ArcGIS Geostatistical Analyst

ArcGIS Geostatistical Analyst lets you generate optimal surfaces from sample data and evaluate predictions for better decision making.

Languages supported: Italian, Portuguese, Russian, Chinese (Simplified), Chinese (Traditional)

9.0/10 (Expert Score) ★★★★★
Product is rated as #11 in category Geology and Seismic Software
Ease of use
8.7
Support
9.0
Ease of Setup
8.0

ArcGIS Geostatistical Analyst is an ArcGIS Pro, ArcMap, and ArcGIS Enterprise extension. It is not always possible or practical to predict and model spatial phenomena through real-world observations. ArcGIS Geostatistical Analyst includes spatial interpolation methods that let you generate optimal surfaces from sample data and evaluate predictions for better decision-making. This solution is especially helpful for atmospheric data analysis, petroleum and mining exploration, environmental analysis, precision agriculture, and fish and wildlife studies.

ArcGIS Geostatistical Analyst
ArcGIS Geostatistical Analyst

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Customer Reviews

ArcGIS Geostatistical Analyst Reviews

User in Consumer Goods

Advanced user of ArcGIS Geostatistical Analyst
★★★★★
ArcGIS Geostatistical Analyst

What do you like best?

Lots of options to try out when creating predictive maps based on the collected survey data.

What do you dislike?

Took a while to learn all the different functions and what you can do with it. Had to do a lot of reading up on the different types of analysis to know which one was right for each circumstance of mapping.

Recommendations to others considering the product:

Great for mapping, does take a little while to get the hang of all the different types of statistical analysis that you can do with it. I had very little statistical learning prior to using Geostatistical Analyst, but was able to read up on the different types and use appropriatly for each type of mapping situation.

What problems are you solving with the product? What benefits have you realized?

I use the tool for predictive mapping the data we collect through surveys. Data will be point features specific, and we are trying to map as a continuous predictive shift of likelihood over the selected area of interest.

Review source: G2.com

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