Implementing the Concept

The description above indicates that each axis would be composed of several metrics. For feasibility, we require them to be scalable in the 0-10 framework. We further require that suitable public data sets be available. Because we want this concept to function at a variety of spatial levels, the data set must also have rather high spatial resolution. Possible suggestions for these metrics are:

1. Ecology Dimension

E1: Geographic context (e.g., landscape texture derived from remote sensing)

E2: Normal differentiated vegetative index (NDVI), a measure of vegetation derived from remote sensing

E3: Ecosystem services (e.g., value scaled from WWF ecosystem services index)

E4: Pollution in land parcel (e.g., value scaled from eutrophication index as measured in phytoplankton growth/(km2/yr)

2. Commercial Dimension:

C4: Artificial water management (e.g., percent of land parcel that can be irrigated)

3. Social Dimension:

S1: Population density (e.g., metric assigned so that maximum score, for an optimum intermediate density, is not very high or low)

S2: Institutional capacity (e.g., mining industry barriers to entry data set or time from permit application to approval data set)

S3: Average education level (e.g., data set to be determined)

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