09-11, 14:00–14:30 (America/Chicago), Grand G
This presentation will highlight the key features of the leafmap Python package for interactive visualization and analysis of geospatial data with minimal coding in a Jupyter environment.
Geospatial data visualization is essential for understanding and analyzing geographic information. While numerous Python packages exist for visualizing geospatial data, few offer interactive capabilities within the Jupyter environment. This poses a challenge, particularly for novice users with limited coding skills, as loading and displaying geospatial data on an interactive map requires writing extensive code. However, Leafmap, an open-source Python package, addresses this issue by enabling interactive mapping and geospatial analysis with minimal coding in Jupyter notebooks. In this presentation, we will showcase the powerful interactive functionalities of Leafmap for visualizing geospatial data. Attendees will learn how Leafmap simplifies the process of loading and displaying various file formats, including local vector and raster datasets, LiDAR data, Cloud Optimized GeoTIFF (COG), and SpatioTemporal Asset Catalog (STAC). Moreover, we will demonstrate additional interactive features provided by Leafmap, such as the interactive pixel inspector, time slider, and open data search. By the end of this presentation, attendees will have a comprehensive understanding of the capabilities of Leafmap and will be empowered to leverage interactive mapping and geospatial analysis with ease, even with limited coding experience.
