File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Using satellite data to estimate particulate air quality in a subtropical city: An evaluation of accuracy and sampling issues

TitleUsing satellite data to estimate particulate air quality in a subtropical city: An evaluation of accuracy and sampling issues
Authors
Issue Date2015
Citation
Remote Sensing Letters, 2015, v. 6, n. 5, p. 370-379 How to Cite?
AbstractAlthough satellite data are increasingly being used for particulate air quality studies, the applicability of satellite-derived aerosol optical depth (AOD or τ) products for use over tropical or subtropical cities with frequent cloud cover should be carefully examined. Using eight years of ground-based and satellite-based observations, we assess the accuracy and sampling issues of using satellite data to study particulate air quality over a typical subtropical city, Hong Kong, at monthly to yearly timescales. The validation of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products shows that 64.6% of the retrievals fall within an expected error envelope of ± (0.05 + 0.15τ) and that they have a low bias during the eight-year study period, thus suggesting that the accuracy of current satellite-derived AOD data still needs to be improved. In addition, the availability of satellite observations is typically less than 30% during the months in spring and summer and less than 35% over seasonal and yearly timescales due to the cloudy and rainy weather. Inadequate sampling issues result in large biases over monthly and seasonal timescales; however, satellite data do not have major sampling issues on the yearly timescale despite the positive bias due to the washout effects of rain.
Persistent Identifierhttp://hdl.handle.net/10722/329356
ISSN
2023 Impact Factor: 1.4
2023 SCImago Journal Rankings: 0.458
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Ming-
dc.contributor.authorHuang, Bo-
dc.contributor.authorJiang, Renrong-
dc.date.accessioned2023-08-09T03:32:12Z-
dc.date.available2023-08-09T03:32:12Z-
dc.date.issued2015-
dc.identifier.citationRemote Sensing Letters, 2015, v. 6, n. 5, p. 370-379-
dc.identifier.issn2150-704X-
dc.identifier.urihttp://hdl.handle.net/10722/329356-
dc.description.abstractAlthough satellite data are increasingly being used for particulate air quality studies, the applicability of satellite-derived aerosol optical depth (AOD or τ) products for use over tropical or subtropical cities with frequent cloud cover should be carefully examined. Using eight years of ground-based and satellite-based observations, we assess the accuracy and sampling issues of using satellite data to study particulate air quality over a typical subtropical city, Hong Kong, at monthly to yearly timescales. The validation of Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products shows that 64.6% of the retrievals fall within an expected error envelope of ± (0.05 + 0.15τ) and that they have a low bias during the eight-year study period, thus suggesting that the accuracy of current satellite-derived AOD data still needs to be improved. In addition, the availability of satellite observations is typically less than 30% during the months in spring and summer and less than 35% over seasonal and yearly timescales due to the cloudy and rainy weather. Inadequate sampling issues result in large biases over monthly and seasonal timescales; however, satellite data do not have major sampling issues on the yearly timescale despite the positive bias due to the washout effects of rain.-
dc.languageeng-
dc.relation.ispartofRemote Sensing Letters-
dc.titleUsing satellite data to estimate particulate air quality in a subtropical city: An evaluation of accuracy and sampling issues-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/2150704X.2015.1035771-
dc.identifier.scopuseid_2-s2.0-84929470655-
dc.identifier.volume6-
dc.identifier.issue5-
dc.identifier.spage370-
dc.identifier.epage379-
dc.identifier.eissn2150-7058-
dc.identifier.isiWOS:000355160800004-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats