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Article: Characterizing the relationship between satellite phenology and pollen season: A case study of birch

TitleCharacterizing the relationship between satellite phenology and pollen season: A case study of birch
Authors
KeywordsAllergic disease
Landsat
Phenology
Pollen
Spring leaf unfolding
Issue Date2019
Citation
Remote Sensing of Environment, 2019, v. 222, p. 267-274 How to Cite?
AbstractPollen released by vegetation in urban and surrounding rural areas is an important risk factor for respiratory allergies. Mapping the onset, duration, and severity of pollen is difficult, because of insufficient stations and/or monitoring networks at the national and international levels. To address this challenge, we evaluated the spatiotemporal relationship between satellite derived vegetation phenology and in-situ station derived information of pollen season during 2001–2015 at five stations in Canada. First, we calculated annual indicators of start of season (SOS) and start of pollen season (SPS) for birch from Landsat time series and pollen concentration data, respectively, at the five stations. Second, we explored the relationship between derived indicators of SOS and SPS and investigated the scale effect on the relationship. Our results indicate the Landsat based SOS is a good proxy for the indicator of SPS in the birch dominated area. The mean SOS and SPS in the study period are close (within 2.7 days) across the five stations. The interannual variability of SOS and SPS suggests the satellite derived phenology indicator can capture well the dynamics of pollen season in spring. Our analysis also indicates that the annual SOS at a finer resolution (30 m) is more consistent with SPS as compared to the indicators derived from coarser resolution satellite observations. This study shows the potential of using fine spatial resolution satellite data (e.g., Landsat) to derive the pollen season indicators, which is important for predicting pollen season severity and risk, and assessment of their impacts on respiratory allergies in urban domains.
Persistent Identifierhttp://hdl.handle.net/10722/329543
ISSN
2023 Impact Factor: 11.1
2023 SCImago Journal Rankings: 4.310
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xuecao-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorMeng, Lin-
dc.contributor.authorAsrar, Ghassem-
dc.contributor.authorSapkota, Amir-
dc.contributor.authorCoates, Frances-
dc.date.accessioned2023-08-09T03:33:33Z-
dc.date.available2023-08-09T03:33:33Z-
dc.date.issued2019-
dc.identifier.citationRemote Sensing of Environment, 2019, v. 222, p. 267-274-
dc.identifier.issn0034-4257-
dc.identifier.urihttp://hdl.handle.net/10722/329543-
dc.description.abstractPollen released by vegetation in urban and surrounding rural areas is an important risk factor for respiratory allergies. Mapping the onset, duration, and severity of pollen is difficult, because of insufficient stations and/or monitoring networks at the national and international levels. To address this challenge, we evaluated the spatiotemporal relationship between satellite derived vegetation phenology and in-situ station derived information of pollen season during 2001–2015 at five stations in Canada. First, we calculated annual indicators of start of season (SOS) and start of pollen season (SPS) for birch from Landsat time series and pollen concentration data, respectively, at the five stations. Second, we explored the relationship between derived indicators of SOS and SPS and investigated the scale effect on the relationship. Our results indicate the Landsat based SOS is a good proxy for the indicator of SPS in the birch dominated area. The mean SOS and SPS in the study period are close (within 2.7 days) across the five stations. The interannual variability of SOS and SPS suggests the satellite derived phenology indicator can capture well the dynamics of pollen season in spring. Our analysis also indicates that the annual SOS at a finer resolution (30 m) is more consistent with SPS as compared to the indicators derived from coarser resolution satellite observations. This study shows the potential of using fine spatial resolution satellite data (e.g., Landsat) to derive the pollen season indicators, which is important for predicting pollen season severity and risk, and assessment of their impacts on respiratory allergies in urban domains.-
dc.languageeng-
dc.relation.ispartofRemote Sensing of Environment-
dc.subjectAllergic disease-
dc.subjectLandsat-
dc.subjectPhenology-
dc.subjectPollen-
dc.subjectSpring leaf unfolding-
dc.titleCharacterizing the relationship between satellite phenology and pollen season: A case study of birch-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rse.2018.12.036-
dc.identifier.scopuseid_2-s2.0-85059634007-
dc.identifier.volume222-
dc.identifier.spage267-
dc.identifier.epage274-
dc.identifier.isiWOS:000457509000019-

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