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2 seminars at UC Berkeley on GIS

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  • asha.weinstein@sjsu.edu
    ... IURD s next two Visiting Scholars Roundtables will deal with GIS. Both will take place in the conference room at 316 Wurster Hall, UC Berkeley. Thursday,
    Message 1 of 1 , Sep 20, 2006
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      ----- Forwarded by Asha Weinstein/SJSU on 09/20/2006 03:44 PM -----

      IURD's next two Visiting Scholars Roundtables will deal with GIS.
      Both will take place in the conference room at 316 Wurster Hall, UC Berkeley.

      Thursday, 9/21, 12 noon, Alan Forghani, GISC Visiting Scholar, on
      "Remote Sensing and GIS: Bushfire Mapping and Modeling."

      Strategies to better minimize damage from natural disasters such as
      wild fire, flood, severe wind, coastal erosion and tsunamis are
      essential to prosperity and safety, and national risk assessment
      methodologies play an essential role. Forghani will give an overview
      of remote sensing and GIS activities at the Australian Center for
      Remote Sensing (ACRES), focusing on the use of spatial information
      technologies capabilities in environmental monitoring, mapping and
      modeling. He will also examine bush fire spread risk mapping as an
      application and development process to establish a regional/national
      bushfire risk assessment framework at the UC Berkeley's Geographic
      Information Science Center (GISC).

      Tuesday, 10/10, 12 noon, Sharon Kazemi, GISC Visiting Scholar, on
      "Developments in Cartographic Generalization: Systems Perspective"

      Research and development of cartographic generalization for the past
      three decades provided the cartographers and GIS community with
      reliable and robust computer mapping solutions, but these still
      cannot compete with cartographers. Although much work has been done
      in the last decade on the development of various
      cartographic-automatic generalization algorithms, it appears the need
      to evaluate and validate existing generalization tools has been
      overlooked. Kazemi's Ph.D. research at the University of New South
      Wales (UNSW) assesses the existing generalization systems to develop
      a detailed generalization framework for deriving multi-scale data and
      map products from a single high-resolution database. This talk
      highlights the need to the maintain one master database in order to
      reduce data handling and data duplication, discuss the generalization
      themes, frameworks and operations. Later, well-known generalization
      tools are introduced, and then assessed as test beds based on the
      principles of generalization leading to development of
      conceptual-practical framework to generalize road networks databases.
      It is done to build a practical generalization framework and workflow
      in order deliver coherent capabilities to automate the generalization
      of roads for use in "derivative mapping" applications.


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