3. Use of GEE data

3.1 Introduction

Google Earth Engine is an innovative cloud computing platform for geospatial analysis.Its data types are very different from traditional data types handled by desktop software.In this chapter, we will introduce the basic Earth Engine data types for storing vector and raster data.Then, we'll explore the Earth Engine data catalog and how to interactively search Earth Engine datasets in the Jupyter environment.We will also cover how to obtain image metadata and compute descriptive statistics.Finally, we'll learn how to automatically convert Earth Engine JavaScript to Python.By the end of this chapter, you should have easy access to Earth Engine data using geomaps in the Jupyter environment.

3.2 Technical Requirements

To study this chapter, you will need to install geemap and several optional dependencies.If you've followed Chapter 1 - Introducing GEE and Geemap, you should already have a conda environment with the necessary packages installed.Otherwise, you need to create a new conda environment and install the pygis package using the following command, which will automatically install geemapand all necessary dependencies:

conda create -n gee pythonconda activate geeconda install -c conda-forge mambamamba install -c conda-forge pygis<