Processed and exported from Google Earth Engine.
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Let’s use Google Earth Engine and satellite data to visualize the time-series of the Amazon Fires 2019. In this post, I will be using FIRMS (Fire Information for Resource Management System). FIRMS disseminates Near-Real-Time active fire from the NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) satellite. This data … CONTINUE READING
The back-end on SNAP has been written in Java. But good news to Python enthusiast, they provide Python interface to Java API. It’s through their module called Snappy. In my previous tutorial, I showed you how you can install snappy in your machine and get geared up for the development work. And before we … CONTINUE READING
In this tutorial, we will learn how we can set up a development environment for Snappy. Snappy is the python interface for accessing the JAVA API of SNAP. SNAP can be used to process the Sentinel series of sensors. I prefer to have a separate environment for the Snappy so I can keep it clean … CONTINUE READING
GeoJSON is great! It can be used in the web maps, can be used as a data exchange format especially with Web Feature Service (WFS) and much more. However, sometimes the white space in the GeoJSON file can add up to the size of the file, as a result of which it becomes slower in … CONTINUE READING