Satellite remote sensing plays an important role in mapping the location and extent of surface water. A variety of approaches are available for mapping surface water, but deep learning approaches are not commonplace as they are ’data hungry’ and require large amounts of computational resources. However, with the availability of various satellite sensors and rapid … CONTINUE READING
Tag: Sentinel-1 Page 1 of 2
Comparing Sentinel-1 Surface Water Mapping Algorithms and Radiometric Terrain Correction Processing in Southeast Asia Utilizing Google Earth Engine
Satellite remote sensing plays an important role in the monitoring of surface water for historical analysis and near-real-time applications. Due to its cloud penetrating capability, many studies have focused on providing efficient and high-quality methods for surface water mapping using Synthetic Aperture Radar (SAR). However, few studies have explored the effects of SAR pre-processing steps … CONTINUE READING
Last week, I was doing some testing using the Python API interface for sentinel-1 toolbox with Snappy and the SNAP desktop to see the time taken by each of them. The workflow for processing the data is described here. The results were astonishing. Each and every steps were significantly slower, especially the co-registration process … CONTINUE READING
In this tutorial, we are going to perform the mosaicing of two adjacent Sentinel-1 scenes using Snappy, the Python interface for SNAP.
If you haven’t, follow along this tutorial to see how you can setup the development environment for SNAP in your machine. To overview, the basic steps that we cover in this tutorial are:… 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