A Multisensor Approach to Global Retrievals of Land Surface Albedo

Details

• Journal Title:
  Remote Sensing
• Personal Author:
  Riihelä, Aku ; Manninen, Terhikki ; Key, Jeffrey ; Sun, Qingsong ; Sütterlin, Melanie ; Lattanzio, Alessio ; Schaaf, Crystal
• NOAA Program & Office:
  NOAA General Documents
• Description:
  Satellite-based retrievals offer the most cost-effective way to comprehensively map the surface albedo of the Earth, a key variable for understanding the dynamics of radiative energy interactions in the atmosphere-surface system. Surface albedo retrievals have commonly been designed separately for each different spaceborne optical imager. Here, we introduce a novel type of processing framework that combines the data from two polar-orbiting optical imager families, the Advanced Very High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). The goal of the paper is to demonstrate that multisensor albedo retrievals can provide a significant reduction in the sampling time required for a robust and comprehensive surface albedo retrieval, without a major degradation in retrieval accuracy, as compared to state-of-the-art single-sensor retrievals. We evaluated the multisensor retrievals against reference in situ albedo measurements and compare them with existing datasets. The results show that global land surface albedo retrievals with a sampling period of 10 days can offer near-complete spatial coverage, with a retrieval bias mostly comparable to existing single sensor datasets, except for bright surfaces (deserts and snow) where the retrieval framework shows degraded performance because of atmospheric correction design compromises. A level difference is found between the single sensor datasets and the demonstrator developed here, pointing towards a need for further work in the atmospheric correction, particularly over bright surfaces, and inter-sensor radiance homogenization. The introduced framework is expandable to include other sensors in the future.
• Keywords:
  General Earth and Planetary Sciences
• Source:
  Remote Sensing, 10(6), 848
• DOI:
  https://doi.org/10.3390/rs10060848
• ISSN:
  2072-4292
• Format:
  PDF
• Publisher:
  MDPI AG
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Library
• Main Document Checksum:
  urn:sha-512:db7770ae57f78f74218996f7e0061eba11bf472e32d04f6a4792de4dcc69b43ec362024fe5a321ac4ace109835ab7507a28ff2867120b05ce3a31bcd7af07c83
• Download URL:
  https://repository.library.noaa.gov/view/noaa/62068/noaa_62068_DS1.pdf
• File Type:
  [PDF - 4.96 MB ]