Mass populations of toxic cyanobacteria in recreational waters can present a serious risk to human health. Intelligence on the abundance and distribution of cyanobacteria is therefore needed to aid risk assessment and management activities. In this paper, we use data from the Compact Airborne Spectrographic Imager-2 (CASI-2) to monitor seasonal change in the concentration of chlorophyll a (Chl a) and the cyanobacterial biomarker pigment C-phycocyanin (C-PC) in a series of shallow lakes in the U.K. The World Health Organization guidance levels for cyanobacteria in recreational waters were subsequently used to build a decision tree classification model for cyanobacterial risk assessment which was driven using Chl a and C-PC products derived from the CASI-2 data. The results demonstrate that remote sensing can be used to acquire intelligence on the distribution and abundance of cyanobacteria in inland waterbodies. It is argued the use of remote sensing reconnaissance, in conjunction with in situ based monitoring approaches, would greatly aid the assessment of cyanobacterial risks in inland waters and improve our ability to protect human health.