Unmanned aerial vehicles (UAV) have been increasingly used for field data collection and remote sensing purposes. Their ease of use, ability to carry sensors and cameras, low cost, and precise maneuverability and navigation makes them a versatile tool for a field researcher. Procedures and instrumentation to use UAVs in the field are largely undefined, especially for atmospheric and hydrologic applications. A field study was conducted to test the UAV’s ability to collect atmospheric data in order to locate and analyze the canopy boundary layer (CBL) above a Costa Rican tropical montane rainforest. This study aims to give further insight on the changes of the CBL throughout the day and for atmospheric comparison to land development. Through the study, it was found that there was little previously defined procedures and preferred instrumentation that directly applied to the UAV field study. Because of this, the methodology of using an UAV for atmospheric and CBL remote sensing and data collection was developed and refined by testing and comparing precision and performance of sensors and executing systematic flight patterns throughout the day. The UAV allowed for quick and specific access to sampling locations and for all of the variables to be measured by sensors over vertical profiles. Flights were scheduled at different locations throughout the day over the Texas A&M Soltis Center and surrounding forest in San Isidro, Costa Rica. Vertical profiles were also measured over the Soltis Center grounds to determine how development has affected the presence of the CBL. The UAV was successful in gathering data above the forest canopy and the Soltis Center at varying elevations during clear and cloudy conditions. The procedure produced reliably consistent vertical profiles over small domains in space and time, validating the general approach. The technique also identified unique profiles at spatially and temporally distinct sample sites including response to meteorological events. These findings suggest a healthy ability to diagnose CBL characteristics of interest. It was also found that there is a distinct increase in temperature and dew point over land development when compared to over forest. Future studies include flights at other locations and determining preferred instrumentation for UAV atmospheric data collection.

In tropical rainforests, large-scale deforestation is considered one of the biggest threats to the environment. This threat has been shown to contribute to a loss of biodiversity, carbon storage, and hydrological services such as erosion control, streamflow regulation, and water quality. Interception losses are a much higher proportion of the water budget in areas such as moist tropical forests, where precipitation can exceed 3000 mm per year. Given interception is higher in forests with large canopy storage capacity than low stature vegetation, we aimed to identify the relative differences in leaf wetness duration in Costa Rican premontane forest and adjoining cropland. Biomass alone determines maximum interception storage, but does not determine interception loss, since storage can saturate with relatively small rain events. We aimed to determine if leaf wetness duration (LWD) is positively correlated with interception. Forest leaves stayed wet five times longer than the crop fields, 487 ± 41 minutes compared to 94 ± 37 minutes. Within crop species, papaya took twice the time to dry than taro and sweet potato (137 ± 51 in contrast to 73 ± 23 minutes). Crop heights were well correlated with dry-down rates (r2 = 0.98). These results suggest the possibility of higher runoff and alteration of rainfall recycling in the humid tropics, following tropical forest conversion to cropland.