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

abrupt seasonal changes in images. Some seamlines were corrected manually by hand editing
vector data, conversion to raster, and merged into new mosaics. For shadows, clouds, and ice,
additional SPOT images were used where available and supervised classification steps were
performed inside shadow, cloud and ice areas as masks. Results were verified against the
original land cover mosaics for any potential seamline issues (abrupt changes between input
images) and then the data was merged into final mosaic land cover data sets.
3.3.3.5 Land Cover Tabulations by Watershed
The final 9-class land cover data sets were then intersected with the 39 community flood
watersheds to tabulate total area (in square kilometers) and percent coverage of each class by
watershed name (Table 3-7). For Quality Assurance / Quality Control purposes, random
watersheds were selected and land cover metrics were calculated by hand then checked
against automated metrics. These tables were then used as direct inputs to the flood
vulnerability assessment.
3.3.4 Results
Results are presented for the overall classification and for each community flood watershed
delineation boundary inTable 3-7. Accuracy assessment results detail the effectiveness of the
classification methods employed in this study. Land cover within 39 watersheds is presented
covering the flood vulnerability areas for the 32 communities identified in the proposal. Table
3-7is presented in alphabetical order by watershed name.
3.3.4.1 Accuracy Assessment
An accuracy assessment was completed to measure the effectiveness of classifying six classes
of land cover derived from the 10-meter SPOT imagery. Classification accuracy was assessed
by comparing ground truth (from 2.5 meter resolution, natural color, pan-sharpened SPOT
images) to the classified land cover at each assessment point. When interpreting the
contingency table (Figure 3-5) a number of important precautions should be considered:
1. Ground truth data (2.5 m) used to assess the accuracy is of a higher spatial resolution than
the data used in the classification (10 m). The difference in resolution and spatial shift can
lead to exaggerated errors, since the larger pixels used in the classification can be a
combination of a number of land cover classes (See Figure 3-4 ).
2. Ground truth data in some cases may be from a time period that differs from the time period
of the classified imagery. While image dates are generally from the same period, not all 10-
meter imagery used for classification had 2.5-meter imagery and vice versa. Spatial shifts
and land cover change may have occurred between the ground truth image and
classification image.
3. Ground truth data are natural color 3-band images, while the classification data use 4-
bands. In natural color, wetlands and barren ground look very similar. Because of this,
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