Introduction
Contents
Introduction¶
What this Jupyter Book is about¶
This Jupyter Book is an introduction to the use of the Google Earth Engine’s Python SDK to visualise and analyse satellite imagery such as those from NASA and the European Space Agency satellites. Each chapter provides code samples to demonstrate how to use the Google Earth Engine API to create and manipulate maps for geospatial analysis. These include simple explanations to the concepts around remote sensing, the satellite image dataset, and/or about the python code.
My aim is to provide a top-down approach to learning this topic — by hands-on code samples that programmers can try out themselves. The code is then supplemented by the concepts (rather than “bottom-up” method of starting from the very basics of geographic shapes then gradually moving to more complex concepts). There’s a bit of introduction to Google Earth Engine to set the minimal conceptual foundations, but the rest of the chapters are led by code to get your started. I believe that a top-down approach delivers much quicker results, especially for professionals who do not have the luxury of taking on months or years of courses. And, most especially, for a topic that naturally leans towards visualising the planet, it seems much more proper to produce visual results right away so that first-timers in this field can appreciate the very essence of looking at the earth from the perspective of satellites.