Determining plant productivity using remote sensing method
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Abstract
This project seeks to assess plant productivity and health in time and space by measuring spectral reflectance from soybean canopies using remote sensing methods that do not require ground assessment. Aerial images and reflectance measurements from a multi-spectral radiometer were obtained simultaneously from a soybean field located in Story County, Iowa. The multi-spectral radiometer has eight wavelength bands, ranging from 460-nm to 810-nm and was used as a ground reference for the data analysis. Aerial images were obtained from altitudes ranging from 152 to 427 meters above the ground during the 2000 growing season. Aerial images were analyzed using the software programs: Matlab[Registered Trademark Symbol], ArcView[Registered Trademark Symbol] and Imagine[Registered Trademark Symbol]. Difficulties in image analysis and interpretation may occur as the sensing equipment increases in altitude; this is because atmospheric influences become more pronounced. Scattering and absorption of electromagnetic waves in the atmosphere change the spectrum of the reflectance from the plants as it propagates from the plants to the sensors. Color calibration procedures were used with red, green and blue ground cloths to correct aerial images in the respective red, blue and green bands. Regression analysis was carried out to quantify the relationships between multi-spectral radiometer data and aerial image data.