## 4 Discussion
### Improved Map Accuracy for Data Integration  
To answer questions of public interest such as those pertaining to natural resource management and land-use planning effectiveness, regional and local governments need to be able to integrate land-use/land-cover change (LULCC) data with other GIS data sources. This requires LULCC data with high spatial resolution and spatial precision because many such data sources have individual units that cover relatively small areas in relation to a medium resolution, 30-m pixel [61]. For example, changes in regulated riparian corridors [59], urban infilling and new satellite development within undisturbed canopies [85] frequently occur at scales smaller than the Landsat minimum mapping unit. To address these needs, object-based change detection methods were used with 1-m publicly available aerial imagery. By lowering the acceptance threshold from 50% in RF50 to 25% in the RF25 map, 93% more development-related change was detected. Further, while, the initial RF50 map captured 85% of the total mapped change area, the RF25 data was heavily skewed towards identifying small permanent changes, _i.e._, average size of \(>\)50%-probability changes was 0.51 ha compared to 25%-50%-probability changes that had an average size of 0.19 ha. Not surprisingly, bigger changes are easier to detect. By type, the average Forestry polygon was 5.43 ha (1275 locations) compared to 0.42 ha for Natural change (2001 locations) and 0.37 ha for Development change (2252 locations). Locating development-related changes was the highest priority because changes associated with human development (urbanization) while usually small, are mostly permanent and often inform how well local governments are meeting their responsibilities under land use planning laws, such as the WA State Growth Management Act (GMA, Chapter 36.70A RCW) or the Shoreline Management Act (SMA, Chapter 90.58 RCW). For example, [PERSON] [86] used high-resolution change location data in an analysis of conservation effectiveness in the Cedar-Sammamish watershed in the Puget Sound region of Washington. [PERSON] located 72 change events between 2006 and 2009 occurring adjacent to streams, totaling 18.7 ha. The cause of change was determined for each change location and evaluated relative to ownership and land-use category. Natural change was the most common change type (7.8 ha) followed by development (5.5 ha) and transportation projects (4.1 ha). Importantly, no change was mapped on parcels containing conservation easements or other land use restrictions suggesting these conservation mechanisms were adequately protecting riparian buffers. The final change map consisted of 1.66% change and 98.34% no-change. Thus, if an uninformative model had been used and simply mapped no change, the overall accuracy would have still been 98.34%. However the commission analysis discovered a 2.55% commission error rate for the base map polygons and a 49.8% commission rate for the additional 25%-50% probability polygons. The omission analysis yielded a 0.27% error rate of omission. Since the commission was eliminated, the only error in the final map was the omission area and the final map overall accuracy was 99.73%, 1.39% better than mapping no change at all. Importantly, some of the common accuracy statistics also become uninformative after applying these procedures. For example, the User's Accuracy assesses the probability that a location mapped as a certain class will be that class. By eliminating commission error the User's Accuracy for the final map was 100%. This informs the user that all mapped changes are actually changes. However, for practical usage, neither a producer's or user's accuracy of 100% nor an overall accuracy of 99.73% conveys much information about the success of the analysis. During the development of these techniques the proportion of mapped change relative to total predicted change was frequently used as a metric of success. This is roughly equivalent to [PERSON] _et al._'s [58] Adjusted Producer's Accuracy (APA).