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DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds
Research article (International Journal of Applied Earth Observation and Geoinformation, 2021) · cited 19× · AI/ML
DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds
Summary
DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds is a scholarly article[1].
Key Facts
DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds's instance of is recorded as scholarly article[2].
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds. Retrieved May 24, 2026, from https://4ort.xyz/entity/deepurbandownscale-a-physics-informed-deep-learning-framework-for-high-resolution-urban-surface-temperature-estimation-v
MLA“DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deepurbandownscale-a-physics-informed-deep-learning-framework-for-high-resolution-urban-surface-temperature-estimation-v.
BibTeX@misc{4ortxyz_deepurbandownscale-a-physics-informed-deep-learning-framework-for-high-resolution-urban-surface-temperature-estimation-v_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds}}, year = {2026}, url = {https://4ort.xyz/entity/deepurbandownscale-a-physics-informed-deep-learning-framework-for-high-resolution-urban-surface-temperature-estimation-v}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DeepUrbanDownscale: A physics informed deep learning framework for high-resolution urban surface temperature estimation via 3D point clouds — https://4ort.xyz/entity/deepurbandownscale-a-physics-informed-deep-learning-framework-for-high-resolution-urban-surface-temperature-estimation-v (retrieved 2026-05-24)
