Accuracy Assessment. A canopy percent cover model was not build for this project, so it is not possible to perform an accuracy assessment. Again, we avoided building this model so as not to under represent the utility of LiDAR data by comparing it to unsuitable field data. Previous work has shown that LiDAR outperforms imagery in canopy percent cover estimates as documented in our past literature review pilot (Xxxxxx & Xxxxx 2015.)
Accuracy Assessment. Estimated Canopy Percent Cover was within ± 25% of field estimated canopy cover for 63 of the 113 plots [56% of all plots]. This outcome is similar to imagery predictions of crown diameter, which are strongly dependent on how individual trees are identified from imagery. As the TDA is configured to fit the majority of plot compositions [Xxxxxxx Firs and Western Hemlocks] there are outliers that warrant a more dynamic approach. The field estimates of the canopy cover were estimated using a spherical densiometer. While this estimate is lacking some objective rigor that is associated with other metrics, it still provides an insight as to how well imagery algorithms are classifying tree canopy area per plot. Imagery predictions were generally underestimating the canopy percent cover when compared to field data. This follows in suit with crown diameter estimations, which were also underestimated more often than overestimated.
Accuracy Assessment. Individual employers and claimants report the information in the EDD’s files. Since the EDD is not the originator of the information disclosed, the EDD cannot guarantee the accuracy of the information. CUSTOMER CODE SPOC NAME ADDRESS PHONE EMAIL E00639 Xxxx Xxxxxx 000 0xx Xxxxxx, 0xx Xxxxx Xxxxxx, Xx 00000 707-268-2595 xxxxxxx@xx.xxxxxxxx.xx.xx E00640 Xxxxxx Xxxxxxx 000 0xx Xxxxxx, 0xx Xxxxx Xxxxxx, Xx 00000 707-268-2576 xxxxxxxx@xx.xxxxxxxx.xx.xx E00641 Xxxxxx Xxxxxx 000 0xx Xxxxxx, 0xx Xxxxx Xxxxxx, Xx 00000 707-268-2578 xxxxxxx@xx.xxxxxxxx.xx.xx
Accuracy Assessment. We did not collect data on where the true channel locations were, so there was no way to test the accuracy of any specific stream channel model or the set of processing choices used to create it, however, as the above figures show, LiDAR is very effective at capturing hydrological features on the landscape due to the detail ground models, this is beyond and above the abilities of other remote sensing technologies.
Accuracy Assessment. Average crown diameter estimates are within plus or minus five feet of the actual mean crown diameter for over 60% of the sample plots – represented by the histogram in Figure 19. This result is the first major reflection of only using a single algorithm for tree identification; it may perform relatively well for many of the stand structures in the area, but outliers do exist and may introduce extraneous error if they are not specifically accounted for.
Accuracy Assessment. − − In 40% of plots, tree stand density predictions are within +5 trees of actual plot counts. In almost 75% of plots, predictions are within +10 trees. Following the error in estimation of the other metrics, the tree delineation tends to underestimate the number of trees per acre. Figure 35. Frequency difference between estimated and measured stand density. Figure 36. Stand density scatterplot +/- 10 trees Figure 37. Stand density - all plots
Accuracy Assessment. Because stem mapping was not implemented in the project’s data collection component, there are no explicit trees that can be used as training objects for accuracy assessment. There were enough stands that were deciduous-dominant and coniferous-dominant to create a prediction that can gauge the two compositions, but without the exact position of any particular tree species it might not be possible to predict this level of granularity.
Accuracy Assessment. An age model was not build for this project, so it is not possible to perform an accuracy assessment.
Accuracy Assessment. Previous VA matches with the Social Security Administration indicate that the names and social security numbers (SSNs) in VA records are 99 percent accurate. VA internal verification procedures have also confirmed this percent of accuracy in VA records. BOP believes that virtually all of the names and SSNs that it will provide to VA will be the same as those furnished by the inmate sources.
Accuracy Assessment. Individual employers and claimants report the information in the EDD’s files. Since the EDD is not the originator of the information disclosed, the EDD cannot guarantee the accuracy of the information.
