Remote detection of community-based rangeland management (CBRM)
By Sircely, Jason A.; Fava, Francesco P. and Oloo, Stephen O.
Several approaches based on remotely sensed data can be applied to assess landscape level management influences in rangelands, such as community-based rangeland management (CBRM). Rangeland condition indicators from remote sensing have their own advantages and assumptions. To test the ability of remote sensing indicators in tracking long–term trends in pastoral rangelands in East Africa, three rangeland condition indicators—cumulative annual normalized difference vegetation index (cNDVI), annual rainfall use efficiency (RUE; cNDVI/annual precipitation), and bare soil were calculated for three time periods between 2003 and 2019 in rangeland units applying CBRM in Kajiado and Laikipia counties in Kenya, and Borana Zone in Ethiopia. Spatiotemporal trends suggested that all three indicators, or a combination thereof, are feasible methods for detection of landscape level influences of community-based rangeland management, although the degree to which various indicators should be weighted in a larger analysis remains debatable. In the three research areas, trends among areas, time periods and indicators sometimes aligned and sometimes conflicted with one another. The substantial set of ecological and social factors are likely responsible for these observed trends and should motivate due diligence in conducting evaluation of rangeland condition indicators from remote sensing.