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DEVELOPMENT of A CITSCI and ARTIFICIAL INTELLIGENCE SUPPORTED GIS PLATFORM for LANDSLIDE DATA COLLECTION

  • R. Can
  • , S. Kocaman
  • , C. Gokceoglu
  • Hacettepe University

Research output: Contribution to journalConference articlepeer-review

10 Citations (Scopus)

Abstract

Geospatial data are fundamental to understand the relationship between the geographical events and the Earth dynamics. Although the geospatial technologies aid geodata collection, the increasing possibilities yield new application areas and cause even a greater demand. Considering the increment in data quantity and diversity, to be able to work with the data, they must be collected, stored, analysed and presented with the help of specifically designed platforms. Geographical Information Systems (GIS) with mobile and web support are the most suitable platforms for these purposes. On the other hand, the location-enabled mobile, web and geospatial technologies empowered the rise of the citizen science (CitSci) projects. With the CitSci, mobile GIS platforms enable the data to be collected from almost any location. As the size of the collected data increases, considering automatic control of the data quality has become a necessity. Integrating artificial intelligence (AI) with the CitSci based GIS designs allows automatic quality control of the data and helps eliminating data validation problem in CitSci. For this reason, the purpose of the present study is to develop a CitSci and AI supported GIS platform for landslide data collection because landslide hazard mitigation efforts require landslide susceptibility, hazard and risk assessments. Especially, landslide hazard assessments are necessary the time of occurrence of a landslide. Although this information is crucial, it is almost impossible to collect time of occurrence in regional hazard assessment efforts. Consequently, use of CitSci for this purpose may provide valuable information for landslide hazard assessments.

Original languageEnglish
Pages (from-to)43-50
Number of pages8
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume43
Issue numberB5
DOIs
Publication statusPublished - 6 Aug 2020
Event2020 24th ISPRS Congress - Technical Commission V (TC-V) on Education and Outreach - Youth Forum - Nice, Virtual, France
Duration: 31 Aug 20202 Sept 2020

Keywords

  • CNN
  • Citizen Science
  • Data Quality
  • Deep Learning
  • Landslide
  • WebGIS

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