How Can Spatial Data Science Methods Help To Analyze Space?

Analyzing Space - Spatial Data Science Methods

Presented By ODSC West'18
ODSC West'18
ODSC West'18

Presentation Description

Spatial data science uses many of the same techniques and algorithm as traditional data science, but the spatial component can add a large amount of additional information by combining with other sources at the same location (e.g., census, geolocated tweets), using real-time routing services, or using the spatial structure of the distribution of the data. In this talk, I will highlight the work we have done in linear optimization, genetic algorithms, and constraint-based clustering that take special advantage of the spatial part of the data. For example, using the Python package CVXOPT, we solved a linear optimization problem that optimally distributes an asset from a source to a drain according to the road network and constraints that the drains cannot be over capacity, occasionally have fixed assignments, and all the asset has to be moved.

Presentation Curriculum

Analyzing Space - Spatial Data Science Methods
40:16
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