📄️ 7.1 Introduction to Geospatial Health Data
This chapter introduces Geospatial Health Data, explaining its significance in uncovering spatial trends in health outcomes. It covers the types of geospatial health data, GIS tools, spatial analysis techniques, visualization methods, and ethical considerations. The case study illustrates the application of geospatial health data analysis in disease outbreak mapping, emphasizing the role of this approach in public health interventions.
📄️ 7.2 Working with Geospatial Data in Python
This section discusses the Python libraries essential for working with geospatial data, covering loading, geometric operations, visualization, spatial analysis, geocoding, and accessing geospatial APIs. It emphasizes the practical applications of these libraries in a case study involving disease spread analysis. The challenges and considerations associated with geospatial data are also addressed.
📄️ 7.3 Visualizing Geospatial Health Data
This section discusses geospatial visualization tools and techniques, including choropleth maps, heatmaps, point maps, line maps, and animation. It provides a case study on visualizing disease spread and emphasizes the importance of effective communication and addressing challenges when working with geospatial health data.
📄️ Resources
- Geopandas for Health Analytics