This dataset is a polygon representation of the Landscape Typologies within parks owned and maintained by DPR with the City and County of Denver (CCD). The Landscape Typology mapping and assessment effort was not comprehensive and did not include all areas maintained by DPR but focused on parks with natural vegetation communities.

The general methodology for vegetation community mapping and scoring was as follows:

1. DPR maintenance boundaries were used for park extents.

2. Impervious surfaces, planting beds, and ball fields were clipped from the boundary.

3. Vegetation communities were delineated using high-resolution aerial imagery. Polygons were mapped at a scale of 1/4th acre for upland areas and 1/6th acre for riparian areas.

4. Vegetation community types and extents were field verified and adjusted as needed.

5. Field data collection included recording the percent cover by each strata (trees, shrubs, forbs, and grasses), the two dominant vegetation species for each strata and their total cover, and the two dominant noxious weeds and their total cover. Additionally qualitative and semi-quantitative parameters were also scored in the field for each park that was assessed.

Function (FUNC_PERCENT) was calculated by summing scores from each assessed parameter and dividing by the total possible score to get a normalized functional score. FUNCTION is based on the following thresholds:

• Excellent: 86-100

• Good: 70-85

• Fair: 50-69

• Poor: <50

Restoration Score (RESTORATION SCORE PERCENT) was calculated by summing scores from each assessed ecological parameter (DIVERSITY SCORE, WILFLIFE SCORE, POLLINATOR HABITAT SCORE, NOXIOUS POPULATION SCORE, and INVASIVE WEED SCORE) and dividing by the total possible score to get a normalized restoration functional score.

CUSP POLYGONS are polygons within +/- 2 points of a higher or lower function (FUNC_PERCENT). CUSP PRIORITY was assigned based on the type of cusp (risk of falling to lower function or ability to increase to higher function):

• Excellent à Good: Low Priority (1)

• Good à Excellent: Low Priority (1)

• Good à Fair: High Priority (5)

• Fair à Good: Moderate Priority (3)

• Fair à Poor: High Priority (5)

• Poor à Fair: High Priority (5)