Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands
Abstract
To support improved rangeland resource management and monitoring for nomadic pastoralists in northern Kenya, we used a task-based mobile application to incentivize pastoralists provide more than 100,000 surveys containing information on local rangeland, water and livestock resources. In this contribution we explore the potential of combining this information with remote sensing data for improved characterization of rangeland resource use and accessibility through integration of local socio-ecological knowledge into land cover mapping methods.
Citation
Fava, F., Jensen, N., Oto, L. de and Mude, A. 2018. Integrating local crowdsourced and remotely sensed data to characterize rangeland resource use in extensive pasturelands. Presented at the CGIAR Platform for Big Data in Agriculture Convention, Nairobi, 3-5 October 2018. Nairobi, Kenya: ILRI.