Spatial Data Mining I: Essentials of Cluster Analysis

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Whenever we look at a map, it is natural for us to organize, group, differentiate, and cluster what we see to help us make better sense of it. This session will explore the powerful Spatial Statistics techniques designed to do just that: Hot Spot Analysis and Cluster and Outlier Analysis. We will demonstrate how these techniques work and how they can be used to identify significant patterns in our data. We will explore the different questions that each tool can answer, best practices for running the tools, and strategies for interpreting and sharing results. This comprehensive introduction to cluster analysis will prepare you with the knowledge necessary to turn your spatial data into useful information for better decision making.

[@219parrot]

This is so helpful! Thank you so much for your detailed and clear explanation/guide to performing a Hot spot analysis

[@renatohingel1376]

Ótima explicação. Bastante didática e com muito exemplos. Parabéns e obrigado pela disponibilização

[@andikahadi7023]

they really deliver the presentation thorough but also fun and casual (Y)

[@johng5295]

Thanks in a million. Great content. Awesome. Very well explained. I couldn't find this explanation--simply put anywhere else. Great teachers are hard to find. Grade: A++💥

[@DjimeDourado]

Amazing explanation, congratulation!

[@brianac7273]

This was incredibly helpful. Thank you for sharing!

[@Ryan125y]

Thank you for adding the big "easy" button, defaults are great

[@shanthidhivya9678]

It's really a very good presentation 👍

[@prabeshshrestha145]

very helpful! thanks!

[@Imrans_Chronicles]

The presentation is so overwhelming in terms of the quality of the content. Thank You.

[@jorgekramer1264]

Excellent presentation, very well rounded.

[@RomuloMagalhaesAutoTOPO]

Great, thanks.

[@ewanharris5433]

This is absolutely brilliant - Pity the software is so expensive esp with exchange rates - SA

[@aben8763]

you can always get the trial version,

[@peterj9351]

Use R and/or QGIS. Problem solved!

[@ewanharris5433]

@@peterj9351
Thx Petr Will try R in combination

[@isaaclopezmorenoflores1688]

Very good video!

[@tawilk]

how do you get a census tract map without the population "black plots" already on it? I can only find maps that have population concentrations attached. trying to overlay information on top of these plots does not look good and is hard to read.

[@charaznable1114]

I didn’t like heat map either until watched this video, thanks

[@vilecypher]

I can totally relate how classifying data into natural breaks and quantiles affects my research hahaha

[@arybekham232]

hi how can i learn the math steps of Getis ord Gi* how it works in optimized hot spot analysis
I have been applied on the crimes

[@mohammadjahidulislamtushar9214]

is the hotspot or Cluster and Outlier can be applicable in environment behavioral pattern change?
For example, multitemporal land-use change and the changing pattern could be B-B-S-S-S-S.. this means if one polygon feature contains Barrend land at the initial stage and the next decade it will remain Bareen land but in the 3rd decade it will change in Settlement..thus the other decades change pattern will be...

[@allanaudsley6447]

Can anyone explain to me why the tool specifies the percentage of features that have less than 8 neighbours based on the distance band? What is the justification for 8 neighbours? Thanks.

[@rumanzihypolite4663]

i didn't get the difference between distance band and cell size. Can anyone explain to me?

[@s.n.g.888]

Business model is a con.👎