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dc.contributor.authorWang, Xin
dc.contributor.authorDu, Peijun
dc.contributor.authorChen, Dongmei
dc.contributor.authorLin, Cong
dc.contributor.authorZheng, Hongrui
dc.contributor.authorGuo, Shanchuan
dc.date.accessioned2020-07-28T15:41:11Z
dc.date.available2020-07-28T15:41:11Z
dc.date.issued2020-07-17
dc.identifier.citationWang X, Du P, Chen D, Lin C, Zheng H, Guo S, Characterizing urbanizationinduced land surface phenology change from time-series remotely sensed images at fine spatiotemporal scale: A case study in Nanjing, China (2001-2018), Journal of Cleaner Production, https:// doi.org/10.1016/j.jclepro.2020.122487.en
dc.identifier.urihttp://hdl.handle.net/1974/27975
dc.descriptionThe final publication is available at Elsevier via https://doi.org/10.1016/j.jclepro.2020.122487 © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.description.abstractContinuous urban expansion and its influence on land surface phenology (LSP) have been gaining considerable attention due to their impacts on climate change, carbon cycling and human health. Most previous studies have investigated the effects of urbanization on LSP from the regional to global scales by using coarse-resolution remotely sensed images and fixed land cover boundary maps. However, the influences of urbanization on LSP are also important at the local level, particularly in and around rapidly urbanizing cities as LSP is closely linked to the local ecology and people’s health. To analyze the dynamic of urbanization and its effect on LSP at the local scale, this study proposed a novel framework of characterizing LSP with consideration of continuous urban expansion based on all available time-series Landsat and Moderate Resolution Image Spectroradiometer (MODIS) Reflectance and Enhanced Vegetation Index (EVI) composite data. The proposed approach was capable of evaluating LSP impacts of urbanization from three aspects: 1) the phenology difference between dynamic annual urban and rural areas; 2) the different rates of phenology trend between the permanent urban and rural areas; and 3) the phenology shifts in the areas that were urbanized during the period. This approach was applied to Nanjing, China and the experimental results indicated that when compared with the rural areas, the phenology cycle started 0.59 ± 0.58 days earlier (start of season, SOS) and ended 1.65 ± 1.55 days later (end of season, EOS) in urban areas, accordingly leading to increased growing season length (GSL) by 2.77 ± 2.61 days. Besides, the experiments also revealed that 70.81% SOS and 78.79% EOS in the permanent urban-rural areas were provided with delayed phenology trends, along with 80.72% of these regions tending to have a prolonged GSL. Furthermore, the rates of SOS and EOS delay in rural areas were 0.12 ± 0.12 day/year and 0.02 ± 0.02 day/year faster than those in urban areas, and the rate of GSL prolonging in urban regions was 0.04 ± 0.04 day/year faster than that in rural counterparts. For the urbanized regions in Nanjing, after experiencing conversion to the impervious surface, SOS and EOS delayed in 65.77% and 70.33% of the regions, accompanied by extended GSL in 70.83% of the regions. Overall, this research proposed a novel approach of analyzing urbanization implications for LSP at the city scale and demonstrated its priority of taking continuous land cover change into account.en
dc.language.isoenen
dc.publisherElsevieren
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectUrbanizationen
dc.subjectImpervious Surfaceen
dc.subjectEnsemble Continuous Change Detection and Classificationen
dc.subjectLand Surface Phenologyen
dc.subjectLandsaten
dc.subjectMODISen
dc.titleCharacterizing Urbanization-Induced Land Surface Phenology Change from Time-Series Remotely Sensed Images at Fine Spatio-Temporal Scale: A Case Study in Nanjing, China (2001–2018)en
dc.typejournal articleen
dc.identifier.doihttps:// doi.org/10.1016/j.jclepro.2020.122487
project.funder.identifierhttp://dx.doi.org/10.13039/501100001809en
project.funder.identifierhttp://dx.doi.org/10.13039/501100000038en
project.funder.identifierhttp://dx.doi.org/10.13039/501100004543en
project.funder.nameNational Natural Science Foundation of Chinaen
project.funder.nameNSERCen
project.funder.nameChina Scholarship Councilen
oaire.awardNumberNo. 41631176en


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