A New Unmanned Aircraft System-Assisted Optical Trapezoid Model for Soil Moisture Assessment
Abstract
In this poster we present the application of high spatiotemporal resolution unmanned aircraft systems (UASs) and satellite information for irrigation management in precision agriculture. A new trapezoidal space was developed from near infrared transformed reflectance (NTR) and normalized difference vegetation index (NDVI) data and used for estimation and mapping of root zone soil moisture (SM) and plant available water (PAW). The UAS data were used to assess spatial variability of SM and PAW at the farm scale, while satellite (VENμS and Sentinel-2) data were applied for generating effective values of SM and PAW. Results indicate that the NTR-NDVI model estimation accuracy varies with soil depth with the highest accuracy obtained for the near-surface soil layer. The high spatial resolution SM and PAW maps enable crop producers to increase water productivity by applying water more precisely and site specifically to match soil and crop status, and to minimized negative effects on crop yield. Integration of high resolution SM and PAW maps with automated pressurized drip or sprinkler systems may facilitate irrigation scheduling in the future.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.B33F2723B
- Keywords:
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- 0402 Agricultural systems;
- BIOGEOSCIENCESDE: 0434 Data sets;
- BIOGEOSCIENCESDE: 0480 Remote sensing;
- BIOGEOSCIENCESDE: 1910 Data assimilation;
- integration and fusion;
- INFORMATICS