I am planning to do a spatiotemporal analysis (2010-2020) of urban heat islands in Metro Manila, Philippines, specifically on how they correlate with factors such as population density, average precipitation, and the prevalence of infectious diseases (e.g. leptospirosis).
I am new to this field of study and the methodology in most papers I have read is highly computational and beyond my comprehension. Can anyone suggest a statistical method I can use to correlate urban heat islands to multiple factors? Also, can anyone suggest an appropriate software I can use to run these analyses?
If you can bring all the information (ie both dependent and independent variables) into one Geographical layer then you can do a spatial regression. You may have to join the map layer that shows the geographical area of interest with tables containing the variables first. GWR, Geographically Weighted Regression has often been used for analyses.
I appreciate your help, Srini and Anna-Maria! I will look into all of these, thanks!
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