ICWG III/IVb: Remote Sensing Data Quality

Working Group Officers:



Chair  

Hussein M. AbdulmuttalibHussein M. Abdulmuttalib
GIS Department, Dubai Municipality
Baniyas Road
Deira, Dubai
UAE
+ 971 555500451

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Co-Chair  

Guoman HUANGGuoman HUANG
Chinese Academy of Surveying and Mapping
No. 28 Lianhuachixi Road
Haidian District
Beijing 100830
P.R. China
+86 10 63880615
+86 10 63880804

Co-Chair  

Thomas BlaschkeThomas Blaschke
Department of Geoinformatics - Z_GIS
University of Salzburg
Schillerstraße 30
5020 Salzburg
Austria
+43 662 8044 7525
+43 662 8044 7589

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Secretary  

Árpád BarsiÁrpád Barsi
Department of Photogrammetry and Geoinformatics
Budapest University of Technology and Economics
Budapest 1111
Műegyetem rkp. 3
Hungary
+36 1 463 1186
+36 1 463 3084

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Supporters

Key Support Personnel  

Anna ZihAnna Zih
Dubai Municipality GIS Department
Baniyas Road
Deira
Dubai
UAE
+ 971 56 4898599

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Terms of Reference:

  • Assess the current status of scientific development and applied practices, related to Remote Sensing Data Quality, and suggest development plans, researches, activities and projects for the improvements and advent of the same.
  • Liaison with sister commissions and WGs involved partially with data quality, and also with other International organizations to assist the development and improvement of Remote Sensing Data Quality Standards and Protocols, and promote their implementations worldwide.
  • Inventory and classify the elements of Remote Sensing Data Quality, and relate it to the quality of other disciplines, the usage and fitness of purpose, and to the simulated world model of data and information.
  • Encourage and support scientific works that deal with the improvement of remote sensing data quality processes and management steps, also that clarify and regulate the effects of error propagation due to acquisition, referencing, storing and archiving, processing, analysing, reporting and other operations related to remotely sensed data.
  • Clarify the quality aspects of Remote Sensing data, resulting and inherited from raster or vector-raster operations, such as but not limited to pixel processing, segmentation, classification, object base image analysis, image sensitivity analysis, etc.
  • Study the reliability and quality measures of Remote Sensing data, in relation to the different application areas that encounter remote sensing, such as environmental monitoring and sustainability, urban planning, city smartness and quality of life, also humanitarian projects for the developing world among other areas of application.
  • Assess Remote Sensing Data Quality with respect to the usage of automated major signatures of the electromagnetic spectral different phases, as much as the relations of the type to the sensors used and the area of application, coverage, visits. Sensor positions, sky clearness, etc.