Measures Development

Table 4. Data measures used in the SCA Tool suite.

No	RESTORE Goal	Priority Attributes	Name of the Measure
1	Habitat	Vulnerability to Conversion	Project Area (Acres)
2		Connectivity	Connectivity to Existing Protected Area (Index)
3			Connectivity of Natural Lands (Percentage)
4		Vulnerability to Conversion	Threat of Urbanization (Index)
5		Land Cover	Composition of Priority Natural Lands (Percentage)
6	Water Quality & Quantity	Quality	303(d): Impaired Watershed Area (Percentage)
7		Flow	Hydrologic Response to Land-Use Change (Percentage)
8		Floodplain and Streambank Integrity	Lateral Connectivity of Floodplain (Percentage)
9		Water Availability	Percent Irrigated Agriculture (Percentage)
10		Floodplain and Streambank Integrity	Composition of Riparian Zone Lands (Index)
11		Hydromodification	Presence of Impoundments (Binary)
12	Living Coastal & Marine Resources	Biodiversity	Vulnerable Areas of Terrestrial Endemic Species (Index)
13		Critical Species	Threatened and Endangered Species - Critical Habitat Area (Percentage)
14			Threatened and Endangered Species - Number of Species (Count)
15		Light Pollution	Light Pollution Index (Index)
16	Community Resilience	Historic Places	National Register of Historic Places (Count)
17			National Heritage Area (Percentage)
18		Vulnerability	Proximity to Socially Vulnerability Communities (Index)
19		Threat	Community Threat Index (Index)
20	Gulf Economy	Land Cover	High Priority Working Lands (Percentage)
21		Fisheries	Commercial Fishing Reliance (Index)
22			Recreational Fishing Engagement (Index)
23		Recreation	Access & Recreation - Number of Access Points (Count)

The methods used to process each measure were dependent on the type of source data (i.e., vector or raster) and the type of measure unit (i.e., index, binary, percentage area, count, or length). See Table 5 for a more detailed summary of the source data type and measure unit type for each of the 22 measures. Figures 13 and 14 provide visualizations of a general workflow used to produce measures from vector and raster source data, respectively.

Figure 13. Visual aid of the steps involved to convert vector source data into a measure.

Figure 14. Visual aid of the steps involved to convert raster source data into a measure.

Table 5. Summary of source data type and measure unit type for each measure.

Source Data Type	Measure Type	Measure
Vector to Measure	Index (0-1)	Commercial Fishing Reliance
		Recreational Fishing Engagement
	Binary (0/1)	Connectivity to Existing Protected Area
		Proximity to Socially Vulnerable Communities
		Presence of Impoundments
	Percentage Area (%)	303(d): Impaired Watershed Area
		Hydrologic Response to Land-Use Change
		Composition of Riparian Zone Lands
		Threatened and Endangered Species - Critical Habitat Area
		National Heritage Area
	Count (#)	Threatened and Endangered Species - Number of Species
		National Register of Historic Places
		Access & Recreation: Number of Access Points
Raster to Measure	Index (0-1)	Threat of Urbanization
		Vulnerable Areas of Terrestrial Endemic Species
		Light Pollution Index
		Community Threat Index
	Percentage Area (%)	Lateral Connectivity of Floodplain
		Connectivity of Natural Lands
		Composition of Priority Natural Lands
		High Priority Working Lands
		Percent Irrigated Agriculture

Figures 15a-15e illustrate the five different types of data measures in preprocessed states (i.e., index, binary, percentage area, count, and length) that are present within the database. Figures 16a and 16b illustrate the two types of source data (i.e., vector and raster) that were utilized in processing the database measures.

Figure 15. Measure types included within the geospatial database. a) An example of an index measure using recreational fishing engagement. b) An example of a binary measure using connectivity to existing protected area. c) An example of a percentage area measure using 303(d) impaired watershed area. d) An example of a count measure using the national register of historic places. e) An example of a length measure using stream abundance.

Figure 16. Source data types. a) An example of vector data using the biodiversity index. b) An example of raster data using the SLEUTH model.

There are two potential sources of uncertainty that need to be considered with the use of this database. First is the time lag between source data production and when the database was created, which will depend on each measure. As time progresses, the accuracy of each measure will inevitably decline, but the database used the most recent version of each source data to minimize any error induced by time lag. A second potential source of uncertainty comes from the 1 km2 resolution that was used for the hexagonal grid. Since the measures were defined to describe general features of an area for conservation considerations, and most lands conserved in this region are roughly 1 km2, the data resolution was adequate for assessments of land conservation value. Caution should thus be noted if using this database for purposes other than land conservation value.

The geodatabase is available at Scholar’s Junction, an institutional repository for Mississippi State University, as a shapefile. A readme file is available for download along with the database where the user can find instructions for how to convert the database from GeoJSON to other formats

For more information on individual SCA data measures see the “Support” section.