(65143))=/ پروژه gis

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شرح پروژه

سلام وقت بخیر

برای یک پروژه دانشجویی gis مزاحمتون شدم

Create a regression model based on the characterises of spatial pattern of vegetation that more effectively explains the variation in temperature.

• Independent variables: 
All from “CA” to “AI” 
• Use “MNF” instead of “ENN_MN” 
• Use “AMF” instead of “ENN_AM” 
• Use “AIF” instead of “AI” 

• Dependent variable: 
Temperature: “MEAM” 

• Spatial weight matrix: Contiguity, 1st order   


Answer the questions below in your report: 
1. Are your samples independent from each other? 
 2. If the answer to the above question is yes: • Run a global spatial regression model and justify your selection regarding the model you chose • Run a local spatial regression model (GWR) ❖ Select variables based on all the following approaches: PCA, forward and backward 
3. Did you observe any difference in the final model in relation to the approach to variable selection? • For each model and variable selection approach: which independent variables did your final model include? Sort them based on their individual importance. 
 4. Which regression model/variable selection approach outperformed? • Were your spatial models able to address the issue of dependency among samples? 
 5. What new insights an be drawn based on a local versus a global regression model? Describe your observations and elaborate on their implications

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