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DTSTART:20200329T030000
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DTSTART:20191027T020000
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DTSTAMP:20260404T015744Z
UID:5c8a5b8a79239631863978@ist.ac.at
DTSTART:20200212T130000
DTEND:20200212T141500
DESCRIPTION:Speaker: Farid KARIMIPOUR\nAbstract: Geospatial data is data ab
 out objects\, events\, or phenomena that are associated to a unique locati
 on on Earth (i.e.\, georeferenced). Geographic Information SCience (GIScie
 nce) studies data structures and computational techniques to capture\, rep
 resent\, process\, and analyze geographic data and information. However\, 
 new advancements in geospatial data collection techniques have resulted in
  high volume multidimensional spatial datasets\, which cannot be easily tr
 eated using conventional spatial data analysis approaches. Moreover\, GISc
 ience is seeking efficient tools for analyzing increasing amount of geospa
 tial data acquired everyday about moving objects. Topological Data Analysi
 s (TDA) seems to be promising in this regards. However\, their extension f
 or taking the particular characteristics of geospatial data (e.g.\, locati
 on-awareness\, spatial autocorrelation\, and spatial dependency) into cons
 ideration would be beneficial. In this talk\, I will provide some ideas ab
 out extension of the classical persistent homology (as a main tool in TDA)
  that may contribute in better topological analysis of new geospatial data
 sets.
LOCATION:Mondi Seminar Room 3\, Central Building\, ISTA
ORGANIZER:hwagner@ist.ac.at
SUMMARY:Farid KARIMIPOUR: GeomTop Seminar: &quot\;Topological Data Analayis
  for Geospatial Data&quot\;
URL:https://talks-calendar.ista.ac.at/events/2639
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