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Sun, Wenlu and Sun, Yao and Liu, Chenying and Albrecht, Conrad M (2023) DeepLCZChange: A Remote Sensing Deep Learning Model Architecture for Urban Climate Resilience. In: International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3616-3619. IGARSS 2023, July 16-21, 2023, Pasadena, CA, USA. doi: 10.1109/IGARSS52108.2023.10281573.
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Official URL: https://ieeexplore.ieee.org/document/10281573
Abstract
Urban land use structures impact local climate conditions of metropolitan areas. To shed light on the mechanism of local climate wrt. urban land use, we present a novel, data-driven deep learning architecture and pipeline, DeepLCZChange, to correlate airborne LiDAR data statistics with the Landsat 8 satellite's surface temperature product. A proof-of-concept numerical experiment utilizes corresponding remote sensing data for the city of New York to verify the cooling effect of urban forests.
| Item URL in elib: | https://elib.dlr.de/195495/ | ||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Poster) | ||||||||||||||||||||
| Additional Information: | latest version available as https://arxiv.org/abs/2306.06269 | ||||||||||||||||||||
| Title: | DeepLCZChange: A Remote Sensing Deep Learning Model Architecture for Urban Climate Resilience | ||||||||||||||||||||
| Authors: |
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| Date: | 2023 | ||||||||||||||||||||
| Journal or Publication Title: | International Geoscience and Remote Sensing Symposium (IGARSS) | ||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||
| Open Access: | No | ||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||
| DOI: | 10.1109/IGARSS52108.2023.10281573 | ||||||||||||||||||||
| Page Range: | pp. 3616-3619 | ||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||
| Keywords: | urban planning, local climate zones, climate resilience, LiDAR, Landsat 8, deep neural network architecture, explainable artificial intelligence | ||||||||||||||||||||
| Event Title: | IGARSS 2023 | ||||||||||||||||||||
| Event Location: | Pasadena, CA, USA | ||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||
| Event Dates: | July 16-21, 2023 | ||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||
| HGF - Program Themes: | Earth Observation | ||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||
| DLR - Research theme (Project): | R - Artificial Intelligence | ||||||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science | ||||||||||||||||||||
| Deposited By: | Albrecht, Conrad M | ||||||||||||||||||||
| Deposited On: | 22 Jun 2023 13:41 | ||||||||||||||||||||
| Last Modified: | 24 Nov 2023 18:43 |
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