1. The following slides are intended to provide a few examples of some problems and issues that come up in Landcover mapping. This will be an ever-growing presentation as more issues and clear examples will arrive in the future. Please feel free to contact Jon Dewitz at dewitz@usgs.gov with any questions.

2. Below is an excellent example of imperviousness masking. Notice the open patches inside the urban area which have been masked. All are continuous forest, which is something that we do not want to be included in imperviousness. Additionally, the open spaces not containing trees have been included in the imperviousness estimate. This eliminates many problems later in the landcover classification. Things appropriate for the open space impervious class are parks, golf courses, and open lots. Also, on the edge of town, many other open areas which are still farmland have been masked, allowing in the future for the landcover to correctly identify these as agricultural areas.

3. Another excellent area of masking. The development area shows around this lake. Without this correct masking, the area could potentially and incorrectly be identified as emergent herbaceous. Notice also the roads that have been identified, and the correct identification of the ditches surrounding this interstate as part of the open space developed class. Good buffering of the roads layer has allowed this, as well as checking of the accuracy of the major roads, which can sometimes be incorrect.

4. This shows an obvious area of interstate that is not correct due to an incorrect roads layer and resulting mask. The actual highway shows through as impervious. There are very few interstates, but they tend to be off drastically in a few places as they are derived from an older roads database. All should be followed, and hand edited if they stray dramatically like this. The buffer for the interstate is too wide as well.

5. In this landcover scene, we have an urban setting with everything outside the extent of view being impervious from a large city. There are a few spots in brown of Ag. Classification which should be recoded to the open space impervious class. There are also hay/pasture areas in yellow. In most cases this should also be edited out, but Kentucky is a special case. There are numerous horse farms and stables inside many of the cities that have the hay/pasture class. In this case, the hay pasture seems an appropriate classification. In many others cases such as parks or golf courses, this class should be edited back to the open space class. Also notice the deciduous class which comes through in green strongly and correctly. Lat/lon (39 09 48, 84 31 20)

6. Another impervious area that has been incorrectly masked initially in the impervious estimate. This has allowed the barren class to show through. This should be edited back to the high impervious class. A better, and more continuous imperviousness mask would have eliminated the errors in both of these scenes. Lat/lon (37 55 05, 87 19 52)

7. There can be areas like this urban Ikonos image in the middle, that have both an impervious estimate on the left, and a canopy estimate on the right. Both are correct and appropriate estimations.

8. Since both the impervious and canopy estimate from the previous slide are correct, and since landcover can be represented by only on class, imperviousness was chosen to be the dominant class of the two in all cases. The canopy estimate is then relied upon to provide the user with a way to appropriately identify areas such as this.

9. This leaf-off NIR DOQQ shows the conifer stands in this zone. The conifer deciduous line is not able to be seen on the right in the canopy estimation, showing a good estimation for all species. The actual estimation was checked through closer scrutiny of other leaf on DOQQ’s. Also, the masking shows excellent delineation of forest non-forest boundaries, without excluding the forested areas in the suburban impervious areas.

10. In this canopy estimation, we can see poor canopy masking over a grassy area, resulting in a low canopy estimate over this grassy area.

11. This shows why all imagery should be checked for any anomalies. The clouds have been classified as lakes. Also notice the seam line. Good training has allowed the seam line to be non-existent in the landcover.

12. This scene shows excellent delineation of deciduous, coniferous, and mixed. Also note the woody wet correctly identified in blue following the river.