Flood Monitoring Using The Semi-Automatic Classification Plugin

This tutorial describes a method for monitoring floods using SCP and the freely available images acquired by MODIS and Sentinel-2.

Several services provide global monitoring of floods. For instance, the near real-time Global Flood Mapping provided by the NASA Goddard’s Office of Applied Science. This services apply a water detection algorithm to MODIS images, as described at this link . You can find an example of produced map here .

Of course, the educational purpose of this tutorial is to monitor flooded areas in a semi-automatic way, exploiting the characteristics of satellite images that can be downloaded with SCP. In particular, MODIS Products allow for the daily monitoring of floods, and the other satellite images (Landsat, Sentinel-2, and ASTER) have higher spatial resolution allowing for more local studies.

In this tutorial we are going to study the severe flooding occurred in the Ganges in August 2016, caused by monsoon rains. For more details, please read this informative page by NASA Earth Observatory.

Webinar by NASA ARSET on Land Cover Classification with Satellite Imagery

NASA ARSET (Applied Remote Sensing Training) is a program for fostering the acquisition and use of NASA satellite data for supporting decisions, through online webinars and in-person workshops.
In particular, free webinars are available in the following areas: Disasters, Health & Air Quality, Land, Water Resources, and Wildfires.

The upcoming webminar provided by NASA ARSET on Land Cover Classification with Satellite Imagery will cover very interesting objectives such as access and download Landsat imagery and learn the basic steps for performing a supervised classifications using QGIS software.
I am very pleased that the Semi-Automatic Classification Plugin will be used during this training.

This webminar is organized in two dates:

• Tue, Jan 31, 2017 6:00 PM - 10:00 PM CET: Introduction to Land Cover Classification and QGIS
• Tue, Feb 7, 2017 6:00 PM - 10:00 PM CET: Improving a Supervised Land Cover Classification

and the Agenda is available here.

Image Credit: NASA/USGS, NASA Earth Observatory

Major Update: Semi-Automatic Classification Plugin v. 5.3.0

This post is about a major update for the Semi-Automatic Classification Plugin for QGIS, version 5.3.0
.

Following the changelog:

-added MODIS download and preprocessing tool
-added tool for stacking raster bands
-added MODIS processing and stack bands to Batch tool
-added option to export training input as shapefile
-fixed Sentinel-2 search
-fixed importing spectral signatures