Spatial data science is a new field that allows us to explore the world using geography, earth sciences, and cartography. Spatial data science is described as combining the best aspects of ‘big data’ and geographic information systems (GIS). From the proliferation of smartphones to increasingly connected commercial and industrial facilities to the constant explosion in sensor technologies, we are presented with new datasets that require analysis at every turn. This article presents a basic overview of spatial data science and practical techniques you can use today when working with spatial data. To begin with, it’s important to understand the basics of spatial data science. Let’s go ahead.  What is spatial data science? Spatial data science uses spatial analysis to gain insight into geographical data. Spatial analysis involves using mathematical algorithms, statistical models, and other methods to extract information from large amounts of complex data. Spatial data science can also be used to analyze geographic information systems (GIS) maps for their ability to show changes over time or connect different objects together. The main advantage of geographical information systems (GIS) is the possibility of spatial analysis. Spatial data science is an emerging area in which people are represented and interact with […] read more