Land Surface Emissivity Assessment for Temperature Mapping Using Dynamic World Classification
DOI:
https://doi.org/10.36023/ujrs.2026.13.2.305Keywords:
land surface emissivity, land surface temperature, land cover classification, Dynamic World, ASTER GEDAbstract
The temperature of the Earth's surface is one of the key characteristics used in modeling the state and dynamics of geosystem development, especially under anthropogenic load and landscape transformations. Over the decades of development of Earth remote sensing systems, a number of satellite sensors have been launched into orbit to obtain temperature mapping data, in particular in the thermal infrared spectral range of 3–14 μm. These include MODIS sensors (Terra and Aqua satellites), TM, ETM+, and TIRS (Landsat series satellites), as well as ASTER (Terra satellite).
A feature of remote thermal radiation studies, which fundamentally distinguishes them from traditional optical studies, within which spectral reflectance coefficients are determined, is the need to measure the characteristics of the energy flux radiated by the Earth's surface. This creates an additional non-trivial task: determining the emissivity of Earth's surface in the spectral range corresponding to the range of thermal radiation registration.
One of the most successful approaches to determining the emissivity of the Earth's surface is the TES (Temperature/Emissivity Separation) method, applied to five-channel data in the long-wave infrared range from the ASTER sensor. On this basis, the geospatial product Global Emissivity Dataset (ASTER GED) was created, which, in particular, is used to generate temperature data from images of Landsat satellites; however, ASTER GED has a number of significant shortcomings that significantly limit its use for obtaining detailed, accurate, and up-to-date temperature distribution data. Taking into account the above-mentioned limitations of ASTER GED, the article proposes a statistical approach to generating images of the spatial distribution of emissivity based on Sentinel-2 optical imagery, using information on the type of the earth's surface derived from the Dynamic World classification. The paper proposes a methodology for obtaining up-to-date, physically justified, and informative emissivity data for subsequent use, together with long-wave infrared radiation data from Landsat satellites. A preliminary assessment of temperature determination accuracy showed that in approximately 90% of cases, the deviation of the temperature obtained using the updated method does not exceed 0.5 °C relative to the reference values.
Author Contributions: Conceptualization – M. Lubskyi and А. Khyzhniak; Methodology – M. Lubskyi; Formal Analysis and Data Processing – А. Lysenko and T. Orlenko; Investigation - M. Lubskyi, А. Lysenko and T. Orlenko; Writing – Original Draft Preparation – I. Piestova; Writing – Review & Editing - M. Lubskyi and I. Piestova. All authors have read and agreed to the published version of the manuscript.
Funding: Described technique is developed under the research Development and improvement of remote sensing data processing methods for geospatial modeling in solving problems of rational environmental management, governmental registration number № 0124U000360.
Disclosure of AI use: The GPT-4 language model was employed to improve the title, systematize the outline, and proofread the text for grammatical, punctuation, and syntactic accuracy.
Data Availability Statement: Data available on reasonable request from the authors.
Acknowledgments: The authors are grateful to the National Academy of Sciences of Ukraine for supporting this research. We are also grateful to the reviewers and editors for their valuable comments, recommendations, and attention to the work.
Conflicts of Interest: The authors declare no conflict of interest.
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