Chapter 3
SPACE AND EARTH REMOTE SENSING
GIS Application to Environmental
Impact Studies
ENVIRONMENTAL IMPACT ANALYSIS USING
REMOTELY SENSED DATA
Piero BOCCARDO
Dipartimento di Georisorse e Territorio Politecnico di Torino, C.so Duca degli
Abruzzi, 24, 10129 Torino, Italy
ABSTRACT
This paper presents results from an activity undertaken at the Dipartimento di
Georisorse e Territorio - Politecnico di Torino, to analyze remotely sensed data in
order to generate thematic maps suitable for environmental impact studies. The
aim is to identify optimal procedures and methodologies, from data acquisition,
through to the final restitution of the product. Several types of data were processed
and different algorithms were implemented in order to compare their
performances. These methods were then used to classify digital images acquired at
different times of the year and in different locations. Particular attention was paid
to the elaboration of a new multi spectral digital image analysis capable of
standardizing the procedures used for the different problems studied. This
standard analysis includes: remotely sensed data acquisition, pre-elaboration of
data, spectral signature extraction, definition of the training samples, fully
automated and/or supervised classification and thematic map generation and
editing. Three different case-studies are presented here: (i) an experimental test to
C. Bardinet et al. (eds.), Geosciences and Water Resources: Environmental Data Modeling
© Springer-Verlag Berlin Heidelberg 1997
SPACE AND EARTH REMOTE SENSING
GIS Application to Environmental
Impact Studies
ENVIRONMENTAL IMPACT ANALYSIS USING
REMOTELY SENSED DATA
Piero BOCCARDO
Dipartimento di Georisorse e Territorio Politecnico di Torino, C.so Duca degli
Abruzzi, 24, 10129 Torino, Italy
ABSTRACT
This paper presents results from an activity undertaken at the Dipartimento di
Georisorse e Territorio - Politecnico di Torino, to analyze remotely sensed data in
order to generate thematic maps suitable for environmental impact studies. The
aim is to identify optimal procedures and methodologies, from data acquisition,
through to the final restitution of the product. Several types of data were processed
and different algorithms were implemented in order to compare their
performances. These methods were then used to classify digital images acquired at
different times of the year and in different locations. Particular attention was paid
to the elaboration of a new multi spectral digital image analysis capable of
standardizing the procedures used for the different problems studied. This
standard analysis includes: remotely sensed data acquisition, pre-elaboration of
data, spectral signature extraction, definition of the training samples, fully
automated and/or supervised classification and thematic map generation and
editing. Three different case-studies are presented here: (i) an experimental test to
C. Bardinet et al. (eds.), Geosciences and Water Resources: Environmental Data Modeling
© Springer-Verlag Berlin Heidelberg 1997