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York University (35,167)
ESSE 3600 (11)
Sohn (11)
Lecture 11

# GIS Lecture 11.docx

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School
Department
Earth, Space Science and Engineering
Course
ESSE 3600
Professor
Sohn
Semester
Winter

Description
GIS Lecture 11 Equal interval classification-note that there are three categories to define classical attributes Random field means each location is XYZ -Field data is treated as a random variable Clustering means to group a dataset into clusters based on their principle, maximizing interclusteral similarity and minimizing interclusteral similarity -ABC is defined according to our parameters -Spatial entities have similar properties and other spatial entitites have nonsimilar properties -Random errors help us analyze similarity or dissimilarity -We can use different classifictation algorithms -The proximity measure measures similairy in Gearys index -There are certain relationships depending on proxminty -Nearest neighbor method involves finding what is the closest -Spatial patterns are related to spatial location -IDW-the weight is the inverse of distance bw red & green -Structural vs geographical matrix -GIS is dependent on a process -The object has to be described. -Attributes help us evaluate the particular object -binary model, regression model -A descriptive model describes existing conditions -prescriptive model is once there is a system, several parameters can be introduced. It is a mathematical system that allows us to predict for example, vegetation maps. The system is built and is good for spatial data modelling. -Resource allocation is a model in which people adopt a stochastic model -Stochastic model helps us to allocate resources -Deductive models are top down models. ie you already have the theory and suggest a hypothesis from this. Inductive is the opposite. You want to go from the specific to the general(think deductive and inductive reasoning) -ex: i predict it takes 40 minute
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