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Improving Temporal Frequency of Landsat Surface Temperature Products Using the Gap-Filling Algorithm

Open-File Report 2023-1006
By: , , , , , , and 
https://doi.org/10.3133/ofr20231006

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Abstract

Remotely sensed surface temperature (ST) has been widely used to monitor and assess landscape thermal conditions, hydrologic modeling, and surface energy balance. Landsat thermal sensors have continuously measured the Earth surface thermal radiance since August 1982. The thermal radiance measurements are atmospherically compensated and converted to Landsat STs and delivered as part of the U.S. Geological Survey Landsat Collection 1 U.S. Analysis Ready Data; however, the low satellite revisit cycles combined with the presence of clouds and cloud shadows reduce the number of valid retrievals. This reduction can limit the ability to monitor annual or seasonal variations in the surface thermal budget. These factors reduce the ability to use the temperature data to fit time series for historical trend analysis to match background climate variations. In this study, we implemented an approach that uses linear harmonic least absolute shrinkage and selection operator regression models to fill gaps because of clouds, shadows, and coarse temporal resolution. The gap-filled data provide increased temporal density of Landsat ST records. The gap-filled Landsat ST, therefore, can allow for an improved monitoring of annual, seasonal, or even monthly landscape thermal conditions.

Suggested Citation

Xian, G., Shi, H., Arab, S., Mueller, C., Hussain, R., Sayler, K., and Howard, D., 2023, Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm: U.S. Geological Survey Open-File Report 2023–1006, 15 p., https://doi.org/10.3133/ofr20231006.

ISSN: 2331-1258 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Enhancement of Temporal Density of Landsat Surface Temperature Data
  • Results for Gap-Filled Surface Temperature Data
  • Summary and Conclusions
  • References Cited
Publication type Report
Publication Subtype USGS Numbered Series
Title Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm
Series title Open-File Report
Series number 2023-1006
DOI 10.3133/ofr20231006
Year Published 2023
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description vi, 15 p.
Country United States
State Georgia
City Atlanta
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details