Potential analysis of feature extraction based quick response for environmental change with social media photos

Yuanfeng Wu, Lianru Gao, Wenzhi Liao, Paolo Gamba, Bing Zhang

Research output: Contribution to conferencePaper

Abstract

A framework based on color feature extraction of social media photos and correlation analysis with air quality parameters is proposed to monitor environmental change. More specifically, photos of the Beijing Olympic Park from Panoramio website have been analyzed as a case study. The aerosol optical depth data at 500 nm wavelength (AOD 500) obtained from sun-photometer observation network station has been used as reference. Results show a proof of concept that social media photos have an interesting potential for air pollution estimate and remote sensing parameter validation with a low cost.
Original languageEnglish
Pages1132-1135
Number of pages4
DOIs
Publication statusPublished - 5 Nov 2018
Event38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain
Duration: 22 Jul 201827 Jul 2018

Conference

Conference38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
CountrySpain
CityValencia
Period22/07/1827/07/18

    Fingerprint

Keywords

  • big data
  • social media
  • remote sensing
  • feature exaction
  • air pollution monitoring
  • image color analysis
  • correlation
  • aerosols

Cite this

Wu, Y., Gao, L., Liao, W., Gamba, P., & Zhang, B. (2018). Potential analysis of feature extraction based quick response for environmental change with social media photos. 1132-1135. Paper presented at 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain. https://doi.org/10.1109/IGARSS.2018.8518696