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Global comparison of diverse scaling factors and regression models for downscaling Landsat-8 thermal data
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Current LST products are constrained by the trade-off between spatial and temporal resolutions imposed by sensor fabrication limitations, which severely limits their practical applications.
“current LST products are often constrained by the trade-off between spatial and temporal resolutions.”
From PGDM: Physically guided diffusion model for land surface temperature downscaling (2025) · cites this paper as Dong et al., 2020
For both the kernel-driven and DCF models, the accuracy discrepancy between the linear and nonlinear variants is not significant.
“For both the kernel-driven and DCF models, the accuracy discrepancy between the linear and nonlinear variants is not significant, which is consistent with previous studies (Dong et al., 2020; Hutengs and Vohland, 2016).”
From PGDM: Physically guided diffusion model for land surface temperature downscaling (2025) · cites this paper as Dong et al., 2020
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Cited by
Sorted by citations
PGDM: Physically guided diffusion model for land surface temperature downscaling
Zhang, H., Tang, B.-H., Hu, T., Jiang, Y., & Li, Z.-L. (2025) · arXiv · doi:10.48550/arxiv.2511.05964 · Cited by 3
Metadata
- Authors
- Dong, P., Gao, L., Zhan, W., Liu, Z., Li, J., Lai, J., Li, H., Huang, F., Tamang, S. K., & Zhao, L.
- Affiliations
- Nanjing University (CN)
- University of Minnesota (US)
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Zhan, Wenfeng
- Venue
- ISPRS Journal of Photogrammetry and Remote Sensing
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 169
- Pages
- 44-56
- ISSN
- 0924-2716 (ISSN-L)
- OpenAlex
- W3086090559
- Cited by
- 52
- References
- 0
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 7 · 2023: 6 · 2022: 9 · 2021: 4
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
- Funders
- National Key Research and Development Program of China (2016YFA0600201, 2016YFC1400903)
- Jiangsu Provincial Natural Science Foundation (BK20180009)
- National Natural Science Foundation of China (41671420)
- Fundamental Research Funds for the Central Universities (090414380024)
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Keywords
- statistical downscaling, land surface temperature, Landsat 8, scale factor, regression models, random forest, support vector regression, artificial neural networks, partial least squares regression, shortwave infrared bands, huts
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