Affiliation:
1. Bule Hora University, Ethiopia
2. Space Science and Geospatial Institute, Ethiopia
3. Samarkand International University of Technology, Uzbekistan
Abstract
This chapter aims to explore the power of Python in spatial data visualization. Spatial data visualization is the process of representing spatial information visually, enabling one to explore and communicate patterns, distributions, and relationships within the data. An informative spatial data visualization with Python effectively represents and communicates spatial information using visual elements, enabling users to gain insights and make informed decisions related to geospatial data. Python provides many sets of libraries and tools for handling and visualizing geospatial data to enhance understanding, facilitate exploration, and present geographic patterns and relationships clearly and intuitively. The chapter demonstrates the capabilities of Python for spatial data visualization by showcasing various techniques, spatial data formats, and tools with Geopandas, Matplotlib, Plotly, and Folium libraries. Examples and code snippets are provided for the readers to gain solid knowledge about spatial data visualization using Python.
Reference12 articles.
1. GeoDa: An Introduction to Spatial Data Analysis
2. Introduction to computers and their development
3. Coppock, J. T., Grelot, J. ., Yuju, H., Kanakubo, T., Morrison, J. L., & Rystedt, B. (1994). Thematic Mapping from Satellite Imagery Visualization in Modern Cartography.
4. The effects of visualization on judgment and decision-making: a systematic literature review
5. Representation and its Relationship with Cartographic Visualization