Biophysical regions of the Southern Highlands, Tanzania: regionalization in a data scarce environment with open geospatial data and statistical methods

Abstract

Spatially explicit, evidence-based and regionally contextualized data on biophysical landscape characteristics is an essential basis for regionally sustainable landscape management schemes. In many regions of the Global South, the availability of such information is poor, especially at the subnational level, and the spatial management is often based on generic and outdated information, leading to severe threats for land sustainability. We have developed a biophysical regionalization of the Southern Highlands area of Tanzania. The map is based on open-source global datasets depicting climate, soil, topography and vegetation. Through replicable statistical and geospatial analyses, we have identified 7 regions and 18 subsections with biophysically similar and spatially distinctive environmental conditions. The regions provide spatially contextualized support for understanding and managing the landscapes of the Southern Highlands. The applications for such data sets are numerous, from screening suitability areas for e.g. afforestation schemes to evaluating the distinctiveness and vulnerability of landscapes to degradation.

Keywords

• data scarcity
• open data
• global south
• africa
• regionalization
• k-means