By Dr. Aditya Singh, August 31, 2018
This research is aimed at assisting the refinement and improvement of aerial mapping in agriculture to support irrigation management and improving water use efficiencies. In brief: small Unmanned Aerial Systems (sUAS) equipped with optical, multispectral and thermal sensors will be used to map three sod production farms to identify areas of potential under and over irrigation on a near-real time basis. A key output of this research will be the development of algorithms that translate data, such weather data and UAS imagery, into actionable information that can be used by growers to improve efficiency and profitability of their operations.
Growers and state water management agencies in Florida are looking towards new approaches for coordinating water resource and supply development and management to protect, conserve, and restore water resources while meeting water demands for urban, agricultural, and other needs. This approach includes continued work on increasing efficiency of water use to ensure sufficient water is available to meet various water needs, working directly with water management districts, and enacting water use policies in direct consultation and collaboration with farmers, stakeholders, and scientists. Therefore, there is a critical need to educate producers on new methodologies to improve efficiencies in irrigation. By targeting water use efficiencies with nutrient management as a secondary goal, this project is aimed at addressing the growing interest in utilizing integrative technologies from government agencies as well as individual growers and grower associations.
My lab specializes in developing remote sensing-based tool and techniques for assessing plant health, productivity, and responses to biotic and abiotic stresses at landscape scales. UAS are an emerging technology that may hold promise for a variety of applications in precision agriculture. While the use of sUAS and ground-based sensors is increasing, applications of such technologies for water conservation and improving agricultural production practices have not been adopted operationally. For example, while thermal imagery has been shown to be an important for determining water stress in a variety of tree and agronomic crops, comparisons of increases in efficiencies between irrigation schedulers using data from weather and soil moisture sensors and sUAS have not been conducted making this an active area of research.
For this project, we will work directly with three turfgrass producers in North-Central Florida. We will conduct aerial mapping in two to three-week intervals at each farm depending on rainfall events and irrigation schedules. Georeferenced map overlays will be generated from commercial implementations of image stitching routines that utilize information provided by image sensors. Concurrent with UAS image collection, we will obtain soil moisture readings from field-embedded sensors, and a portable soil moisture sensor will be used to measure soil moisture in areas identified as anomalies in sUAS imagery. Concurrent to sUAS flights, we will obtain spectral measurements over turfgrass canopies which will be sampled at regular intervals. In combination sUAS-borne thermal and multispectral imagery, ground-based canopy foliar spectrometry may help us concurrently monitor plant water use and foliar nutrient content. The aim being conserving water and minimizing nutrient runoff by targeting fertilizer application only to nutrient-deficit plants.
The overall long-term goal of this project is to reduce agricultural water demand and nutrient loading via improving irrigation efficiencies by conducting comparative assessments of increases in efficiencies brought about by employing sUAS imaging-based, in comparison to soil moisture sensing-based irrigation scheduling methods. A key output of this research will be the development of algorithms that translate data, such weather data and UAS imagery, into actionable information that can be used by growers to improve efficiency and profitability of their operations.
By targeting water use efficiencies with nutrient management as a secondary goal, this project will address the growing interest in utilizing integrative technologies from government agencies as well as individual growers and grower associations. This project expands on the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy goals to develop, adopt, and assist with the implementation of agricultural Best Management Practices to protect and conserve water resources pursuant to the Florida Watershed Restoration Act. The integrated approach used in this project will help producers manage water demand, while still achieving sustainable yields and minimizing fertilizer use. The interdisciplinary and field-based nature of this project will allow collaboration across departments, engagement of multiple stakeholders, and the leveraging of the University of Florida’s strong Extension and education networks to make practical adoption possible in a wide variety of cropping systems.
This project is a collaborative effort with turfgrass farmers, extension agents, and scientists at UF/IFAS ABE.
Dr. Aditya Singh is an Assistant Professor of Remote Sensing in the Department of Agricultural and Biological Engineering at the University of Florida. Dr. Singh specializes in the application of optical remote sensing science in support of landscape scale research on forest health, agricultural irrigation water management, assessment of pest and disease stress and occurrence, and food security in developing nations.