User:Brettbechamp

Introduction and Purpose

The analysis of multispectral imagery is useful for a detecting a wide range of geospatial patterns that would otherwise not show in visible spectrum imagery. The purpose of this tutorial will be to familiarize you with concepts related to landcover classification based on multispectral imagery, and to expose you to SAGA GIS; an application for geospatial analysis.

Software

To perform the tasks described below, you will need to dowload SAGA from sourceforge.net

SAGA GUI interface

Here is the basic layout of SAGA GIS. Notice the multi-pained format. The project tree or temporary work space is in the top left. This where you'll find all of your project data as well as access SAGA's array of Geoprocessing tools. You can navigate between data view, map layer view, tools, and thumbnails using the tabs at the top of the temporary work space. Below that is the file tree. There is not a lot to be said about this area; It is where you can look up files and folders in order to add data. Beside the file tree is the Tool/layer properties window. This is where you will enter tool parameters, look up layer properties, analyse look up tables and set display parameters for you data. To the right, is the map view; fairly self explanatory.

Data

The sample data used for the creation of this tutorial came from the Ontario SPOT Pansharpened Orthoimagery dataset. The dataset can be found on scholar's geoportal Here. The data is three band-false colour composite imagery with bands NIR-R-G. This combination of spectral bands is often used for the study of vegetation due to the high NIR reflectance of foliage. The dataset was collected with the SPOT satellite between 2005 and 2010. The pixel size for this imagery is 20m and each scene covers a geographic area of 40km by 40km.