ArcGis map Implementation with Artificial Intelligence

Posted By :Shubham Sharma |27th November 2020

What is ArcGis?


Arcgis is a platform that provides an organization or a creator to create a map, share, and create clustering analysis. It can be used on a mobile, desktop, or as a developer tool.


In Acrgis we can import data in various ways.


1. CSV, GEOJSON, GEOLOCATION:- These files can be uploaded from your system.
2. URL:- We can link a layer or a document from the web.
3. An Application:- We can link mobile, web mapping, desktop, or an application.
4. Cloud Drive:- We can upload data from cloud drives as well very easily.

Arcgis allows us to share the created layer with the organization as well as allows us to embed the visuals to a website or either display it publically.


In arcgis, we can create spatial analysis in which can create clusters using the location data. Arcgis also allows us to create maps based on address or postcode. In Arcgis we can create various types of maps (Heat maps, Size, and many more).


Artificial Intelligence in Arcgis


In Arcgis we can use spatial analysis which is used for creating clusters in the map using location data. In this we can perform multiple analysis:-


1. Calculate Density.
2. Find HotSpots.
3. Outliers.
4. Point Clusters.
5. Interpolate points.


It can also perform other tasks as well based on points we can plan routes, find the nearest location and many more things. Arcgis uses deep learning for plotting and creating spatial analysis. Using deep learning can easily detect the object and create a map according to them. We can also use Phyton to create a model and implement on the Arcgis for plotting a heatmap or a sized based map.



Arcgis is a great tool for mapping data and location for creating hotspots or maps based on size. It can create a cluster using HDBSCAN clustering or find outlier which can make data more useful. It also can be used with deep learning for finding routes or nearest locations.

About Author

Shubham Sharma

Shubham Sharma is an accomplished backend developer with expertise in Node.js. He has a strong command over various cutting-edge technologies such as Node.js, JavaScript/ES6, Express.js, Elasticsearch/OpenSearch, MongoDB, HTML/CSS, Quicksight, AWS and Git. Shubham's extensive experience has enabled him to successfully deliver numerous internal and client projects, including Wellsite, Virgin Media, Mason, and Konfer. He also has his skills in creating visuals using MongoDB and has created visuals for Konfer and Mason, demonstrating his proficiency in queries and DAX operations. With his strong technical background and ability to deliver high-quality solutions.

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