Journal of Hydroinformatics (May 2021)
A feasibility study of uninhabited aircraft systems for rapid and cost-effective plant stress monitoring at green stormwater infrastructure facilities
Abstract
Vegetation health monitoring is key to identifying early signs of water stress, pollutant-induced toxicity, and plant diseases in green urban stormwater facilities. However, rigorous monitoring to collect accurate quantitative data is an expensive and time-consuming process. This paper examines the feasibility of using uninhabited aircraft systems (UAS), in comparison to standard ground-based methods, for monitoring biomass and primary production in two bioswale cells at an urban stormwater facility. Implementation of the UAS-based approach involved flight planning in an urban area to meet resolution requirements of bioswale imagery obtained from near-infrared and red-green-blue cameras. The resulting normalized difference vegetation index (NDVI) estimated from UAS data was tracked over a 2-month period during the transition from spring to summer, showing the spatial distribution of NDVI and the change in vegetation coverage areas over time. In comparison, ground-based measurements of the fraction of intercepted photosynthetically active radiation (PAR) presented multiple practical challenges during implementation in the field, leading to over- and underestimates of intercepted PAR. Overall, UAS-derived NDVI was found to be a valuable reflectance-based, vegetation health-monitoring methodology that can be used by utilities and cities for practical, cost-effective, and rapid assessment of vegetation stress and for long-term maintenance in green stormwater facilities. HIGHLIGHTS Ground-based monitoring of green infrastructure (GI) facilities for estimation of fraction of intercepted photosynthetically active radiation poses multiple operational challenges.; Uninhabited aircraft systems (UAS) were found to enable efficient acquisition of multi-temporal normalized difference vegetation index (NDVI) data for GI site monitoring, through the workflow developed in this study.; Time series of UAS-derived NDVI showed the expected downward trend over a two-month period starting on June 1, 2019.; Spatial variation in UAS-derived NDVI provides plant-specific health information that may assist in GI site management.;
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