Forest Proximate People Database 

Mapping the Spatial Proximity between People and Forests: A New Dataset to Aid Environment and Development Decision-Making

How many people live in and around forests?

Variability in the definitions of forest dependence, and an absence of global datasets that measure dependence, mean that reliably calculating consistent and replicable estimates of the number of forest-dependent people is not viable. However, many definitions of ‘forest-dependent people’ also include criteria of a spatial relationship between people and forests, most often referring to rural people living in and around forests (Newton et al. 2016). This subset of ‘forest-proximate people’ typically derive direct livelihood benefits from forests, compared to those living in locations distant from forests, despite some notable exceptions. It is likely that this is the demographic most often targeted by agencies invested in poverty alleviation and/or sustainable socio-economic development within forested regions. Forest proximity is therefore often a necessary, although not sufficient, criterion for forest dependence. Proximity is also a measure that is quantifiable at global scale using publicly available global forest cover and population datasets at a relatively fine spatial resolution. We use remote sensing and census data to generate measures of forest proximity as a partial proxy for forest dependence.

We combined recent forest cover and human population density data to map the spatial relationship between people and forests on a global scale. We used 1km resolution global population density data (Bright et al., 2012) and 30m resolution global forest cover dataset version 1.0 (Hansen et al., 2013) to generate spatial overlays that identified population subsets living in or close to forests. We first created a global forest cover map by mosaicking the forest cover tiles from Hansen et al. (2013) into a global raster image using ArcGIS. We calculated baseline global forest cover in 2000 using Hansen et al.’s definition of stand replacement (50% tree cover threshold; Hansen et al., 2013), and used forest gain and forest loss datasets for the subsequent twelve years to generate a final forest cover estimate for the year 2012. We resampled the forest cover raster dataset from 30m to 1km resolution using the nearest neighbor function to match the resolution of the global population density dataset and to improve computing viability. We projected both datasets into the Mollweide equal-area projection (Usery and Seong, 2001) so that kilometers could be used for the buffer zone distance. We used a Euclidian distance measure to create a 5 kilometer buffer zone around each forest pixel. Using the Zonal Statistics tool, we then calculated the population living within that 5 kilometer buffer zone and summed the total for each country. We excluded urban areas from our analysis, defining them as areas with population densities equal or greater than 1500 people per km2 (Brezzi et al., 2012). Brezzi et al. (2012) also consider 1000 people per km2 as an alternative metric for urban areas; we chose the higher population density to generate the most liberal estimates of the number of forest proximate people.

We calculate that 1.61 billion rural people lived within 5km of a forest in 2012, globally.

We provide all country-specific estimates below, as well as maps that show forest proximate people for the 80 countries that make up 90% of (1) the worlds poor, (2) forest cover, and (3) global population.

REFERENCES

Byron, Neil, and Michael Arnold. 1999. “What Futures for the People of the Tropical Forests?” World Development 27(5): 789–805.
Calibre Consultants. 2012. Numbers of Forest Dependent People: A Feasibility Study. Reading: Calibre Consultants and the Statistical Services Centre (SSC), University of Reading.
Hansen, Matthew C et al. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342(6160): 850–53.
Landscan. 2012. “LandScan 2012: High Resolution Global Population Data Set.”
Newton, Peter, Daniel C. D.C. Miller, M.A.A. Mugabi Augustine Ateenyi Byenkya, and Arun Agrawal. 2016. “Who Are Forest-Dependent People? A Taxo Nomy to Aid Livelihood and Land Use Decision-Making in Forested Regions.” Land Use Policy 57: 388–95. OECD. 2012. “Redefining ‘Urban’: A New Way to Measure Metropolitan Areas.” OECD Publishing (September): 1–9.
http://www.oecd.org/regional/redefiningurbananewwaytomeasuremetropolitanareas.htm (April 29, 2018).
Usery, Lynn E., and Jeong Chang Seong. 2001. “All Equal-Area Map Projections Are Created Equal, but Some Are More Equal than Others.” Cartography and Geographic Information Science 28(3): 183–94. World Bank. 2002. A Revised Forest Strategy for the World Bank Group_31 October 2002. Washington, D.C.: World Bank.