Title :
Wheat cycle monitoring using radar data and a neural network trained by a model
Author :
Frate, F. Del ; Ferrazzoli, P. ; Guerriero, L. ; Strozzi, T. ; Wegmüller, U. ; Cookmartin, G. ; Quegan, S.
Author_Institution :
DISP, Tor Vergata Univ., Rome, Italy
Abstract :
An algorithm, based on an electromagnetic model and a neural network, aimed at monitoring the multitemporal evolution of wheat fields, is described. Three different sites are used to validate the model, provide reference ground data, and test the algorithm.
Keywords :
agriculture; geophysical signal processing; geophysical techniques; neural nets; radar imaging; remote sensing by radar; synthetic aperture radar; vegetation mapping; Avignon; Driffield; England; SAR; Triticum; UK; agriculture; algorithm; crops; electromagnetic model; growth cycle; measurement technique; model; monitoring; neural net; neural network; radar remote sensing; synthetic aperture radar; training; vegetation mapping; wheat; wheat fields; Biomass; Crops; Electromagnetic modeling; Electronic mail; Monitoring; Neural networks; Soil; Spaceborne radar; Testing; Vegetation;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1025080
