Global Landsat image acquisition probability: 1984–2023
• Cloud cover threshold is set at 24 % for global Landsat acquisition assessments. • Landsat achieves 45 % acquisition probability over 40 years at 24 % cloud threshold. • ETM + shows higher acquisition probability than OLI and TM at 24 % cloud threshold. • Landsat imagery acquisition probability peaks in Africa and troughs in Europe. • Climate drives spatial and temporal variations in Landsat acquisition probability. Cloud cover affects and reacts to climate change, and it obstructs optical observations. Despite the existence of historical Landsat scene cloud cover data, the image acquisition probability (IAP) of global Landsat has not yet been examined under a universal cloud cover threshold. The recently proposed coarse-and-fine thresholding (CAFT) method, designed to minimize cloud interference while optimizing imaging supply, shows potential for establishing such a threshold for studying sub-continental IAPs. Nevertheless, the CAFT’s feasibility and effectiveness in establishing a worldwide threshold have not been evaluated. With the 1984–2023 scene cloud cover of global (excluding Antarctica) Landsat-5/7/8 Thematic Mapper (TM), Enhanced TM Plus (ETM+), and Operational Land Imager (OLI) imagery (nearly six million), we explored a universal threshold among six continents using CAFT to derive global annual IAPs and then examined their geographic, temporal, and senor-based variations. We concluded that the pre-defined 24% can be a globally applicable threshold and the 40-year benchmarking IAP of global Landsat is estimated to be nearly 45%. ETM+ has higher global average IAPs (>47%) compared to OLI (45%) and TM (43%). Monthly and annual IAP variations are more pronounced at continental scales, with the highest in Africa and the lowest in Europe. Notably, climate explains the latitudinal and temporal differences, showing higher and lower IAPs in the Arid and Polar climate zones, respectively. Through the evaluation of Landsat 40-year scene cloud cover, this study provides a comprehensive understanding of global IAPs and suggests the necessity to examine the dynamics and mechanisms of pixel-based cloud cover.
Authors
- Suresh Chand (ORCID: https://orcid.org/0000-0002-7445-8933)
- Yin Yang (ORCID: https://orcid.org/0000-0003-2602-3078)
- Hong Yang (ORCID: https://orcid.org/0000-0002-8650-4802)
- Zhiming Feng (ORCID: https://orcid.org/0000-0002-3682-4955)
- Peng Li (ORCID: https://orcid.org/0000-0002-0849-5955)
Institutions
- University of Delhi (IN)
- National University of Defense Technology (CN)
- Chinese Academy of Sciences (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- International Journal of Applied Earth Observation and Geoinformation
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1016/j.jag.2025.104928
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00