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Geodata Pixel Documentation pixel_logopixel_logo

Welcome to the comprehensive documentation for Geodata Pixel. This documentation covers both the browser-based application and the Python client library, providing you with all the information you need to effectively use the Geodata Pixel platform.

About Geodata Pixel

Geodata Pixel is a cloud-based platform for managing, processing, and publishing geospatial imagery and raster data. The platform provides:

  • A web interface for efficient image management
  • A Python client library for programmatic access
  • API endpoints for integration with other systems

The web interface is available at:

https://geodatapixel.no/{tenant}

Where {tenant} is your organization's tenant ID. Contact your administrator for your specific tenant URL.

Documentation Overview

News & Updates

Stay informed about the latest developments with our News Feed, which includes:

  • Announcements of new features
  • Important updates and changes
  • Latest developments

For a complete history of changes, check out our Changelog.

User Manual for Browser Application

The User Manual provides comprehensive guidance for using the Geodata Pixel browser application, including:

  • Creating and managing projects
  • Uploading and organizing images
  • Working with image series
  • Managing user access and permissions
  • Setting up and publishing services
  • Integration with Esri products

Python Client Library

The Python client library allows you to interact with the Geodata Pixel API programmatically:

  • Installation Guide - How to install the Pixel client library
  • Getting Started - Get up and running quickly with basic examples
  • Examples - Detailed examples of using the client library for various tasks
  • Changelog - History of changes and updates to the Python client library

Key Features

Browser Application

  • Common place to upload, store, and structure image data
  • Easy image discovery based on time and place
  • Sharing mechanisms based on ArcGIS
  • Safe storage with anonymization for sensitive data
  • Automatic tagging using machine learning

Python Client Library

  • Create and manage projects and data collections
  • Upload and manage image and raster data
  • Optimize rasters for better performance
  • Create and manage ArcGIS services
  • Attach files to projects and data collections
  • Retrieve and filter data with pagination support

API Reference

Examples

The documentation includes various code snippets demonstrating common tasks with the Python client: