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
Author: biplovbhandari Page 2 of 6
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
In this tutorial, I will walk through some of the basic steps needed to process the Sentinel-1 SAR data using SNAP. For this tutorial, I am using SNAP version 7.0. You can check the version of the SNAP from Help -> About SNAP…
- If you do not have already, go ahead and download the SNAP
In this tutorial, we will be adding the attribute to the shapefile and updating its value using ArcPy. You need to have ArcGIS installed in order to use ArcPy. This script has been tested with ArcGIS Version 10.6 but should work with most versions.
In this tutorial, we are going to write a simple script to zip your shapefiles so you can upload them to Google Earth Engine (GEE). If you are following along, refer to this post, you can see that GEE takes in certain kind of files in for it to be valid shapefile. Alternatively, you … CONTINUE READING
The Map Projection System used in Nepal is the MUTM (Modified Universal Transverse Mercator). Read more about Map Projection System in Nepal here.
In this exercise, I will be using ArcGIS. Other methods will be posted in the future.
- Load the data in MUTM. If you don’t have data yet, you can download from
Note: This is a very simple method for generating Landcover maps meant for showing the basic workflow for generating Landcover maps. You can use more sophisticated algorithms like … CONTINUE READING
In this exercise, we will try to sample a composite image of the Landsat with the landcover feature collection that we have. The full code can be found here.
The Feature Collection has the following integer assigned for ‘landcover’ column.
0 -> urban
1 -> vegetation
2 -> water
- We will use Landsat.simpleComposite method