GIS Science

a scientific field that studies the theories, methods, and technologies/ implications of geographic information

GIScience

the theories, methods, and technologies/ implications of geog info

GISystems

the organized collection of computer hardware, software, geog data, and infrastructure to collect, manage, display, and analyze maps

Spatial referencing systems (3)

geographic identifier/ linear/ coordinate

Vector data model

human-defined shapes // points, lines, and polygons // space is measured and defined by the objects it’s coutning

raster data model

organized into rows and columns (ie, cells and grids). space is fixed

tessellations

They provide a way of dividing up geographic space with a non-overlapping geometry (a grid)

Process = putting a grid on a map and selecting/ determining what is important and what is to be included. Errors will occur.

cell resolution

larger cell = lower resolution/ less detail

small cell = higher resolution/ more detail

raster registration

one raster data layer overlaying antoher raster data layer but have no coordinate system associated with it.

raster georeferencing

A raster data layer matched with a projected coordinate system (UTM, etc)

The transformation of an image into an alternate space (ie, a map)

Tracking cells (math)

by rows and column numbers as subscripts (rows before column)

mapping

determining the geographic location of features on earths curved surface and then transforming thoes location into position on a flat map

ground control points

points on the surface of the earth wehre both image and map coordinates can be identifes (ie, the coordinate points on an image ‘mathched’ with the points on a map

RMSE

Root Mean Square Error

a value that give a sense of accuracy in georeferencing.

a low value increases accuracy, not an absolute vlaue

data file strucures

byte, integer, real, ASCII, binary, packed binary

Truncate data

data are clipped without any rounding

eg. 3.14159 is → 3

Rounding data

data are rounded to the nearest integer based on the value of the next digit

eg. 3.14159 is → 3

floor data

data are rounded down to the nearest integer equal to or lower than the value

eg. 3.14159 is → 3

ceiling data

data are rounded up to the nearest integer equal to or higher than the value

eg. 3.14159 is → 4

map algebra characteristics

provides tools to perform raster analysis operations.

is based on matrix algebra (arrangement of numbers in rows and columns)

requires that there is a 1-to-1 correspondence between cells in the raster data being analyzed

creates new features and attribute relations by overlaying the features from 2 or more input map layers

map algebra

single groupd of cells with multiple layers used to combine layers, visualize info, extract info, and imporve understanding of raster data through label catageories and numberic values

local operations

preform calculations on a single cell

eg. multiplying cells in the exact same x,y, coords

[in layer ] * 2 —> [in layer a] + [in layer b] = [sum layer] —> [landslide risk] = [slope] + [aspect] + [precipitation]

focal operations

preform calculations on a neighbourhood of cells

eg, finding the mean of a 3-by-3 square, before moving onto the next 3-by-3 and doing it again to create a ‘smooth average’

zonal operations

preform calculations based on a zoned data layer

eg. a specific class or region

layer 1 = the zone/ region → layer 2 = the raster cell values

global operations

preform calculations for the entire data layer

eg., Euclidean distances, calculating a buffer from the center of each cell to its closest source (the 3-by-3 grid)

spatial proximal

a relationship within a distance of smth else.

near, far, absolute, relative

spatial topological identical

are spatially identical to smth

shape, size, location, vertices

spatial topological adjacent

are spatially next to one another/ neighbours

spatially directional

bearings and compass directions (NESW)

distance analysis - source cells

points, lines, or areas of interest

distance analysis - cells and cell size

cell size = resolution and affects precision and computation

distance analysis - barriers

impassable areas (eg, water, urban, etc)

distance analysis - cost/ friction surface

represents travel difficulty or resistance

distance analysis - elevation or terrain

movement often depends on slope and elevation

raster distance analysis (2)

measures distance from source cells across a raster surface

each cell stores a value representing distance, travel cost, direction, or allocation

euclidean distance operations

straight line from cell origin to destination (a to b) without pause

uses the pythagorean theorem fro 2+ points // (distance = SQR_/ (x2 - x1)² + (y2 - y1)²)

euclidean distance - characteristics/ def

source cells are objects of interest. these cells have values, while non-source cells do not have values

the distance grid contains the measures of distance from every outpout cell toioi the nearest source cell

creating zones around the soruce cells - like a buffer but not really

euclidean allocation

assigns a value identity to the cells with no value equal to the closest source cell

network distance - routing

typically vector. resutls can be used in a raster environment after rasterization for linear paths

geographical space characteristics

not a flat place // the real length is often more because of elevation changes // account the effect of altitude // trig calc increases the complexity due to computations and data requirements // not uniform in any direction

cost distance

Cost distance = cost friction * distance

Weighted distance operations across a surface.

calculated by multiplying cell resolution by the cost of each cell, then summing it. ie, (adjacent cost = [cost1 + cost2]/[2] * distance factor)

cost distance creation

the model creates a cross-country mobility cost surface// each location is given the cost per unit distance for moving through

the cost surface used is measured as you define (time, dollar, fuel) (eg, road construction ($) = f (soil type, slope, land value, etc)

cost surface friction

a measurement between 2 points — Distance is not always physical distance, sometimes it’s time, effort, or money

movement cost depends on terrain, lond cover, roads, slope, or restrictions

cost path

the optimal route between 2 locations

each cell stores a pointer to the next cell on the least-cost path to a source. supports paath tracing and connectivity analysis

direction to a point

direction from each cell to a specified target location

direction of greatest change

direction of steepest ascent of descent based on a raster surface (eg, DEM)

flow direction

direction that water would flow from each cell to one of its neighbouring cells

aspect direction

direction a slope is facinng (azimuth of downslope direction)

raster overlay analysis

combines 2+ layers by comparing/ calculating values

used to integrate multiple spatial variables that impact a process/ pattern

is actually a cell-by-cell operation (ie, focal map algebra)