Call/WhatsApp: +1 914 416 5343

Data visualization, Spatial/Geospatial Data Visualization

Read the posted slides of Chapters 5 and 6 of the optional textbook – Interactive Data Visualization: Foundations, Techniques, and Applications: of Chapter 5 – Visualization Techniques for Spatial Data of Chapter 6 – Visualization Techniques for Geospatial Data  Identify two geospatial datasets (the two datasets should use different geographic maps in visualization. For example, one dataset uses a city map, and the other dataset uses a country map) and one spatial dataset (e.g., medical imaging, flow data, point cloud, or other scientific computational simulation or modeling data).  Use Python or R to visualize data in each dataset and explore trends/patterns. When you do visualization of your datasets, try different spatial/geospatial data visualization techniques for different datasets. Your work will be graded based on the variety and quality of the generated visualization. Prepare a report (in Word or PDF format) in which you describe the identified datasets. For each data dataset, 1. Explain the dataset type (whether the dataset is in the form of a table, network, tree, field, geometry, cluster, set, or list – see textbook Section 2.4, Page 24). 2. Explain data types (whether the data in the dataset is in the form of items, attributes, links, positions, or grids – see textbook Section 2.3, Page 23). 3. Explain the number of attributes/dimensions, the attribute types and semantics of the data (i.e., the real-world meaning of the data, see textbook Sections 2.5-2.6, Page 31).4. Include into the report the visualization figures of the data and your best explanation of trends/patterns/outliers discovered through data visualization.