Open Access
Issue |
E3S Web Conf.
Volume 350, 2022
International Conference on Environment, Renewable Energy and Green Chemical Engineering (EREGCE 2022)
|
|
---|---|---|
Article Number | 01007 | |
Number of page(s) | 6 | |
Section | Green Chemical Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202235001007 | |
Published online | 09 May 2022 |
- J.T. Kiehl, J.J. Hack, G.B. Bonan, et al. Description of the NCAR Community Climate Model (CCM3). National Center for Atmospheric Research Publishing, The Boulder (1996). [Google Scholar]
- B. Pinty, T. Lavergne, T. Kaminski, et al. Partitioning the solar radiant fluxes in forest canopies in the presence of snow. Journal of Geophysical Research, 113 D04104 (2008) [CrossRef] [Google Scholar]
- D.S. Kimes and P.J. Sellers, Inferring Hemispherical Reflectance of the Earth’s Surface for Global Energy Budgets from Remotely Sensed Nadir of Directional Radiance Values. Remote Sensing of Environment, 18: 205–223 (1985) [CrossRef] [Google Scholar]
- D.S. Kimes, P.J. Sellers and W.W. Newcomb, Hemispherical Reflectance Variations of Vegetation Canopies and Implications for Global and Regional Energy Budget Studies. Journal of Climate and Applied Meteorology, 26: 959–972 (1987) [CrossRef] [Google Scholar]
- A. Henderson and M. Wilson., Surface albedo data for climatic modeling. Reviews of Geophysics. 21: 1743–1778 (1983) [CrossRef] [Google Scholar]
- P. Sellers, B. Meeson, F. Hall, et al. Remote sensing of the land surface for studies of global change: Models-Algorithms-Experiments. Remote Sensing of Environment, 51: 3–26 (1995) [CrossRef] [Google Scholar]
- Z. Wang, C. Schaaf, Q. Sun, et al. Capturing rapid land surface dynamics with Collection V006 MODIS BRDF/NBAR/Albedo (MCD43) products. Remote Sensing of Environment, 207 50-64 (2018) [CrossRef] [Google Scholar]
- Z. Wang, A. Erb, C. Schaaf, et al. Early spring postfire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data. Remote sensing of environment, 185: 71-83 (2016) [CrossRef] [PubMed] [Google Scholar]
- P. Lewis, et al. The ESA globAlbedo project: Algorithm. In: 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich. 57455748 (2012) [Google Scholar]
- W. Lucht, C. Schaaf and A. Strahler, An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 38 977–998 (2000) [CrossRef] [Google Scholar]
- C. Schaaf, F. Gao, A. Strahler, et al. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83: 135–148 (2002) [CrossRef] [Google Scholar]
- C. Bacour and F. Bréon, Variability of biome reflectance directional signatures as seen by POLDER. Remote Sensing of Environment, 98 8095 (2005) [CrossRef] [Google Scholar]
- S. Liang, X. Zhao, S. Liu, et al. A long-term Global Land Surface Satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth, 6 5-33 (2013) [CrossRef] [Google Scholar]
- Q. Liu, L. Wang, Y. Qu, et al. Preliminary evaluation of the long-term GLASS albedo product. International Journal of Digital Earth, 6: 69-95 (2013) [CrossRef] [Google Scholar]
- Y. Shuai, J. Masek, F. Gao, et al. An algorithm for the retrieval of 30-m snow-free albedo from Landsat surface reflectance and MODIS BRDF. Remote Sensing of Environment, 115 2204-2216 (2011) [CrossRef] [Google Scholar]
- Y. Shuai, J. Masek, F. Gao, et al. 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, 152 467-479 (2014) [CrossRef] [Google Scholar]
- Y.H. Zheng, L. Huang and J. Zhai, Impacts of land cover changes on surface albedo in China, the United States, India and Brazil. Journal of Remote Sensing(Chinese), 24: 917-932 (2020) [Google Scholar]
- H. Zhang, Z.T. Jiao, D.Y. Dong, et al. Albedo retrieved from BRDF archetype and surface directional reflectance. Journal of Remote Sensing(Chinese), 19 355-367 (2015) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.