Event Title

Estimating Water Use and Yield of Potatoes Using Remotely Sensed Inputs

Presenter Information

Saravanan Sivarajan

Location

ECC 216

Event Website

https://water.usu.edu/

Start Date

3-31-2008 7:00 PM

End Date

3-31-2008 7:05 PM

Description

Multispectral aerial and satellite remote sensing in recent years have proved to be effective tools in assessing and monitoring crop biophysical data namely vegetation development, photosynthetic activity, biomass accumulation, crop evapotranspiration and crop yield prediction. High resolution aerial and satellite data can be used to improve crop yield models in the areas of soil and crop growth variability and their impact on crop water use and yield. This paper describes the use of high-resolution multispectral aerial remote sensing in validating and extending an existing statistical vegetation index yield model developed for potato crop. Spot yield samples collected from potato fields in the year 2005 will be used in testing the existing model. Each yield sample was identified based on soil and crop growth patterns in the study field and has the size of 3.63m by 3.03m. Soil adjusted vegetation index (SAVI) obtained from the remotely sensed overflights on three different dates will be integrated over the season and used in the existing model to obtain estimated yield to be compared with actual yield. Most of the studies involving crop yield predictions are done assuming there is no water stress on the fields. Water stress in the fields is a major factor that affects the yield and it’s directly related to crop evapotranspiration. So as a method to improve the yield estimate, the study also will involve estimating actual evapotranspiration using remotely sensed inputs and weather data, modeling the soil water balance in the root zone of the crop and incorporating actual ET in the yield model to improve model predictions.

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Mar 31st, 7:00 PM Mar 31st, 7:05 PM

Estimating Water Use and Yield of Potatoes Using Remotely Sensed Inputs

ECC 216

Multispectral aerial and satellite remote sensing in recent years have proved to be effective tools in assessing and monitoring crop biophysical data namely vegetation development, photosynthetic activity, biomass accumulation, crop evapotranspiration and crop yield prediction. High resolution aerial and satellite data can be used to improve crop yield models in the areas of soil and crop growth variability and their impact on crop water use and yield. This paper describes the use of high-resolution multispectral aerial remote sensing in validating and extending an existing statistical vegetation index yield model developed for potato crop. Spot yield samples collected from potato fields in the year 2005 will be used in testing the existing model. Each yield sample was identified based on soil and crop growth patterns in the study field and has the size of 3.63m by 3.03m. Soil adjusted vegetation index (SAVI) obtained from the remotely sensed overflights on three different dates will be integrated over the season and used in the existing model to obtain estimated yield to be compared with actual yield. Most of the studies involving crop yield predictions are done assuming there is no water stress on the fields. Water stress in the fields is a major factor that affects the yield and it’s directly related to crop evapotranspiration. So as a method to improve the yield estimate, the study also will involve estimating actual evapotranspiration using remotely sensed inputs and weather data, modeling the soil water balance in the root zone of the crop and incorporating actual ET in the yield model to improve model predictions.

https://digitalcommons.usu.edu/runoff/2008/Posters/5