Unsupervised Image Classification using QGIS and SCP Extension

Learn how to source and download an orthoimage from Equator, import the orthoimage (a raster file) into QGIS, install the SCP extension, and run an unsupervised image classification analysis.

Unsupervised image classification is a remote sensing method used to classify raster images without predefined (human input) training data. It uses clustering algorithms to group raster pixels with similar spectral properties. The user can assign land-cover classes to each cluster once the process has finished. Image classification is used in land-use and land-cover mapping, environmental monitoring, disaster management, urban planning, natural resource management, agriculture, and forestry.

To install the SCP plugin, open QGIS and click on Plugins in the top menu. Select Plugins, then Manage and Install Plugins. The dialogue box for Plugins will appear. Search for SCP, select it, and click install.

Equator has an extensive collection of the latest orthoimagery and LiDAR data available that can be converted to contour lines. You can download your data and get started on your project immediately.

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00:00 - Intro
00:18 - Source Orthoimage from Equator
01:29 - Open QGIS and Import Orthoimage (Raster File)
01:58 - Unsupervised Image Classification using SCP Extension

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