A Pilot Study to Explore the Possibility of Combining Field and Remotely Sensed Data for Agricultural Resources Management

Abstract

Soil moisture and temperature are important measures of soil productivity, but monitoring agricultural stresses such as water shortage and extreme temperature at large scale farming can be difficult. This research is a pilot study conducted on a research plot to explore the possibility of utilizing both field data and remotely sensed data for agricultural management. The DJI Inspire 1 drone was used to collect aerial images of the plot while Davis soil moisture and temperature station was used to collect field measurements from the plot. Results from the study show field data on soil moisture and temperature can provide insights on to movement of soil water and remotely sensed data such as aerial images and digital surface models can be used to quantify crop conditions with normalized difference vegetation index (NDVI) Such combination of on-ground and off-ground data could provide a holistic approach to observe field conditions and crop health that allows monitoring crops throughout growth and development cycle and planning for optimal harvest.