Mo Sarwat – Medium

Mo Sarwat

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Processing Spatial Raster Data in Apache Sedona

Raster data is a type of geospatial data representation of the Earth’s surface and atmosphere from a distance, typically using satellite or…

Aug 3, 2023

Processing Spatial Raster Data in Apache Sedona

Aug 3, 2023

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Apache Sedona Frequently Asked Questions (FAQ)

Apache Sedona is a distributed spatial analytics platform that provides tools for working with geospatial data in a distributed computing…

Dec 8, 2022

Apache Sedona Frequently Asked Questions (FAQ)

Dec 8, 2022

H3 Spatial Grid Support in Apache Sedona

Uber H3 is a technique to model and index and geospatial data. H3 grids the earth surface by casting it on a icosahedron, and tiles it by…

Oct 16, 2023

H3 Spatial Grid Support in Apache Sedona

Oct 16, 2023

Why you should use WHEROBOTS for your geospatial data processing pipeline?

Today’ s technology allows hundreds of millions of users to frequently use their mobile devices to access their healthcare information and…

Apr 5, 2022

Why you should use WHEROBOTS for your geospatial data processing pipeline?

Apr 5, 2022

Published in
Towards Data Science

GeoSpark stands out for processing geospatial data at Scale

The spatial data deluge

May 12, 2020

GeoSpark stands out for processing geospatial data at Scale

May 12, 2020

Mo Sarwat

Mo Sarwat

Mo is the founder of Wherobots.ai, CS Prof at Arizona State University, & the creator of Apache Sedona (a scalable system for processing big geospatial data)

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