geeviz 2026.5.1

A package to help with GEE data processing, analysis, and visualization

geeViz

The Earth Engine Visualization Toolkit for Python

Docs Google Earth Engine

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geeViz makes exploring, visualizing, and analyzing Earth Engine data and geospatial imagery easy in Python. Whether you’re an analyst, scientist, or just getting started, geeViz offers interactive mapping, time series, and advanced charting—without the JavaScript overhead.

Developed by RedCastle Resources, geeViz features a powerful, customizable map viewer and Pythonic interfaces for working with Google Earth Engine (GEE).

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Key Features

• Interactive Map Viewer (launches in your browser)
• Layer toggling, opacity, visualization tools, querying, & area charting
• Dynamic time-lapse creation from GEE ImageCollections
• Built-in charting & analysis tools (point/polygon, time series, area stats)
• Inline zonal summary & charting (geeViz.outputLib.charts, formerly geeViz.chartingLib) — run zonal stats and produce Plotly charts (time series, bar, grouped bar, donut, scatter, per-feature time series subplots, Sankey) directly in notebooks
• Summary area retrieval (geeViz.getSummaryAreasLib) — 15 functions returning filtered ee.FeatureCollection objects for political boundaries, USFS units, census geographies, buildings, roads, and protected areas
• Jupyter/Colab support and standalone scripting
• Supports Landsat, Sentinel-2, MODIS, LCMS, LCMAP, and more
• Extensive examples and ready-to-run wrappers
• Built-in MCP server for AI coding assistants (Cursor, Claude Code, VS Code Github Copilot, Windsurf, AntiGravity, etc...)

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Quick Links

• PyPI: pypi.org/project/geeViz
• Docs/Home: geeviz.org
• Notebooks & Scripts: examples/
• Community Repo: github.com/gee-community/geeViz
• Forest Service GitHub: code.fs.usda.gov/forest-service/geeViz

JavaScript Version & Related Links

• GEE Playground Module
• JS Modules on GitHub
• Forest Service JS Repo

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Documentation & Help

• geeViz Documentation and API Reference
• See examples/ for Jupyter/Colab notebooks and scripts.
• Need help? Email us at [e-mail].

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Installation

The fastest way to get started:

1. Sign up for Google Earth Engine
2. Install geeViz via pip:

   pip install geeViz
   

3. Authenticate your Google account with Earth Engine:

   earthengine authenticate
   

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Manual / Advanced Installation

1. Install the Earth Engine Python API if not present:

   pip install earthengine-api
   

2. Clone this repository:

   git clone https://github.com/gee-community/geeViz
   

3. Optionally, add or symlink the geeViz folder to your Python site-packages.

4. To update to the latest version:

   pip install geeViz --upgrade
   

   or, if installed via Git:

   git pull origin master
   

geeViz is also mirrored at code.fs.usda.gov/forest-service/geeViz.

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Optional: API Keys for Google Maps & Gemini

Some geeViz features (googleMapsLib, outputLib.reports LLM narratives) require API keys from Google Cloud. These are optional — core GEE functionality works without them.

Gemini API Key (for AI-generated report narratives and image interpretation):

1. Go to Google AI Studio
2. Click Create API Key → select a project → copy the key

Google Maps Platform API Key (for geocoding, Street View, places, elevation, air quality, solar):

1. Go to Google Cloud Console → select/create a project
2. Navigate to APIs & Services → Credentials → Create Credentials → API Key
3. (Recommended) Restrict the key to: Geocoding, Street View Static, Places (New), Elevation, Air Quality, Solar, Roads, Maps Static

Store your keys in a .env file in your geeViz package directory (alongside geeView.py):

# .env file in your geeViz package directory
GEMINI_API_KEY=your_gemini_api_key_here
GOOGLE_MAPS_PLATFORM_API_KEY=your_maps_platform_key_here

You can also set these as environment variables. The .env file is loaded automatically by googleMapsLib and outputLib.reports on import.

Key	Used by	How to get
GEMINI_API_KEY	googleMapsLib.interpret_image(), googleMapsLib.label_streetview(), outputLib.reports LLM narratives	Google AI Studio
GOOGLE_MAPS_PLATFORM_API_KEY	googleMapsLib.geocode(), streetview_*(), search_places(), get_elevation(), get_air_quality(), get_solar_insights(), etc.	Google Cloud Console

Optional pip extras:

pip install geeViz[gemini]         # Adds google-genai for AI features
pip install geeViz[segmentation]   # Adds torch + transformers for SegFormer
pip install geeViz[all]            # Everything

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AI-Assisted Development (MCP)

geeViz includes a built-in MCP (Model Context Protocol) server with 21 tools that give AI coding assistants live access to geeViz and Google Earth Engine. Instead of generating code from training data (which is often wrong or outdated), your AI assistant can look up real function signatures, read actual example scripts, execute and test code, inspect assets, export data, manage tasks, and more.

Works with Cursor, Claude Code, VS Code with GitHub Copilot, Windsurf, and any MCP-compatible client. The mcp SDK is included as a dependency — no extra install needed.

Quick setup

1. Add a config file for your editor (see MCP Server docs):

   {
     "mcpServers": {
       "geeviz": {
         "command": "python",
         "args": ["-m", "geeViz.mcp.server"]
       }
     }
   }
   

2. Copy the agent instructions from geeViz/mcp/agent-instructions.md into your editor's instructions file (.github/copilot-instructions.md, .cursorrules, CLAUDE.md, or .windsurfrules).

What the MCP server can do

The 21 tools are organized into categories:

Category	Tools
Code Execution	run_code — persistent REPL with ee, Map, gv, gil, sal, tl, rl, cl pre-loaded; save_session — export as .py or .ipynb
API Introspection	get_api_reference — function signatures & docstrings; search_functions — search across all modules; examples — list/read example scripts; get_reference_data — lookup reference dicts
Dataset Discovery	search_datasets — keyword search across official & community catalogs
Asset Inspection	inspect_asset — bands, CRS, scale, date range, properties; list_assets — browse GEE folders
Map Control	map_control — view, list layers, or clear the interactive map
Exports	export_image — export to asset, Drive, or Cloud Storage
Task/Asset Management	track_tasks, cancel_tasks, manage_asset (delete/copy/move/create/update ACL)
Google Maps	get_streetview — Street View imagery; search_places — places/geocoding
Reports	create_report, add_report_section, generate_report, get_report_status, clear_report
Environment	env_info — versions, namespace, project info

Charting (cl.summarize_and_chart()), thumbnails (tl.generate_thumbs()), EDW queries (edwLib), and geocoding (gm.geocode()) are accessed via run_code for maximum flexibility.

For the complete tool reference, architecture details, and usage examples, see the MCP Server README and the online MCP Server guide.

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Getting Started

geeViz comes with ready-to-run examples and templates for fast onboarding.

Example: Launch in Python Authenticate and then try: from geeViz.examples import geeViewExample Explore other examples: from geeViz.examples import timeLapseExample from geeViz.examples import getLandsatWrapper from geeViz.examples import getSentinel2Wrapper from geeViz.examples import getCombinedLandsatSentinel2Wrapper from geeViz.examples import harmonicRegressionWrapper from geeViz.examples import LANDTRENDRWrapper from geeViz.examples import LANDTRENDRViz from geeViz.examples import CCDCViz from geeViz.examples import lcmsViewerExample from geeViz.examples import LCMAP_and_LCMS_Viewer from geeViz.examples import phEEnoVizWrapper from geeViz.examples import GFSTimeLapse

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Use with Jupyter & Colab

• Interactive notebooks are in the examples/ directory (see docs ➔).
• The geeViz map viewer also works directly inside Jupyter and Google Colab.

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Features at a Glance

• One line mapping: Map any GEE image or collection instantly
• Interactive: Toggle layers, set opacity, area/point query, and chart
• Dynamic Time-Lapses: Animate temporal stacks and export GIFs
• No JavaScript required: Pure Python interface

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Contributing

We love contributions and new users!

• Share a GEE script, notebook, or suggestion?
  [e-mail]
• Pull requests & feature requests:
  github.com/gee-community/geeViz

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License

geeViz is released under the Apache 2.0 License.
See the LICENSE file for details.