland. EARSeL ePROC, 2, 88–96.

    Google Scholar 

  • Tasumi, M., Allen, R. G., & Trezza, R. (2008). At-surface reflectance and albedo from satellite for operational calculation of land surface balance. Journal of Hydrologic Engineering, 13, 51–63.

    Article  Google Scholar 

  • Wang, D., Liang, S., He, T., & Yu, Y. (2013). Direct estimation of land surface albedo from VIIRS data: Algorithm improvement and preliminary validation. Journal of Geophysical Research Atmospheres. https://doi.org/10.1002/2013JD020417.

    Google Scholar 

  • Wiscombe, W. J., & Warren, S. G. (1980). A model for the spectral albedo of snow, I: Pure snow. Journal of the Atmospheric Sciences, 37, 2712–2733.

    Article  Google Scholar 

  • Woodcock, C. E., Allen, R., Anderson, M., Belward, A., Bindschadler, R., Cohen, W., Gao, F., Goward, S. N., Helder, D., Helmer, E., Nemani, R., Oreopoulos, L., Schott, J., Thenkabail, P. S., Vermote, E. F., Vogelmann, J., Wulder, M. A., & Wynne, R. (2008). Free access to Landsat imagery. Science, 320, 1011. https://doi.org/10.1126/science.320.5879.1011a.

    Article  Google Scholar 

  • Zhong, Q., & Li, Y. H. (1988). Satellite observation of surface albedo over the Qinghai-Xizang plateau region. Advances in Atmospheric Science, 5, 57–65.

    Article  Google Scholar 

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Acknowledgements

The authors are grateful to Shri. Naresh Kumar, Director, Snow and Avalanche Study Establishment (SASE), Chandigarh, for providing facilities to carry out this work. The authors would like to acknowledge SASE staff for collecting ground data. We are thankful to Shri R. K. Das for providing WSN data for validation. Authors are also thankful to http://earthexplorer.usgs.gov and http://ladsweb.modaps.eosdis.nasa.gov for providing Landsat-8, Landsat-7 and MODIS data, respectively.

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Correspondence to Dhiraj Kumar Singh.

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Singh, D.K., Gusain, H.S., Mishra, V.D. et al. Automated Retrieval of Snow/Ice Surface Broadband Albedo in Beas River Basin, India Using Landsat-8 Satellite Images and Validation with Wireless Sensor Network Data. J Indian Soc Remote Sens 47, 33–44 (2019). https://doi.org/10.1007/s12524-018-0863-2

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