Conclusions

Four different classification methods were tested on a Worldview-2 image to classify six land cover types with an objective of accurately mapping the invasive wetland plant

Phragmites. Four and eight band datasets were classified using the per-pixel maximum likelihood classifier and object-based methods. Three major conclusions have been determined as a result. First, object-based methods resulted in higher classification accuracy than their respective per-pixel maximum likelihood classifications. Using four band imagery, the overall classification accuracy for the object-based method was 19.7% higher than per-pixel MLC. Similarly, eight band imagery and object-based classification resulted in an increase of 10.6% in overall classification accuracy over eight band per- pixel MLC. Therefore, object-based methods were superior than per-pixel MLC for classification. Second, for both per-pixel MLC and object-based methods, eight band imagery resulted in higher classification accuracy than four band imagery. Eight band per-pixel MLC was 10.4% overall more accurate than four band, while eight band object- based was 1.3% overall more accurate. Although the eight band object-based method did not result in a large increase in accuracy over the four band object-based method, the accuracy of the vegetation classes was improved by using the eight band imagery and the associated method. Therefore, the additional spectral information provided by the

Worldview-2 satellite was useful in separating the classes on Walpole Island and

mapping the invasive plant. Third, the best method for mapping Phragmites was the eight band object-based method. This method increased overall accuracy of the six class classification by 21% over the four band per-pixel MLC, 10.6% over the eight band per- pixel, and 1.3% over the four band object-based method. The Kappa statistic for the

Phragmites and Non-Phragmites classification for the eight band object-based method was also 0.422 higher than the four band per-pixel MLC, 0.211 higher than the eight band per-pixel, and 0.025 higher than the four band object-based method. Therefore, the eight band object-based method was the best for both classifying the six land covers and for distinguishing between Phragmites and Non-Phragmites.

This study showed that a single date, eight band high resolution image classified with object-based methods was effective for mapping an invasive wetland plant species in a southwestern Ontario Great Lakes coastal wetland. Although detailed steps for Method 2 presented here were significant for extracting the six classes, its extension for classifying other images collected by the Worldview-2 satellite for this purpose may not be

appropriate. A similar classification scheme may be appropriate for images collected late in the growing season when vegetation conditions are similar. The Worldview-2 satellite may be an option for mapping Phragmites for management as a single date image can provide high accuracy for the invasive wetland plant.

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Chapter 3