Supporting Information for Tracking progress towards urban nature targets using landcover and vegetation indices: A global study for the 96 C40 Cities

These datasets include the results published in Martin, G.K., K. O'Dell, P.L. Kinney, M. Pescador Jimenez, D. Rojas-Rueda, R. Canales, and S.C. Anenberg (2024). Tracking progress towards urban nature targets using landcover and vegetation indices: A global study for the 96 C40 Cities. GeoHealth, In press.

Supplmental Data S1 contains infomration for the main analysis using Urban Centre Database bounds and includes city-level summary measures. These include measures of natural space and population as well as model diagnostics and outputs. Supplmental Data S2 is a parallel dataset of the sensitivity analysis using the self-defined C40 urban bounds. 

Variable definitions:

city= name of urban area

country= country in which urban area is located

region= C40-defined global region in which urban area is located

t1_mean_ndvi= city-mean NDVI. The mean of the 100m pixel NDVI values within the urban bounds. This value was used to assess Target 1.

t1_mean_mndvi= city-mean NDVI plus water. The mean of the 100m pixel NDVI plus water values within the urban bounds. Water pixels were assigned a value of 1.

t1_mean_ga= city-mean proportion of green area. The mean of the 100m pixel green area values within urban bounds. This value was used to assess Target 1.

t1_mean_gba= city-mean proportion of green or blue area. The mean of the 100m pixel green or blue area values within the urban bounds.

t2_mean_ndvi= city-mean blurred NDVI. The mean NDVI within a 1000m buffer area of each 10m pixel was first calculated and then aggregated to 100m. This is the mean of each 100m pixel’s blurred NDVI value within urban bounds.

t2_mean_mndvi= city-mean blurred NDVI plus water. The mean NDVI plus water within a 1000m buffer area of each 10m pixel was first calculated and then aggregated to 100m. This is the mean of each 100m pixel’s blurred NDVI plus water value within urban bounds. This value was used to assess Target 2.

t2_mean_ga= city-mean blurred green area. The mean green area within a 1000m buffer area of each 10m pixel was first calculated and then aggregated to 100m. This is the mean of each 100m pixel’s blurred green area value within urban bounds.

t2_mean_gba= city-mean blurred green or blue area. The mean green or blue area within a 1000m buffer area of each 10m pixel was first calculated and then aggregated to 100m. This is the mean of each 100m pixel’s green or blue area value within urban bounds. This value was used to assess Target 2.

city_adult_pop= total adult population within urban bounds. The sum of the population aged 20 or older living within each 100m pixel within the urban bounds.

pct_access_gba= percent of adult population with access to green or blue space within a 1000m buffer.

t1_adjr2= adjusted R2 value for each city’s Target 1 regression model

t1_rmse= rmse value for each city’s Target 1 regression model

t1_p_ndvi_30= the predicted NDVI value equivalent to achieving 30% green area value from each city’s Target 1 regression model

t1_p_ndvi_40= the predicted NDVI value equivalent to achieving 40% green area value from each city’s Target 1 regression model

threshold_reg= the predicted NDVI value equivalent to 100% green area value from each city’s Target 1 regression model. This value was used in a sensitivity analysis to determine whether a pixel was considered “green” for Target 2.

threshold_reg75= the predicted NDVI value equivalent to 75% green area value from each city’s Target 1 regression model. This value was used to determine whether a pixel was considered “green” for Target 2.

threshold_reg90= the predicted NDVI value equivalent to 90% green area value from each city’s Target 1 regression model. This value was used in a sensitivity analysis to determine whether a pixel was considered “green” for Target 2.

t2_adjr2 = adjusted R2 value for each city’s Target 2 regression model

t2_rmse= rmse value for each city’s Target 2 regression model

t2_p_mndvi_70= the predicted NDVI plus water value equivalent to 70% of the 100m pixels having access to green or blue area within 1000m from each city’s Target 2 regression model

t1_yes_30= city meets Target 1 (30% green area). 0=no, 1=yes

t1_yes_40= city meets Target 1 (40% green area). 0=no, 1=yes

t2_yes= city meets Target 2 (70% of population has access to green or blue area within 1000m). 0=no, 1=yes