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Flood Risk and Vulnerability Analysis Project - Atlantic Climate ...

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Figure 3-3. Graphical model of l<strong>and</strong> cover/l<strong>and</strong> use classification<br />

methods used in this study<br />

3.3.3.2 ISODATA Classification <strong>and</strong> Aggregation<br />

Images <strong>and</strong> image groups with similar visual characteristics were then classified using the<br />

ISODATA (Iterative Self Organizing Data <strong>Analysis</strong> Techniques) algorithm within the software<br />

ERDAS Imagine. The ISODATA algorithm is an unsupervised classification that generates<br />

statistically significant clusters of similar pixels based on values within each b<strong>and</strong> <strong>and</strong> the userdefined<br />

number of clusters. The number of clusters selected for a particular classification was<br />

dependent on the overall size of the image or image group but ranged from 20 for small images<br />

to 100 for large images (the larger the image, the greater number of pixels, the greater number<br />

of clusters selected). Clusters were then manually assigned to one of six l<strong>and</strong> cover classes<br />

using higher resolution aerial <strong>and</strong> satellite imagery. ISODATA is very similar to the Fuzzy K<br />

Means unsupervised classification used in the Stephenville, Newfoundl<strong>and</strong> l<strong>and</strong> cover<br />

classification study. To create the 7 th l<strong>and</strong> cover class for 2010 conditions, municipal area 15<br />

boundaries were then used to separate non-forest vegetation into open space (municipal green<br />

space) vs. fields/pasture (agricultural l<strong>and</strong> outside municipal boundaries). The classification at<br />

this point takes on more of a l<strong>and</strong> cover / l<strong>and</strong> use data set with the influence of supporting GIS<br />

data. The 8 th <strong>and</strong> 9 th classes showing the type of deforested l<strong>and</strong> conversion were then<br />

accomplished with an overlay <strong>and</strong> reclassify of EOSD data (methods described below).<br />

Final l<strong>and</strong> cover classes (Table 3-5) for the <strong>Flood</strong> <strong>Vulnerability</strong> study. Non-forest vegetation from<br />

the original classification is separated into Fields/Pastures or Open Space relative to municipal<br />

boundaries. Two types of deforestation are reported based on original l<strong>and</strong> cover class.<br />

15 Municipal boundaries provided by Charmaine Winter, Computer Programmer 1 (GIS), NL Dept. of<br />

Municipal Affairs, (709) 729-6666, cwinter@gov.nl.ca.<br />

TA1112733<br />

39

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