Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/96507
DC Field | Value | Language |
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dc.contributor | Department of Land Surveying and Geo-Informatics | - |
dc.creator | Zhao, C | en_US |
dc.creator | Weng, Q | en_US |
dc.creator | Wang, Y | en_US |
dc.creator | Hu, Z | en_US |
dc.creator | Wu, C | en_US |
dc.date.accessioned | 2022-12-07T02:55:14Z | - |
dc.date.available | 2022-12-07T02:55:14Z | - |
dc.identifier.issn | 1548-1603 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/96507 | - |
dc.language.iso | en | en_US |
dc.publisher | Routledge, Taylor & Francis Group | en_US |
dc.rights | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. | en_US |
dc.rights | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.rights | The following publication Zhao, C., Weng, Q., Wang, Y., Hu, Z., & Wu, C. (2022). Use of local climate zones to assess the spatiotemporal variations of urban vegetation phenology in Austin, Texas, USA. GIScience & Remote Sensing, 59(1), 393-409 is available at https://doi.org/10.1080/15481603.2022.2033485. | en_US |
dc.subject | Austin metropolitan area | en_US |
dc.subject | Environmental sustainability | en_US |
dc.subject | Local climate zones | en_US |
dc.subject | Urban vegetation | en_US |
dc.subject | Urban-rural gradients | en_US |
dc.subject | Vegetation phenology | en_US |
dc.title | Use of local climate zones to assess the spatiotemporal variations of urban vegetation phenology in Austin, Texas, USA | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 393 | en_US |
dc.identifier.epage | 409 | en_US |
dc.identifier.volume | 59 | en_US |
dc.identifier.issue | 1 | en_US |
dc.identifier.doi | 10.1080/15481603.2022.2033485 | en_US |
dcterms.abstract | Phenological changes caused by urbanization may provide evidence of how vegetation responds to global warming. However, the phenological characteristics of vegetation in metropolitan areas have been poorly studied, especially in terms of spatiotemporal variations. In this study, we explored the applicability of Local Climate Zones (LCZs) to investigate the spatiotemporal variations in urban vegetation phenology by linking MODIS-derived phenology metrics with LCZs in the Austin metropolitan area in Texas, USA. We extracted three vegetation phenology metrics from MODIS data between 2008 and 2018, including the start of growing season, end of growing season, and length of the growing season (i.e. SOS, EOS, and LOS, respectively). The results showed that during the study period, the EOS and SOS gradually advanced, while LOS showed no obvious change. Statistical analysis was conducted to examine the spatiotemporal variations of the phenology metrics among different LCZs and along “Urban-Rural Gradients” (URGs). There were 37.5%, 75.0%, and 74.3% pairs of LCZs, indicating statistically significant phenological differences in terms of SOS, EOS, and LOS in 2012, respectively. In contrast, most pairs of URGs showed almost no differences in phenological metrics, especially in EOS. Geographically, SOS showed a fluctuating change with an advancing tendency, whereas the EOS decreased very slowly with distance from the city center (i.e. along the URGs). LCZs can be used to help identify distinctive phenology metrics with statistically significant differences, especially in EOS and LOS. Compared to URGs, LCZs offer a unique analytical framework for studying urban ecosystem patterns, functions, and dynamics. Lastly, LCZs can enable the identification of sensitive areas for ecological protection in support of sustainable urban development and environmental stewardship. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Giscience and remote sensing, 2022, v. 59, no. 1, p. 393-409 | en_US |
dcterms.isPartOf | Giscience and remote sensing | en_US |
dcterms.issued | 2022 | - |
dc.identifier.scopus | 2-s2.0-85124187579 | - |
dc.identifier.eissn | 1943-7226 | en_US |
dc.description.validate | 202212 bckw | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | - |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Zhao_Use_Local_Climate.pdf | 15.52 MB | Adobe PDF | View/Open |
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