Application of Machine Learning Methods and Airborne Hyperspectral Remote Sensing for Crop Yield Estimation.POMPES PAR TRANSITIONS MULTIPLES

منو

" Application of Machine Learning Methods and Airborne Hyperspectral Remote Sensing for Crop Yield Estimation.POMPES PAR TRANSITIONS MULTIPLES "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	153837
Doc. No	:	ET25629
Main Entry	:	Yoji Uno
Title Proper	:	Application of Machine Learning Methods and Airborne Hyperspectral Remote Sensing for Crop Yield Estimation.POMPES PAR TRANSITIONS MULTIPLES
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Accurate description of within-field crop yield variability is one of the greatest concernsin precision agriculture. This study investigated the potential of developing in-seasoncrop yield forecasting and mapping systems based on interpretation of airbornehyperspectral remote sensing imagery by machine learning algorithms. The data used forthis study was obtained over a corn (Zea mays L.) field in eastern Canada..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL49894.pdf
Title and statement of responsibility and	:	Application of Machine Learning Methods and Airborne Hyperspectral Remote Sensing for Crop Yield Estimation.POMPES PAR TRANSITIONS MULTIPLES [Thesis]