Lead Researcher: Dilruba Yeasmin, Fayzul Pasha, Charles Hillyer
Contact: Dilruba Yeasmin
Industry Partner: WiseConn USA, Irrometer
In 2013, California growers from 18 counties responded to a survey on their perceived changes in irrigation water use due to adopting precision agriculture technology such as soil moisture sensors as part of a study conducted by CIT, and Fresno State, funded by PG&E. That study indicated significant opportunities to improve irrigation efficiency by adopting technology such as soil moisture sensors. In that context, this project proposes a remote sensing approach to evaluate crop water status in the orchards of the same counties in California. While UAV based imageries can provide real-time data on crop water status, long term and large scale monitoring are possible through free of cost satellite imageries, even some cases readily available vegetation indices datasets such as NDVI’s. Few examples are MODIS-NDVI through USGS Earth Explorer, Sentinel multispectral image, Landsat, AVHRR, etc. Different field measurements for available water in plants like stem water potential, leaf water content are time consuming and cover a small area. With the launch of Landsat1 in 1972, agricultural monitoring by satellite imageries started (Leslie, R. et al. 2017). Utilizing satellite imageries, this project will analyze crop water status in critical summer months from 2017 to 2019 for all major fruit and nut orchards (cropland data layer, USDA). Orchards that are frequently facing water stress issues (consistently shows low values for vegetation indices such as NDVI, EVI, etc.) will be identified. A survey will be conducted among growers of those areas to explore if they are adopting any precision agriculture technology. With geocoding and spatial analysis “no-precision-technology” orchards can be identified from the survey responses. Geo-spatial analysis using satellite imageries and survey output will generate final products as series of datasets, maps, and tables that are helpful to identify orchards where irrigation water management can be improved through the adoption of precision agriculture technology.