Unsupervised Landcover Classification In SNAP Using Sentinel 1 Imagery
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Contents
Introduction
- Synthetic Aperture Radar, or SAR, is a method of RADAR imaging that propagates a microwave signal to create an image over an area. The image is generates based on the type of backscatter that occurs when the signal
hits a target. Unlike optical remote sensing, SAR is not affected by clouds or time of day; however, it can be adversely affected by heavy precipitation. This tutorial will use SAR data and image processing software to classify a RADAR image using an unsupervised classification method.
Unsupervised Classification
Software and Computer Requirements
http://step.esa.int/main/download/snap-download/previous-versions/
- SNAP 7.0 has a bug in the software that effects a component of classification; therefore SNAP 6.0 should be used.
The European Space Agency recommends SNAP be run on computers with at least 4GB of memory; however, for the classification, 16 GB would be preferred.
