Location: Water Management Research2011 Annual Report
1a. Objectives (from AD-416)
To develop algorithms relating remotely sensed canopy cover to basal crop coefficients and software for conversion of remote sensing images to crop coefficient maps.
1b. Approach (from AD-416)
Canopy ground cover of various crops from the west side of the San Joaquin Valley will be derived from Landsat and/or other multispectral images collected under acceptably clear weather conditions. Image analyses will be required to process these data. Correlation between the satellite based canopy cover data and basal crop coefficient will be made and algorithms established on crop specific bases. A prototype user interface program will be developed to facilitate the translation of the satellite imagery to canopy cover or crop coefficient maps based on the relationships and algorithms developed in the previous phases of the project. An economic analysis will also be carried out to compare cost and benefit of employing remote sensing for improving crop water use efficiency.
3. Progress Report
This Grant Agreement supports Objective 1 of the parent project. The ability to estimate crop evapotranspiration (ET) with remotely-sensed data contributes to efficient management decisions by irrigation managers with information to help them schedule irrigation water deliveries and applications. During this project period, Landsat-5 Thematic Mapper terrain-corrected images were atmospherically corrected to surface reflectance via the Landsat Ecosystem Disturbance Adaptive Processing System, and converted to normalized difference vegetation index (NDVI) on a per-pixel basis. The normalized difference vegetation index values were converted to crop fractional cover based on an equation developed earlier in this project. Results were presented at the 5th National Decennial Irrigation Conference and the American Geophysical Union fall meeting in December 2010. The satellite-based NDVI approach, as implemented in regions with an available ETo network, potentially enables timely estimation of biological crop water demand for resource monitoring, evaluation of irrigation efficiencies, and scheduling of irrigation events. The project is monitored by the lead scientist via email and telephone communications, and face-to-face meetings with the cooperator.