RSLab Global Land Surface Albedo product from MODIS

作者：David Parastatidis, Nektarios Chrysoulakis · 年份：2023 · DOI：10.1109/jurse57346.2023.10144151 · 被引用次数：1 · 研究领域：Remote Sensing in Agriculture、Urban Heat Island Mitigation、Cryospheric studies and observations

Land surface albedo is one of the most important climate variables as it influences the radiation budget and the energy balance between the surface and the atmosphere. It is important to estimate and study in several scales from local to global scales. Satellites providing data on a regular basis are excellent information source to obtain global scale land surface albedo. There are several satellite products providing directional-hemispherical (black-sky) and bi-hemispherical (white-sky) albedo products, but time series of high spatial resolution true (blue-sky) albedo estimations at global level are yet not readily available. RSLab has exploited the capabilities of Google Earth Engine (GEE) for big data analysis to derive global snow-free daily land surface albedo estimations and trends at a 500m scale, using MODIS observations from 2000 to 2021. This study presents the updated RSLab surface albedo product from an updated estimation process, including new input products and a new user interface application, which can be found here: http://rslab.gr/albedo.html.