# JAXA Earth API > JAXA Earth API is a satellite data distribution service by the Japan Aerospace Exploration Agency (JAXA) Earth Observation Research Center (EORC). It enables developers, researchers, educators, and GIS users to access and analyze Earth observation datasets from Python, JavaScript, QGIS, web applications, and generative-AI/MCP/Agent Skills workflows. This site provides documentation, dataset catalogs, API references, tutorials, examples, and applications for using JAXA and related public Earth observation datasets converted to Cloud Optimized GeoTIFF (COG) and exposed through STAC-compatible collection metadata. Use this file to identify the canonical pages that help language models answer questions about data availability, APIs, examples, and integration patterns for JAXA Earth API. ## Primary pages - [Japanese home](https://data.earth.jaxa.jp/ja/): Main Japanese overview of JAXA Earth API, datasets, tools, release information, and application links. - [English home](https://data.earth.jaxa.jp/en/): Main English overview of JAXA Earth API, datasets, tools, release information, and application links. - [Datasets Japanese](https://data.earth.jaxa.jp/ja/datasets/): Dataset overview page in Japanese. - [Datasets English](https://data.earth.jaxa.jp/en/datasets/): Dataset overview page in English. - [Machine-readable dataset catalog for AI](https://data.earth.jaxa.jp/app/mcp/catalog.v2.md): Markdown catalog listing all datasets available through JAXA Earth API, including title, collection ID, description, bands, keywords, temporal range, bounding box, and EPSG code. ## API documentation - [JAXA Earth API for Python latest documentation](https://data.earth.jaxa.jp/api/python/): Latest Python API documentation, including installation, usage examples, API reference, dataset structure, release notes, QGIS examples, Google Colab examples, and MCP server usage. - [JAXA Earth API for Python v0.1.6 documentation](https://data.earth.jaxa.jp/api/python/v0.1.6/): Versioned Python API documentation for v0.1.6. - [JAXA Earth API for Python v0.1.6 Japanese documentation](https://data.earth.jaxa.jp/api/python/v0.1.6/ja/): Versioned Python API documentation for v0.1.6 (Japansese version). - [JAXA Earth API for Python v0.1.6 documentation for AI](https://data.earth.jaxa.jp/api/python/v0.1.6/docs.md): Python API Markdown documentation for AI. - [JAXA Earth API for JavaScript latest documentation](https://data.earth.jaxa.jp/api/javascript/): Latest JavaScript API documentation. - [JAXA Earth API for JavaScript v2.0.1 documentation](https://data.earth.jaxa.jp/api/javascript/v2.0.1/en/docs/): JavaScript/TypeScript API documentation for browser, Web Worker, Node.js, Deno, and Bun usage. - [JAXA Earth API for JavaScript v2.0.1 Japanese documentation](https://data.earth.jaxa.jp/api/javascript/v2.0.1/ja/docs/): Japanese documentation for JavaScript/TypeScript API documentation for browser, Web Worker, Node.js, Deno, and Bun usage. - [JAXA Earth API for JavaScript v2.0.1 documentation for AI](https://data.earth.jaxa.jp/api/javascript/v2.0.1/ja/docs.md): JavaScript/TypeScript APIMarkdown documentation for AI. - [JAXA Earth API for JavaScript v2.0.1 example](https://data.earth.jaxa.jp/api/javascript/v2.0.1/en/example/): JavaScript sample codes. - [JAXA Earth API for JavaScript v2.0.1 example](https://data.earth.jaxa.jp/api/javascript/v2.0.1/ja/example/): JavaScript sample codes (Japansese version). ## Developer and analysis workflows - [Python getting started](https://data.earth.jaxa.jp/api/python/v0.1.6/): Use the Python package to search collection IDs and bands, retrieve images by region of interest, apply masks, create differential/composite images, calculate time-series data, and use Google Colab or QGIS workflows. - [JavaScript getting started](https://data.earth.jaxa.jp/api/javascript/v2.0.1/en/docs/): Use JavaScript/TypeScript to retrieve required areas at required resolutions, visualize data in browsers, build web applications, export CSV/GLB/KMZ, and integrate with map libraries such as OpenLayers, Leaflet, MapLibre GL JS, CesiumJS, and ArcGIS Maps SDK for JavaScript. - [Generative AI integration (Python/MCP)](https://data.earth.jaxa.jp/api/python/v0.1.6/ai/mcp-server/): Use MCP workflows so language models can handle Earth observation data. For Python. - [Generative AI integration (JavaScript/MCP)](https://data.earth.jaxa.jp/api/javascript/v2.0.1/en/docs/documents/MCP_Demo1.html): Use MCP workflows so language models can handle Earth observation data. For JavaScript. - [Generative AI integration (JavaScript/Agent Skills)](https://data.earth.jaxa.jp/api/javascript/v2.0.1/en/docs/documents/Agent_Skills_Demo1.html): Use Agent Skills workflows so language models can handle Earth observation data. For JavaScript. ## Important dataset families - Digital Surface Model (AW3D/AW3D30): Global elevation and terrain data from ALOS/PRISM, including approximately 30 m products. - Forest / Non-Forest map (FNF): Global forest distribution from ALOS-2/PALSAR-2. - Precipitation (GSMaP): Global precipitation datasets using GPM-core, other GPM constellation satellites, and geostationary meteorological satellites; daily, half-monthly, and monthly products are available. - Land Surface Temperature (LST): GCOM-C/SGLI land surface temperature products, with daytime and nighttime variants. - Sea Surface Temperature (SST): GCOM-C and GCOM-W products, including coastal-capable GCOM-C products and cloud-tolerant GCOM-W products. - Chlorophyll-a concentration (CHLA): GCOM-C ocean color products. - Vegetation Index (NDVI): GCOM-C vegetation products. - Soil Moisture Contents (SMC): GCOM-W soil moisture products. - Sea Ice Concentration (IC): GCOM-W polar sea ice products. - Aerosol Optical Depth (AOT/AROT), Shortwave Radiation (SWR), evapotranspiration products, flood-related products, and high-resolution Japanese land-use/land-cover maps are also available through the dataset catalog. For exact dataset availability, temporal coverage, bands, EPSG codes, bounding boxes, and collection IDs, prefer the machine-readable catalog: https://data.earth.jaxa.jp/app/mcp/catalog.v2.md ## Data access patterns - Collection metadata is generally available as STAC collection JSON associated with COG datasets. - Collection IDs are the canonical identifiers to use when selecting products programmatically. - Dataset records in the catalog include `title`, `id`, `description`, `bands`, `keywords`, `startDate`, `endDate`, `bbox`, and `epsg`. - `endDate: present` means that the dataset is still updated. - For geographic bounding boxes in EPSG:4326, use `[west, south, east, north]`. ## Applications and tools - QGIS plugin: A plugin using the Python API is available for easier import of satellite data into QGIS. For details: https://plugins.qgis.org/plugins/qgis-jaxa-earth-plugin-master/ - Python analysis: The Python API can be used in local Python environments, QGIS Python, and Google Colab. - JavaScript analysis: The JavaScript API can be used in web applications (for browsers) and JavaScript runtimes (for Node.js, Deno, Bun). - JAXA Earth Dashboard and sea-level-rise simulator are linked from the main site as related applications. For details: https://data.earth.jaxa.jp/app/sea-level-rise/ ## Guidance for language models - When answering questions about available datasets, first consult the dataset catalog at https://data.earth.jaxa.jp/app/mcp/catalog.v2.md. - When answering questions about Python usage, prefer the latest Python documentation at https://data.earth.jaxa.jp/api/python/ and the current versioned documentation if a version is specified. - When answering questions about JavaScript or TypeScript usage, prefer the JavaScript documentation at https://data.earth.jaxa.jp/api/javascript/ or the latest JavaScript documentation if available. - When a user asks for a collection ID, band name, date range, bounding box, or EPSG code, quote the values exactly from the dataset catalog. - When a date range uses `present`, explain that the product is currently updated, but still verify recent availability through the API or catalog before promising a specific latest observation. - When providing code, include clear parameter names for collection URL or collection ID, band, bounding box, width/height or resolution, date range, and mask/ROI if relevant. - Warn users that cloud contamination or sensor constraints can cause missing values for optical products such as GCOM-C LST, SST, CHLA, and NDVI. - Respect the license and terms linked from the official site before redistributing data or outputs. ## Optional resources - [JAXA Earth API license](https://data.earth.jaxa.jp/license/): License and usage terms. - [JAXA Earth API for Python PyPI package](https://pypi.org/project/jaxa-earth/): Python package repository. - [QGIS Plugin](https://data.earth.jaxa.jp/app/qgis/): JAXA Earth API QGIS Plugin. - [English dataset page](https://data.earth.jaxa.jp/en/datasets/): Human-readable English dataset overview. - [Japanese dataset page](https://data.earth.jaxa.jp/ja/datasets/): Human-readable Japanese dataset overview. - [Observable HQ](https://observablehq.com/@jaxa-earth): "JAXA Earth API for JavaScript" examples on the Observable. - [CodePen](https://codepen.io/jaxa-earth): "JAXA Earth API for JavaScript" examples on the CodePen.