(i) Raster and vector are two very different but common data formats used to store geospatial data. Raster data: It represents a graphic feature as a pattern of grids of squares. Raster data type consists of rows and columns of cells, with each cell storing a single value. The relationship between cell size and the number of cells is expressed as the resolution of the raster. Raster data can be images with each pixel containing a color value. Rasters often look pixelated because each pixel is associated with a value or class.
Rasters are digital aerial photographs, imagery from satellites, digital pictures, or even scanned maps. Below is an example of a classified raster dataset showing land use pattern.
In the diagram below, you can see how this simple polygon feature will be represented by a raster dataset at various cell sizes.
Vector Data Format: Vector data use X and Y coordinates to define the locations of points, lines, and areas (Polygons). Line (or arc) data is used to represent linear features like rivers, trails, streets, etc. Polygons are used to represent areas such as the boundary of a city. Point data is most commonly used to represent for geographical features that can best be expressed by a single point reference like city.
A given vector map using each of the vector elements: points, lines, and a polygon.
(ii) The following sequences of the activities are involved in GIS related work:
Spatial data Input: The spatial database into a GIS can be created from a various sources and may be divided into two categories:
The most common ways of inputting spatial data in to a GIS are through digitisation and canning.
Entering of the attribute data: Attribute data define the properties of a spatial entity that need to be handled in the GIS. For example, a river may be captured as a line entity. These are represented in the spatial part of the GIS by a certain colour, symbol, etc.
Data Verification and Editing: The spatial data captured of GIS requires verification and editing to ensure the accuracy of data. The errors caused during digitisation may include data omissions, and under/over shoots.
Spatial and attribute data linkages: The linkages of spatial and the attribute data are important in GIS. Matching of one data layer with another is also significant.
Spatial Analysis: It is a technique applied to structures at the human scale, most notably in the analysis of geographic data. The strength of the GIS lies in its analytical capabilities. It facilitates the study of real world processes by developing and applying models. The spatial analysis operation such as overlay analysis, buffer analysis, network analysis and digital terrain model, may be undertaken using GIS.
(i)
Raster Data Model |
Vector Data Model |
Raster data represent a graphic feature as a pattern of grids of squares. |
Vector data represent the object as a set of lines drawn between specific points. |
A raster file would represent this image by sub-dividing the paper into a matrix of small rectangles, similar to a sheet of graph paper called cells. |
A vector representation of the same diagonal line would record the position of the line by simply recording the coordinates of its starting and ending points. |
(ii) Overlay analysis is one of the spatial GIS operations. It integrates spatial data with attribute data. The hallmark of GIS is overlay operations. An integration of multiple layers of maps using overlay operations is an important analysis function. GIS makes it possible to overlay two or more thematic layers of maps of the same area. Map overlay can be used to study the changes in land use in different periods.
(iii) There are following advantages of a GIS:
(iv) The important components of a Geographical Information System are following:
(v) The following sequence of the activities are involved in GIS related work:
(vi) The word spatial is derived from space. The Spatial Information Technology relates to the use of the technological inputs in collecting, storing, retrieving, displaying, manipulating, managing and analysing the spatial information.
(i) (d) All the above forms
(ii) (b) Data display
(iii) (d) Difficult network analysis
(iv) (d) Compact data structure
(v) (a) Overlay operations
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