REPRESENTATION OF SPATIAL AND TEMPORAL DATA IN ARCGIS
Representation of spatial and temporal data in ArcGIS
Jonathan Goodall, David Maidment and Jennifer Sorenson*
ABSTRACT: The representation of hydrologic phenomena in a Geographic Information System (GIS) requires the integration of geospatial data with time series. Rainfall, streamflow, nutrient loading, and stage are examples of hydrologic parameters that exhibit high spatial and temporal variability and, therefore, must be described with both spatial and temporal data. While the representation and visualization of geospatial hydrologic data in GIS is established practice, extending GIS to the temporal domain is a relatively new concept that introduces additional complexities. For example, hydrologic parameters can vary continuously over space and time (rainfall) or they can be recorded regularly (streamflow) or irregularly (water quality) at gages. In addition, hydrologic objects can have dynamic shapes (floodplain inundation) or their existence can be time-indexed (addition or removal of flow control structures). Understanding how to represent these cases in a GIS, and how ArcGIS can be used to render dynamic visualizations of temporal events, requires a data model for the temporal as well as spatial domains. This research explains enhancements to the temporal component of the Arc Hydro Data Model to better represent the various time series cases possible with hydrologic information. The result is a time series data model consisting of four components: Time Series, Attribute Series, Feature Series, and Raster Series. Time series describes the traditional, non-spatial use of time series, Attribute Series describes stationary features with dynamic attribute values, Feature Series describes moving features with dynamic attribute values, and Raster Series describes a sequence of raster datasets through time.
KEY TERMS: GIS, space time representation, dynamic rendering, ArcGIS Tracking Analyst
INTRODUCTION
To understand
Jonathan Goodall, David Maidment and Jennifer Sorenson*
ABSTRACT: The representation of hydrologic phenomena in a Geographic Information System (GIS) requires the integration of geospatial data with time series. Rainfall, streamflow, nutrient loading, and stage are examples of hydrologic parameters that exhibit high spatial and temporal variability and, therefore, must be described with both spatial and temporal data. While the representation and visualization of geospatial hydrologic data in GIS is established practice, extending GIS to the temporal domain is a relatively new concept that introduces additional complexities. For example, hydrologic parameters can vary continuously over space and time (rainfall) or they can be recorded regularly (streamflow) or irregularly (water quality) at gages. In addition, hydrologic objects can have dynamic shapes (floodplain inundation) or their existence can be time-indexed (addition or removal of flow control structures). Understanding how to represent these cases in a GIS, and how ArcGIS can be used to render dynamic visualizations of temporal events, requires a data model for the temporal as well as spatial domains. This research explains enhancements to the temporal component of the Arc Hydro Data Model to better represent the various time series cases possible with hydrologic information. The result is a time series data model consisting of four components: Time Series, Attribute Series, Feature Series, and Raster Series. Time series describes the traditional, non-spatial use of time series, Attribute Series describes stationary features with dynamic attribute values, Feature Series describes moving features with dynamic attribute values, and Raster Series describes a sequence of raster datasets through time.
KEY TERMS: GIS, space time representation, dynamic rendering, ArcGIS Tracking Analyst
INTRODUCTION
To understand
References: Blongewicz, M., 2000. DHI’s Water Modeling and GIS. GIS in Water Resources Conference, Austin, TX. Maidment, D.R. (ed.), 2002a. “Arc Hydro: GIS for Water Resources”. ESRI Press, Redlands, CA. Maidment, D.R., 2002b. Arc Hydro: GIS for Water Resources. University of Florida, Department of Environmental Engineering Sciences Research Colloquium, http://www.ees.ufl.edu/programs/archive.asp. Maidment, D.R., Fogg, A., Sorenson, J., Goodall, J.L., Strassberg, G., Martinez, S., Hampson, J., Aurit, M., Mercado, R., and Brink, T. , 2003, Enhanced Arc Hydro Framework for the South Florida Water Management District., Report presented to the South Florida Water Management District. Peuquet, D.J., 2001. Making Space for Time: Issues in Space-Time Data Representation. Geoinformatica 5(1):11-32. Sorenson, J., Maidment, D.R., and Goodall, J.L., 2004, Arc Hydro Time Series Framework for Defining Hydroperiod Inundation, Proceeding of the AWRA GIS in Water Resources III Conference, Nashville, TN. Using the ArcGISTM Tracking Analyst, 2002. ESRI Press, Redlands, CA.