Remote Sensing for Precision Agriculture
The UWRL is a leader is creating scientific applications that rely on remotely sensed data from both satellites and unmanned aerial vehicles. These applications are vast and varied, but one area that is showing incredible value is precision agriculture. Our researchers are engaged in cutting edge projects designed to marshal these technologies in ways that bring actionable data to farmers and water managers on the ground and in the field.
Various locations throughout the western United States
ARS, Gallo, NASA, Utah Dept. of Water Resources, and many others
Remote sensing data has come a long way over the past few decades and has great potential, through integration into precision agriculture, to increase both productivity and the efficient use of resources and decrease farm costs. However, in many cases, farmers, producers, and water managers still base their decisions on factors like water share amounts, tradition, and past experience. These factors are not necessarily related to the actual crop water use and they are used because related information cannot be provided in a timely manner and in an adequate format. The projects highlighted here are only a few of those underway at the UWRL that are developing the means to deliver continuous and personalized information about crop requirements to farmers/producers/water managers at various levels from crop fields to irrigation systems to watersheds and basins.
The Crop and Water Monitoring and Information System (CWMIS) is a new decision support system (DSS) platform that addresses the absence of information about actual crop water requirements and crop performance by providing continuous updated farm-based crop water use along other farm performance indicators such as crop yield and farm management to irrigators and water managers. This resource, available on the internet and accessible via cell phone, exploits the periodicity of the Landsat Satellite Mission (8 to 16 days, depending on the year), to provide remote monitoring at individual farm and irrigation system levels. The Landsat satellite images are converted into information about crop water use, yield performance and field management by use of state-of-the-art semi-physical and statistical algorithms that provide this information at pixel basis that ultimately are aggregated to farm and irrigation system levels. A version of the CWMIS has been implemented for the agricultural lands in the Lower Sevier River, Central Utah, and has been operational since the beginning of the 2013 irrigation season. The main goal is to provide continuous and personalized information to farmers and water managers regarding crop fields and irrigation system along the irrigation season, so decisions related with agricultural water use can ultimately provide water savings while improving or not negatively affecting.crop yield rates.
E&J Gallo Vinery Project with ARS-USDA
UWRL researchers are employing the AggieAir umanned aerial remote sensing aircraft over wine grape vineyards in California to provide a number of data products useful to growers. One such application is the ability to determine the health of individual vines based on their leaf canopy volume The AggieAir group has developed software that uses the remotely sensed imagery in the visual and near infrared spectra to automatically identify and very precisely geolocate each individual vine in the vineyard. This software uses the DEM and point cloud data derived from the orthorectification process to automatically estimate the leaf canopy volume of each individual vine. As is evident from the image below, the estimated canopy volume for the vines in this small example area
ranges from zero to about five cubic meters. A vine that has zero cubic meters of canopy volume at this stage of growth is dead. Growers typically do not know how many dead vines they have and, in general, only know the location of dead vines that are close to the road. Data from a single UAV flight can provide information to the grower about the precise number of dead vines that are contained in a vineyard and about their precise location, allowing the grower to send in a crew to replace the dead vines with living stock when the number of dead vines is sufficient to justify the marshaling costs, etc. Moreover, such analyses can be made for a vineyard each year, and growers can discover patterns through time seek out the causes of the problem. This type of information can also be used for yield forecasting. This is an example of the sort of potentially valuable product that can be generated from DEMs, point clouds, and, most importantly, tight orthorectification.
Looking to the Future
A new project is just getting started in which UWRL faculty member Alfonso Torres-Rua and Larry Hipps from the department of Plants, Soils and Climate at USU will be creating statewide models with daily estimates of plant water consumption across several states for agricultural basin scale water management toward the end of 2017. The states involved will be Utah, Wyoming, Colorado, Arizona, and New Mexico.
Benefits to Utah
Remote sensing is an emerging technology with incredible economic potential. The UWRL is becoming well known for their expertise in remote sensing technology and processes in the area of precision agriculture. Additionally, since approximately 85% of Utah's water is allocated to agricultural uses, the results of these research projects has the potential to benefit Utah farmers and water managers both directly and indirectly.
New NASA / Gallo Grant
The AggieAir team was recently awarded a grant through the NASA ROSES program to greatly expand their work with ARS and Gallo.
AggieAir is a scientific-grade remote sensing system developed at the UWRL. Learn more here
Other Water Resources Engineering Project Highlights:
Integrated Cyberinfrastructure Development and Data Collection
Impacts of Climate Change on Arctic Rivers & Streams
Aquifer Saline Injection in Utah's Uintah Basin
Managing Water to Improve Wetland Functions & Ecosystems
Cyberinfrastructure for Intelligent Water Supply