###### Abstract  
Over the past few decades, there has been a notable surge in interest in green stormwater infrastructure (GSI). This trend is a result of the need to effectively address issues related to runoff, pollution, and the adverse effects of urbanization and impervious surfaces on waterways. Concurrently, unmanned aerial vehicles (UAVs) have gained prominence across applications, including photogrammetry, military applications, precision farming, agricultural land, forestry, environmental surveillance, remote-sensing, and infrastructure maintenance. Despite the widespread use of GSI and UAV technologies, there remains a glaring gap in research focused on the evaluation and maintenance of the GSIs using UAV-based imagery. This study aimed to develop an integrated framework to evaluate plant density and health within GSIs using UAV-based imagery. This integrated framework incorporated the UAV (commonly known as a drone), WebOpenDroneMap (WebDOM), ArcMap, PyCharm, and the Canopeo application. The UAV-based images of GSI components, encompassing trees, grass, soil, and unhealthy trees, as well as entire GSIs (e.g., bioretention and green roofs) within the Morgan State University (MSU) campus were collected, processed, and analyzed using this integrated framework. Results indicated that the framework yielded highly accurate predictions of plant density with a high R\({}^{2}\) value of 95.8% and lower estimation errors of between 3.9% and 9.7%. Plant density was observed to vary between 63.63% and 75.30% in the GSIs at the MSU campus, potentially attributable to the different types of GSI, varying facility ages, and inadequate maintenance. Normalized difference vegetation index (NDVI) maps and scales of two GSIs were also generated to evaluate plant health. The NDVI and plant density results can be used to suggest where new plants can be added and to provide proper maintenance to achieve proper functions within the GSIs. This study provides a framework for evaluating plant performance within the GSIs using the collected UAV-based imagery. green stormwater infrastructure (GSI); unmanned aerial vehicle (UAV); plant density; plant health; images +
Footnote †: journal: _Sciences_  
and natural processes. GSIs have numerous environmental, social, and economic benefits, including stormwater-runoff reduction [4], air-quality improvement [5], heat-island-effect reduction [6], carbon storage and sequestration, resilience of drainage-system improvement, pollutant reduction, water-quality improvement, urban beautification, land-value increment, and energy-demand reduction [4; 5; 6; 7]. Consequently, there is a global surge in interest and implementation of GSIs aimed at mitigating adverse impacts such as flooding, waterway contamination, and stream degradation. This is achieved by disconnecting the expanding impervious surfaces such as pavements and rooftops in the cities from the storm sewer systems [7; 8; 9]. Plants play an integral part and multifaceted role within GSIs and contribute to various environmental, ecological, and aesthetic functions. A modeling study using hourly meteorological and pollution concentration data from across the US demonstrate the substantial air-pollution-removal capacity of urban trees for pollutants such as O\({}_{3}\), NO\({}_{2}\), SO\({}_{2}\), and CO, thereby enhancing urban air quality [10]. Additionally, vegetation is widely acknowledged as a particulate matter (PM)-removal solution in cities, taking various forms of green infrastructure [11]. Plants contribute to the improvement of runoff quality by removing nutrients (nitrogen and phosphorus), heavy metals, total suspended solids (TSSs), pathogens, emerging contaminants, and organic pollutants. They also enhance hydrological performance by preventing substrate clogging, mitigating stormwater volume infiltration and evapotranspiration, mitigating erosion, and influencing preferential flow paths [12; 13].