Introduction to GIS notes by maveric149/2002-03-19 Lecture

Introduction to GIS notes by maveric149 2002-03-19 Lecture

Raster data structures

Cector data structre is good for siaplay discrete features, not. Raster data structure is good fo coverages, generates calure for every cell in a grid.

Examples

• elevation data, satellite imagery, orthophotes, scanned maps, graphic files

Way use raster?

• large additonal set of GIS analyses, most GIS software allow simultaneous display a and alysis of reawster and vecotor data.

Componets

• Grid consistis of rows and columns
• Point is difine by a whole cell in raster model
• line is defined by a sequence of neighboring cells
• Areas are represented by collections of contiguous cells.

Cells

• integer vlues represent categorical data
• floating point numbers typically represtend continuous data

• No spearation between spatial and attrbute data
• resolution is determined by cell size. large cells can't represent the precise locacton of spatial features.

• greid is usually projected on a coordinate system like UTM
• Grid data have fied cell location

Types of raster data

remote sensed images (Landsate, AVHRR)

• SPOT imagery from France
• all need separtate image processig software (RDAS and ER Mapper)
• Digital Elevation Models (array of uniformly spaced elevation data that is point based)

Digital orthophot quad

• processed aerial photographs to remove distortion caused by camera tilt and relief
• georeferenced
• can be registerd with topographic can other maps

Digital raster graphics

• scanned USGS topo map

Graphic fies

TIFF, GIF, and JPEG

Encoding

• cell by cell encoding (every cell has a value in the grid) = no compression, used for DEMs
• Run length encoding (only mention cells that have a specific value & then only note the beginning and end values of each row) = some compression of data
• Chain code compression (records the boundary of a region of redundant values by specifyin cardinal direction) = greater amount of compression
• Block code compression (breaks raster region into square blocks) = stars by stating

Compression

• Lossless or reversible compression
• Lossy or Irreversible compression

MrSID (multi-resolution seamless image datbase) allows ecalliung the image at differeent scales and resutions

• Zip, tar

Distortion

Warping or rubber sheeting ay be needed to allow the closest fit between raster and vector data (georeferencing)

Conversion

rasteriation or vectorization of data (both need computer algorihms)

Integration

allow for processin of sicrete and continuopus data at the same time.