Introduction. 
The aim of this work is to characterize some individuals from 
different arboreal species starting from data obtained by a digi 
tized false colour image (Fig. 1). 
The proposed thesis is that the characterization of an indivi 
dual which belongs a certain species does not depend only on cha 
racteristics discernable through pseudospectral behaviour but ca 
n also take place on the basis of morphological and morphometric 
characteristics of both the individual and the scene to which it 
belongs. 
This work illustrates the first results of an exploratory ana 
lysis aimed at defining some features which characterize the ind 
ividuals of some species of interest and the line which will be 
followed for the use of the morphological and morphometric chara 
cteristics of scene. 
These characteristics have a precise algorithmic form, and 
thus constitute the necessary basis for a possible automatizatio 
n of the system. 
l. Exploratory analysis. 
By exploratory analysis of data we mean a mathematical handli 
ng of data with the aim of finding out indication that may serve 
as hints in approaching further data. 
The indication obtained allows the user (in this case the re 
mote sensing user) to decide whether they are significative with 
respect to the system observed and the experiment under way or 
whether, to the contrary, they are to be judged as pure formal 
accidents. 
Our analysis aims at gathering indications relative to charac 
teristics or to combinations of characteristics of a structural 
and morphological nature able to help characterize an individual 
as belonging to a particular arboreal species. 
1.1 Pseudospectral analysis. 
By pseudospectral analysis we mean that sort of analysis whi 
ch is carried out with the classic criteria of multispectral ana 
lysis, but starting out with data obtained with a spectral conve 
rsion. 
The typical case is that -adopted here- in which an analysis 
is made of the chromatic components of an object as they emerge 
from a false colour image, these being handled as though they we 
re true and proper spectral bands, despite the fact that a trans 
fer function has been introduced into the image recording system. 
The type of spectral analysis of the data undertaken involved 
the following phases: 
a) identifying of the co-ordinates of the areas of precise grou 
nd truth (training areas) 
b) acquiring three hystograms (blue, green, red) relative to the 
training area data