Title :
Estimation of tree species proportions of forest compartments using ranging scatterometer
Author :
Torma, Markus ; Hyyppa, Juha
Author_Institution :
Inst. of Photogrammetry & Remote Sensing, Helsinki Univ. of Technol., Espoo, Finland
Abstract :
Tree species proportions of forest stands were estimated using a ranging scatterometer called HUTSCAT. The employed estimation method was a multilayer perceptron neural network with error backpropagation training algorithm. Different methods based on intensity and/or shape of measured profiles were tested. The best classification accuracy of the main tree species was about 88% and the mean error of estimation for tree species proportions was 0.26
Keywords :
airborne radar; backpropagation; feature extraction; forestry; geophysical signal processing; image classification; multilayer perceptrons; radar imaging; remote sensing by radar; vegetation mapping; HUTSCAT; classification accuracy; error backpropagation training algorithm; estimation method; forest compartments; forest stands; intensity; multilayer perceptron neural network; ranging scatterometer; shape; tree species proportions; Backscatter; Chirp modulation; Laboratories; Materials testing; Radar measurements; Remote sensing; Shape measurement; Soil; Space technology; Spaceborne radar;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
DOI :
10.1109/IGARSS.1999.774437
