Table of contents

1. Introduction and advantages of GEE platform

Google Earth Engine is a cloud-computing platform for satellite imagery and other Earth observation data. Google Earth Engine combines petabyte-scale catalogs of satellite imagery and geospatial datasets with planetary-level analysis capabilities. Scientists, researchers, and developers use Earth Engine to detect changes in the Earth's surface, map trends, and quantify differences. Earth Engine is now available for commercial use and remains free for academic and research use. It mainly has the following advantages:

1) Free for non-commercial users

2) Large amount of basic data

3) Strong background processing ability

4) Complete ecological development environment

2. Introduction to GEE infrastructure

2.1 GEE Technical Architecture

GEE is mainly divided into four parts in terms of technical architecture:

1) Front-end call service

Including GEE's own web-side code editor (Code Editor) and its third-party Web Apps applications.

2) API library

GEE provides JavaScript API and Python API for users to edit and develop to complete the functions required by users.

3) Background computing server

It is divided into two types: real-time computing server (synchronous) and asynchronous computing server. The real-time calculation server is responsible for interpreting the content written by the user, and outputting and displaying the calculation results in real time; the asynchronous server is mainly responsible for exporting task calculations (tasks), etc.

4) Data storage server

It mainly includes image pyramid (slice/tile) service and its own data storage service, providing users with all kinds of image and vector data needed for analyzing applications, and users can also upload the required resources to Assets by uploading resources. use.

2.2 GEE Operating Architecture

The application processing flow of the GEE platform is shown above. At present, the processing and analysis of spatial data such as image data or vectors are mainly performed by editing codes. The user edits the code, calls the corresponding API interface, and sends the task to the background, and the background performs corresponding analysis according to the code logic, and distributes the task to different servers for processing.

In the real-time calculation task (synchronous task), the background receives the processing result, returns the calculation result to the map interface on the web side for display, and outputs the operation result required by the user in the console.

In the asynchronous computing task, the background will generate related export tasks according to the logic, execute them asynchronously in the background until the export task is completed, and store the exported resources in the defined path or resource library.