- #Raster data models archive#
- #Raster data models software#
In map algebram the fundamental building block of representation is a cell that represents a localtion having some attribute (a value). Because it is a language of functions that treat map layers as inputs and outputs, and that create new map layers as outputs these techniques are sometimes known as Cartographic Modeling, The term Map Algebra is also sometimes used.Ī Functional Vocabulary of Rasters and Map Algebra Whereas SQL can be said to be the offspring of set theory, Tomlin's language for Cartographic Modeling takes its metaphor from map overlays.
#Raster data models software#
Dana Tomlin is credited for describing (if not inventing) this language of tools in the early 1980s in a software package named the Map Analysis Package. Raster GIS has a similar family of procedures that are much different from SQL. Like Vector-Relational GIS has its language of logical operators for filtering, transforming and associating enitities represented in tables. Spatial Models for Scholarship and Decistion Support.
#Raster data models archive#
Click here to download the zip archive of the sample dataset. It is not uncommon to have GIS analyses that use both Raster and Vector procedures. Raster and Vector data models and analytical techniques are both important tools for people concerned with spatial problems. Disintegrating these lumpy features into cells facilitiates exploration the juxtaposition of conditions on a cell-by-cell basis. Rasters can also represent categorical phenomena like land use or census geography. Examples include: Elevation, and its derivitive, slope diffuse phenoena such of sound or air polution, cumulative costs associated with traveling over the landscape, and many more. There are many aspects of the landscape that are more conveniently modeled as raster layers. These layers are suited to representing phenomena that vary in a smooth, continuous fashion from one location to another. While vector data models attempt to represent discrete features, raster datasets represent "locations" in a layer of congruent cells. We have also looked at raster / cell-based data like terrain models and imagery we downloaded from the U.S. For example it can be helpful to think of a transit stop as a point or a property parcel as a polygon. For many purposes the chunkification of the world can be helpful. The entities represented are singular and discrete. The vocabulary of vector-relational GIS is categorical in nature. These allow us to explore spatial relationships like proximity or overlap. Vector GIS extends relational databse functions with spatial data types and spatial functions. Relational databases provide a collection of tools (structured query language) that allow us to represent and explore relationships between these entities. In previous tutorials we have looked at the language of relational data models that represent entities as collections of attributes stored as rows in tables. This tutorial introduces several useful tools and patterns for using raster GIS data and procedures. Analytic Techniques Common Patterns in Raster Modeling
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