60
Chapter 7
reliability will be obtained from these data if and when they will be analyzed
with advanced models and inversion procedures. Another promising avenue
is to investigate further the feasibility and efficiency of merging two or more
data streams from various remote sensing sensors, when they can provide
complementary information (synergy).
Last but not least, all applications relying on the analysis of data
collected in the past will continue to have to rely on remote sensing data
from old platforms such as the NOAA/AVHRR, Landsat, or SPOT. These
sensors are quite unsatisfactory compared to today’s standards of quality and
to the level of expectation of the users, but they have generated the only
global data sets available over the last 15 years. A coherent and focused
research and development (R&D) program should be implemented to design
and use state of the art algorithms and models. In particular, such a program
should aim at compensating for the inadequacies of old sensors through the
intelligent use of up to date models and environmental information derived
from more recent instruments and fundamental research. The future
exploitation of remote sensing for disaster management thus largely relies on
our capacity to carry out R&D programs to improve existing techniques for
processing existing and future remotely sensed data and for retrieving the
needed information.
Chapter 7
reliability will be obtained from these data if and when they will be analyzed
with advanced models and inversion procedures. Another promising avenue
is to investigate further the feasibility and efficiency of merging two or more
data streams from various remote sensing sensors, when they can provide
complementary information (synergy).
Last but not least, all applications relying on the analysis of data
collected in the past will continue to have to rely on remote sensing data
from old platforms such as the NOAA/AVHRR, Landsat, or SPOT. These
sensors are quite unsatisfactory compared to today’s standards of quality and
to the level of expectation of the users, but they have generated the only
global data sets available over the last 15 years. A coherent and focused
research and development (R&D) program should be implemented to design
and use state of the art algorithms and models. In particular, such a program
should aim at compensating for the inadequacies of old sensors through the
intelligent use of up to date models and environmental information derived
from more recent instruments and fundamental research. The future
exploitation of remote sensing for disaster management thus largely relies on
our capacity to carry out R&D programs to improve existing techniques for
processing existing and future remotely sensed data and for retrieving the
needed information.