Quantifying Impacts of Grazing and Poor Land Management Strategies on Erosion through a Semi-Automated Change Detection Workflow in Ka’amola, Molokai

Space Dynamics Laboratory, Auditorium Rm A

A challenge faced by those working in a system plagued by non-native vegetation invasion and disturbance from ungulates is the ability to collect landscape-level information about land cover change and the mass movement of soils associated pulsed rainfall events. Our goal was to conduct high-precision change detection of land cover and surface features during a two-year period that included several mass sediment flux events associated with tropical storms. We present here preliminary results of the development and testing of a rule set based classification algorithm used to classify imagery from 2019 and 2021 of a single watershed in Molokai to evaluate the efficacy of the approach as well as sharing limitations that need to be considered before further implementing this for long term usage.