Lecture 2 Introduction to GIS, Data models, Data structures

REPRESENTATION AND DATA STRUCTURES Coordinates and Attributes

Common Data Models

REPRESENTATION AND DATA STRUCTURES Most common data models define thematic layers Typically, layers, one layer for each distinct view of a theme

Part 1: Coordinates (Cartesian)

Spherical coordinate can be expressed two ways e.g., 44 o or o 30’35”(DMS) (DD)

We Can Convert

Three Types of Vector Features

One-to-one, because of Attributes

Enforced Uniformity

Planar Topology – no overlaps

On a blank sheet of paper, draw a topologically correct (not necessarily geometrically correct) rendition of the 6 coastal (name counties, if you can). Identify all the nodes. Create a table corresponding to the geographic data you drew (make the linkages clear). Include an attribute for county area, in square kilometers, and square miles

Rasters – Fixed Cell Size, Grid Orientation

Connecting data, contrast with vector

Raster, one-to-one correspondence, how many rows in the attribute table?

Number of cells = 100! Raster, one-to-one correspondence, rarely used

Many-to-one much more common, to tame the attribute table

How can we mimic a vector one-to-one relationship between individual polygon codes and table rows, when using a raster, without keeping track of individual cells?

Raster – The Mixed Pixel Problem Landcover map – Two classes, land or water Cell A is straightforward What category to assign For B, C, or D?

Resampling Ambiguity

Changing Resolution (resampling) with Categorical Data Assignment Method Matters!

Orientation and/or Cell Size May Differ

Resampling - Distance-weighted averaging continuous data: bilinear interpolation z

No Decision is Final – We Can Convert

Data and File Structures Data are stored as binary numbers Bits are 0 or 1 Bytes are 8 bits Data (e.g., raster cells) are often references as 1 byte, two byte, etc.

Cells Have a Type, Size Type – e.g., Real, unsigned integer, signed integer, text Size – 8 bit, 32 bit, 64 bit, long, short, character width These control the size of the datasets, and type of data that may be stored Mixing types, sizes, often requires some care

Raster data set properties We can store a number up To 2 or 4,293,967,296 in a cell 32

Data and File Structures Data often have specific organization to reduce size speed access ease updates

Example: ESRI Shapefiles Landcover dataset, wash_lc is a cluster of files, wash_lc.shp - containing the coordinates wash_lc.dbf - containing the attributes wash_lc.shx - containing linkages, other info wash_lc.prj - optional, containing projection information wash_lc.sbn - an optional indexing file Thursday, August 22, 13

Data and File Structures Compression Reducing size – e.g., raster run-length coding

Rasters – Discrete or Continuous Features Can we compress either without loss? discretecontinuous