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by: Jamarcus Ritchie V


Jamarcus Ritchie V
Texas A&M
GPA 3.59

A. Klein

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About this Document

A. Klein
Class Notes
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This 6 page Class Notes was uploaded by Jamarcus Ritchie V on Wednesday October 21, 2015. The Class Notes belongs to GEOG 665 at Texas A&M University taught by A. Klein in Fall. Since its upload, it has received 45 views. For similar materials see /class/225769/geog-665-texas-a-m-university in Geography at Texas A&M University.




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Date Created: 10/21/15
Map Algebra Topics for Tonight 0 Focal Functions 7 GIS Operators 7 How Focal Functions are accomplished 7 Some Examples 0 Map Algebra 7 Rescaling 7 Determining Weights Operators Arithmetic Relational Bitwise Boolean Combinational Logical Accumulative possrwewwe Assignment Arithmetic Ilm H II H Relational H I II III E III Boolean ImI I I IE 8 ll E III Neighborhood Functions Won t you be my Neighbor Types of Neighborhood Analysis 0 Total neighborhood analysis examine a unifying attribute for the entire area eg crime 0 targeted analysis focus on smaller portions of the total area eg high crime neighborhoods 0 extended neighborhoods include areas adjacent to the target neighborhood as well Types of Neighborhoods Static functions 0 analysis occurs at once for the entire selected target area Roving Window functions 0 analysis occurs within the framework of a window that moves across the coverage 1 Focal Functions 2 Block Functions Types of Windows Rectangle Doughnuts Typical Roving Window Analysls l l 39 39 T quot quot 39 E Valuecalculatedforcenter quotl l T 39 quot pixelofrectangle I a V theboxusuallyhasodd i dimensions in x andY l l commonly the dimensions are equal Typical Roving Window Analysls 7 J I I I l Theboxthenmovesacertain l T 39 quot numberofcellsoverinboth 397 V L 7 XandYandanewvalueis 39 i calculated quot 5 A H F 439 Typical Roving Window Analysis 39 Tneprneessistlnenrepeatea fortlne entire gin Focal Functions Actually as mentioned in DeMers tlnere are two different types Focal and Block 71 will illustrate the difference Types of Filters HighPass sharpening Low Pass smoothing Directional give arneasure ofonentation Edge Detection Terrain Analysis Using aDigital Elevation Model many things can be calculated Slope Aspect Hillshading Visibility What can be seen from a certain point Hillshade Hillshading calculates the hypothetical illumination ofa surface by determining illumination values for each cell in an elevation grid It does so by evaluating the relationship between the position ofthe light source and the irection and steepness ofthe terrain It can greatly enhance the visualization ofa surface for analysis or graphical display Visibility lnvi sibie 7 9 2 Scale for comparisons Saaty and Vargas 1991 Equal importance Moderate prevalence of one over another Strong or essential prevalence Very strong or demonstrated prevalence Extremely high prevalence 4 o 8 Intermediate values Reciprocals For inverse compan39son How do we determine weights 0 Rescaling data to common ranges 0 Various methods to determine weighs Analytical Hierarchy Process AHP Relative weighting of factors Knst Distances Distances Fncture slopes Sailtypes dlstnbnnmts ta minor tn mum densities ruilts streams Karsi dmnlmmans i instances ta mini ruilts U5 t usincesta nnaisireims US in i Fracture demoes U2 3 2 i stapes w W m w i Types 18 U5 U5 U8 m i Weights n 4243 n 1399 in ms in 2542 in mm mm Conn arSail stencymoa n 2


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