GISBox

Google Earth Engine (GEE)

GISBox is a one-stop 3D GIS data editing, conversion and publishing platform that supports editing in multiple GIS formats such as OSGB/GEOTIFF/RVT, converting to 3DTiles/Terrain and publishing.

Introduction

**Google Earth Engine (GEE) **is a cloud-based geospatial analysis platform provided by Google, which can use earth observation data for large-scale analysis and visualization. Its feature is that it can efficiently and quickly process large-capacity, multi-dimensional information such as remote sensing images, geospatial data, and climate data in the cloud. Users can access rich archival resources from major satellite data providers such as NASA, USGS, and ESA for free, and write scripts using programming languages (JavaScript or Python), which are widely used in many fields such as surface change analysis, climate modeling, agricultural monitoring, and forest management.

Data Format Overview

  1. GeoTIFF: A raster data format containing spatial reference information, widely used in remote sensing images and surface analysis.
  2. NetCDF: A multidimensional time-space format suitable for scientific data such as climate and ocean.
  3. Shapefile (.shp): A mainstream vector data format that can handle surface, line, and point data such as administrative divisions and land use.
  4. CSV (with geographic information): Attribute data containing latitude and longitude coordinates, often used for lightweight location analysis or data merging.
  5. JSON/GeoJSON: A lightweight, flexible vector format suitable for WebGIS development and API docking.
  6. KML/KMZ: Highly compatible with Google Earth, suitable for map visualization and sharing.

Pros

  1. **Rich database: **Decades of remote sensing data from Landsat, Sentinel, MODIS, etc. are available for free.
  2. Powerful cloud processing capabilities: Large-scale analysis tasks that cannot be completed by local computing can be run at high speed on Google’s servers.
  3. **Browser-based: **No software installation is required, and online visualization and analysis can be performed directly.
  4. **Support script automation: **JavaScript or Python can be used to automate batch analysis processes.
  5. **Free for research and education: **Most functions are free to use in non-commercial situations.

Cons

  1. **You need to master the programming interface: **You need to have basic programming knowledge of JavaScript or Python.
  2. **You must be connected to the Internet: **Since the platform is completely cloud-based, it relies on a stable network connection.
  3. **There are certain limitations on local data integration: **The format and file size of uploaded data are subject to certain restrictions.
  4. **Commercial use is restricted: **If you need to use it for full commercial purposes, you may need to sign a licensing agreement with Google.

Application Scenario

Google Earth Engine has demonstrated strong capabilities in many geospatial-related fields. With its access to massive remote sensing data and high-speed computing performance in the cloud, GEE is widely used in deforestation monitoring, agricultural assessment, urban expansion analysis, climate change research, and disaster risk management.

Example

  1. Use the JavaScript web interface of Google Earth Engine.

  1. Use Python to call GEE and draw the specified area on the map.

Related GIS Services

Web Coverage Service (WCS)

Web Feature Service(WFS)

Web Map Tile Service (WMTS)

Tile Map Service (TMS)

References

  1. https://earthengine.google.com/
  2. https://www.google.com/earth/outreach/learn/introduction-to-google-earth-engine/
  3. https://sanborn.com/blog/google-earth-engine-frequently-asked-questions/