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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume L-4/W2-2026
https://doi.org/10.5194/isprs-archives-L-4-W2-2026-245-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-archives-L-4-W2-2026-245-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Sep 2026
| 28 Sep 2026
Evaluating High-Resolution Geospatial Data for Urban Microclimate Simulations: A Comparative Study Using Official Local and Open Global Datasets in Sofia
Lidia Lazarova Vitanova
GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
Kunihiko Fujiwara
Research & Development Institute, Takenaka Corporation, Japan
Ryota Karube
GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
Graduate School of Science and Technology, University of Tsukuba, Japan
Evgeny Shirinyan
GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
Yasuhiko Azegami
Research & Development Institute, Takenaka Corporation, Japan
Quang-Van Doan
Graduate School of Science and Technology, University of Tsukuba, Japan
Hiroyuki Kusaka
Center for Computational Sciences, University of Tsukuba, Japan
Dessislava Petrova-Antonova
GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
Sylvia Ilieva
GATE Institute, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
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Short summary
This study proposes (i) the structural k-means (S k-means) algorithm for clustering spatiotemporally structured climate data and (ii) the clustering uncertainty evaluation framework (CUEF) based on the mutual-information concept.
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