NH53A-02
Next Generation UAV Based Spectral Systems for Environmental Monitoring: project developments, preliminary outcome and findings

Friday, 18 December 2015: 13:55
309 (Moscone South)
Petya K. E. Campbell1, Philip A Townsend2, Daniel Mandl3, Vuong T Ly3, Clayton Kingdon2 and Robert Allen Sohlberg4, (1)UMBC, Greenbelt, MD, United States, (2)University of Wisconsin Madison, Forest and Widlife Ecology, Madison, WI, United States, (3)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (4)University of Maryland, College Park, MD, United States
Abstract:
This investigation contributes for bridging the gap in Earth observation between field and airborne measurements. We will reduce the risk of operating science grade instruments from Unmanned Aerial Systems (UAS), by developing robust methods to make well-characterized spectral measurements for integration, calibration and validation with NASAs science quality satellite and airborne data. Because of the potential for rapid deployment, spatially explicit data from UASs can be acquired irrespective of many of the cost, scheduling and logistic limitations to satellite or piloted aircraft missions. Provided that the measurements are suitably calibrated and well characterized, this opens up opportunities for calibration/validation activities not currently available. There is considerable interest in UASs from the agricultural and forestry industries but there is a need to identify a workflow that yields calibrated comparisons through space and time. The goal of our effort is to ensure that optical high spectral resolution measurements from UAV’s are collected and processed in a fashion that allows ready integration with or comparison to NASA satellite and airborne data and derived products. We target the consistent retrieval of calibrated surface reflectance, as well as biological parameters including nutrient and chlorophyll content, chlorophyll fluorescence and photosynthetic capacity. We will test our technology and protocols first using spatially-resolved discrete point measurements characterizing canopy VNIR reflectance and solar-induced fluorescence, followed by imaging spectroscopy. A Rapid Data Assimilation and delivery system will be developed, based on SensorWeb Intelligent Payload Module for high speed onboard processing. The deployment of UAS sensors at sites such as flux towers will facilitate measrurement validation and parameter retrieval, than is possible by foot, from sensors fixed to a tower, or irregular aircraft missions. We will report preliminary results and outcomes in the project development regarding the accurate measurement of spectral reflectance at high temporal frequencies and stability to depict diurnal/seasonal cycles in vegetation function.