Vini's 2nd Ph.D. paper on monitoring on-farm reservoirs with multi-sensor satellite imagery is published in Remote Sensing of Environment

Mollie D. Gaines
Last updated on Oct 28, 2022 1 min read
From Figure 12 in the paper: “Sub-weekly surface area time series obtained from the Kalman filter for the study case OFRs (see Table 4) between January 2017 and December 2020. Gray shaded area represents +/− one and two standard deviations. The r2 and MAPE values were derived from the Kalman filter comparisons with the independent PS subset.”

“A multi-sensor satellite imagery approach to monitor on-farm reservoirs” was accepted to in Remote Sensing of Environment in November 2021.

Vini’s 2nd paper employed a novel algorithm based on the Kalman filter to comnine PlanetScope, RapidEye, Sentinel 2, and Sentinel 1 imagery to monitor the sub-weekly surface area of on-farm reservoirs. When the algorithm was applied across 736 on-farm reservoirs in eastern Arkansas, the resulting surface area time series had <5% error for most reservoirs.

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Bibliographic Citation

Perin, V., Tulbure, M. G., Gaines, M. D., Reba, M. L., & Yaeger, M. A.. 2022. A multi-sensor satellite imagery approach to monitor on-farm reservoirs. Remote Sensing of Environment, 270(112796). https://doi.org/10.1016/j.rse.2021.112796

Mollie D. Gaines
Mollie D. Gaines
PhD Candidate

I am a PhD student with the Center for Geospatial Analytics at North Carolina State University.