opengeos/leafmap

Features

• Interactive Map Generations - Generates interactive maps from Python data structures for seamless display in notebooks and web pages.
• Geospatial Visualizations - Provides a comprehensive framework for mapping and visualizing data based on geographic coordinates and spatial relationships.
• Remote Sensing Machine Learning - Integrates deep learning frameworks to process, classify, and analyze satellite and aerial imagery.
• Satellite Imagery Classification - Implements machine learning techniques for categorizing features and segmenting satellite imagery.
• COG Tile Rendering - Renders Cloud Optimized GeoTIFFs as tile layers from remote endpoints with custom band and color settings.
• Geospatial Catalogs - Enables searching and discovering specific geospatial items within STAC catalogs using spatial and temporal filters.
• Geospatial Data Catalogs - Provides tools to search remote registries and access geospatial datasets from cloud providers and public archives.
• Basemap Integrations - Integrates background map layers using predefined providers or custom tile URLs for geographic context.
• Mapping Engine Abstractions - Implements a backend-agnostic rendering system to switch between different mapping engines via a consistent API.
• Slippy Map Vector Renderers - Renders geospatial vector data from data frames or JSON files with interactive tooltips.
• Raster Layer Visualizers - Displays local or Cloud Optimized GeoTIFFs with configurable bands, colormaps, and value ranges.
• STAC Item Visualizers - Displays multiple geospatial items from a STAC data catalog on an interactive map.
• STAC Layer Visualizers - Visualizes SpatioTemporal Asset Catalog items as tile layers via remote endpoints.
• Tiled Image Loading - Implements efficient loading of Cloud Optimized GeoTIFFs by fetching only necessary image chunks from remote servers.
• Raster Imagery Renderers - Renders Cloud Optimized GeoTIFFs as interactive raster tile layers with custom band and color settings.
• Notebook Map Embeds - Embeds interactive map components directly into Jupyter notebook cells for real-time visualization.
• Python Geospatial Visualization Libraries - A Python library for creating interactive maps and performing geospatial analysis with minimal code in Jupyter environments.
• Interactive Map Components - Provides UI components for rendering geographical map views, including thematic maps and split-panel comparative views.
• Spatial Databases - Integrates with PostGIS databases to retrieve and display spatial data directly on interactive maps.
• Geographic Map Visualizations - Generates choropleth and heat maps to visualize data values and density across geographic areas.
• Pixel-Level Spatial Analysis - Allows interactive probing of RGB and data pixel values in raster datasets at specific scales.
• Map View Exports - Saves the current map state as a standalone HTML file or returns the HTML content as a string.
• Database Connectors - Connects PostGIS databases to retrieve and render spatial data directly onto interactive maps.
• Geospatial Feature Retrieval - Retrieves building and place data from mapping providers for specified bounding boxes.
• Remote Imagery Retrieval - Fetches agriculture imagery data for specific bounding boxes and years from remote data catalogs.
• STAC Asset Fetchers - Fetches specific bands or all assets from catalog items using parallel downloads and multi-band merging.
• Visualization Engine Configurations - Allows users to switch between different rendering engines to change visualization styles and available capabilities.
• Data-Driven Color Mappings - Transforms numeric or categorical data into colors using continuous or categorical colormaps.
• Geospatial Feature Editing - Provides interactive tools for modifying geospatial geometries and drawing points, lines, and polygons on maps.
• Geospatial Layer Management - Allows interactive switching of basemaps and overlaying of geospatial data from tile and vector services.
• Geospatial Tile Layer Integration - Creates bitmap layers from specific tile URLs with adjustable opacity and visibility settings.
• Comparative Map Layouts - Provides split-panel and linked map views for side-by-side comparison of different geospatial datasets.
• Cross-Library Layer Mapping - Translates geospatial data formats into compatible layer definitions for multiple different JavaScript mapping libraries.
• Raster-Vector Hybrid Pipelines - Combines diverse geospatial data sources like GeoJSON and GeoTIFFs into a single unified map coordinate system.
• Map Legend Styling - Creates custom legends and colorbars to represent data values with specific colors and labels.
• Temporal Animation Engines - Implements engines for playing back time-series geospatial data with adjustable speeds and rolling windows.
• Map View Synchronizations - Links the state and viewport of separate map instances to enable side-by-side comparative analysis.
• Map Viewport Controllers - Sets the map viewing window to a specific bounding box defined by minimum and maximum coordinates.
• Split-Panel Map Views - Builds split-panel maps for side-by-side comparison or linked maps that synchronize interactions.
• UI Component Embeddings - Displays interactive maps directly within Streamlit web applications as functional UI components.

Star history