Understanding Spatial Data Science
understanding spatial data science
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The first module of "Spatial Data Science and Applications" is entitled "Understanding of Spatial Data Science." This module is composed of four lectures. The first lecture "Introduction to spatial data science" was designed to give learners a solid concept of spatial data science in comparison with science, data science, and spatial data science. For Learner's better understanding, examples of spatial data science problems are also presented. The second, third, and fourth lectures focus on "what is spatial data so important? - unique aspects of spatial data science from three perspectives of business, technology, and data, respectively. In the second lecture, learners will learn five reasons why major IT companies are serious about spatial data, in other words, maps. The third lecture will allow learners to understand four issues of dealing with spatial data, including DBMS problems, topology, spatial indexing, and spatial big data problems. The fourth lecture will allow learners to understand another four issues of spatial data including spatial autocorrelation, map projection, uncertainty, and modifiable areal unit problem.