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Klein, Levente J und Albrecht, Conrad M (2022) Urban Forests for Carbon Sequestration and Heat Island Mitigation. "Fragile Earth" workshop (AI for Good) at ACM Knowledge Discovery and Data Mining (KDD) conference, 2022-08-14 - 2022-08-18, Washington, DC, USA.
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Offizielle URL: https://ai4good.org/wp-content/uploads/2022/08/FE2022-Urban-Forests-for-Carbon-Sequestration-and-Heat-Island.pdf
Kurzfassung
Urban forests serve both as a carbon sequestration pool and heat island mitigation tool. Climate change will increase the frequency and severity of urban heat islands. Thus, new urban planning strategies demand our attention. Based on multimodal, remotely sensed data, we map the tree density, its carbon sequestered, and its impact on urban heat islands for Long Island, NY and Dallas, TX. Using local climate zones we investigate concepts of urban planning through optimized tree planting and adjusting building designs to mitigate urban heat islands.
| elib-URL des Eintrags: | https://elib.dlr.de/187233/ | ||||||||||||
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| Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||
| Zusätzliche Informationen: | workshop webpage: https://ai4good.org/fragile-earth-2022 | ||||||||||||
| Titel: | Urban Forests for Carbon Sequestration and Heat Island Mitigation | ||||||||||||
| Autoren: |
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| Datum: | August 2022 | ||||||||||||
| Referierte Publikation: | Ja | ||||||||||||
| Open Access: | Ja | ||||||||||||
| Gold Open Access: | Nein | ||||||||||||
| In SCOPUS: | Nein | ||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||
| Seitenbereich: | Seiten 1-8 | ||||||||||||
| Status: | veröffentlicht | ||||||||||||
| Stichwörter: | heat island mitigation, carbon sequestrations, urban planning, local climate zones, big geospatial data analytics, LiDAR, Landsat 8 surface temperature | ||||||||||||
| Veranstaltungstitel: | "Fragile Earth" workshop (AI for Good) at ACM Knowledge Discovery and Data Mining (KDD) conference | ||||||||||||
| Veranstaltungsort: | Washington, DC, USA | ||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||
| Veranstaltungsbeginn: | 14 August 2022 | ||||||||||||
| Veranstaltungsende: | 18 August 2022 | ||||||||||||
| Veranstalter : | Association for Computing Machinery | ||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||
| HGF - Programm: | Raumfahrt | ||||||||||||
| HGF - Programmthema: | Erdbeobachtung | ||||||||||||
| DLR - Schwerpunkt: | Raumfahrt | ||||||||||||
| DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | R - Künstliche Intelligenz | ||||||||||||
| Standort: | Oberpfaffenhofen | ||||||||||||
| Institute & Einrichtungen: | Institut für Methodik der Fernerkundung > EO Data Science | ||||||||||||
| Hinterlegt von: | Albrecht, Conrad M | ||||||||||||
| Hinterlegt am: | 11 Jul 2022 11:41 | ||||||||||||
| Letzte Änderung: | 24 Apr 2024 20:48 |
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