GeoISEM Home         Spatial modeling and analysis of nearshore environment using Open source GIS Helena Mitasova and Tom Drake

Department of Marine, Earth and Atmospheric Sciences North Carolina State University Raleigh NC
email: hmitaso@unity.ncsu.edu

Coastal studies involve processing, analysis and visualization of large spatial data sets, often in different computational environments, coordinate systems and formats. Geographic Information System (GIS) as a tool for management of georeferenced data, is a natural choice for integration of these heterogeneous data. However, the traditional concept of a 2D static GIS is not sufficient and extension of GIS capabilities is needed. Recent developments in Open Source GIS as well as the industry-wide moves towards open, extendable GIS created opportunities to enhance and develop new tools suitable for coastal applications.

The presentation focus is on evaluation and enhancements of Open source GIS methods and tools for spatial interpolation (gridding) of coastal data with simultaneous analysis of terrain geometry using Regularized Spline with Tension and visualization. Surface geometry analysis which includes the computation of slope, aspect, various types of curvatures as well as partial derivatives, can be performed at various levels of detail. GRASS GIS visualization is demonstrated by interactive analysis of measured data and models, using multiple surfaces, cutting planes, lighting and spatial query as powerful tools for gaining better understanding of measured data and studied phenomena.

The link between process modeling and GIS is discussed using our experience with multiscale spatial modeling of surface hydrology and overland flow erosion, using path sampling method and possible coastal applications will be discussed.

The Open source GIS tools will be illustrated by applications to LIDAR coastal data, Real Time Kinematic Survey measurements and other types of coastal and nearshore mapping.

powerpoint presentation

Jockey's Ridge interpolated by RST from LIDAR (data from ...NOAA)