Télédétection et ressources en eau/Remote sensing and water resources
25
knowledge of the environment and of surface quantification of specific parameters are easily
understood. A lot of hopes are also vested in the use of GIS for the integrated management of
spatial data. On the other hand, the associated models are still at the research stage.
The applicability of these approaches is in fact highly variable and can be judged through a
number of criteria such as:
• region of application (the value increases in little or poorly known environments);
• previous thematic knowledge for validation (importance of field measurements and of
observation on experimental watersheds);
• the required precision, determined by the objective of the application;
• the ease of application (simple vs. complex, operational vs. research);
• combined use of remote sensing, GIS and of classic information sources.
Methodological bottlenecks
The difficulties of using these new tools and these new data appear less and less connected to the
techniques themselves. Through the spectacular evolution of these tools, of numeric data and of
available software, cartography and numerical analysis have experienced a remarkable
development. Digital maps produce documents of proven quality and with such improvements to
cause a growing unbalance between techniques and conceptualization. The main problem is not
the production of maps, but their analysis, their use and their interpretation for thematic
objectives.
The use of remote sensing and of GIS for the study of water resources makes it possible to
integrate elements of the landscape into calculation algorithms in an increasingly detailed fashion.
Their efficient use cannot be obtained other than with a schematization of reality. Nowadays, the
main problems reside in this schematization or modelization. It is now essential to orient research
on the utilization of space through the notion of objects and the relationship between objects.
As far as remote sensing per se is concerned, the improvement in utilization should not only
be expected from an improvement in the technical characteristics (for example better resolution),
but also from a better use of the available information. Often the potential resolution becomes too
fine in relation to the objective and it might be useful to accept some degradation of the image in
order to obtain the desired results. The search for the optimal resolution, in relation to the
objective of the study should be a more fundamental and systematic preoccupation and become a
prerequisite of each application.
Many applications start from the idea that is possible to delimit areas that have
homogeneous hydrological behaviours. The difficulties reside not only in tracing the boundaries
of these areas but also in their definition. In fact, it is not easy to choose the criteria to be used for
the definition of these zones, knowing that homogeneity does not correspond to reality. So, it is
possible to match each type of image with a segmentation of space based upon homogeneous
units defined by visual characteristics, but the segmentation of space should also have a
functional meaning related to the studied processes.
On the other hand, the ease of image processing software and of associated applications
presents a certain danger. It is now possible to classify images in an anarchic fashion, without
field checks, without control or relation to the thematic objective. It is possible to rapidly
25
knowledge of the environment and of surface quantification of specific parameters are easily
understood. A lot of hopes are also vested in the use of GIS for the integrated management of
spatial data. On the other hand, the associated models are still at the research stage.
The applicability of these approaches is in fact highly variable and can be judged through a
number of criteria such as:
• region of application (the value increases in little or poorly known environments);
• previous thematic knowledge for validation (importance of field measurements and of
observation on experimental watersheds);
• the required precision, determined by the objective of the application;
• the ease of application (simple vs. complex, operational vs. research);
• combined use of remote sensing, GIS and of classic information sources.
Methodological bottlenecks
The difficulties of using these new tools and these new data appear less and less connected to the
techniques themselves. Through the spectacular evolution of these tools, of numeric data and of
available software, cartography and numerical analysis have experienced a remarkable
development. Digital maps produce documents of proven quality and with such improvements to
cause a growing unbalance between techniques and conceptualization. The main problem is not
the production of maps, but their analysis, their use and their interpretation for thematic
objectives.
The use of remote sensing and of GIS for the study of water resources makes it possible to
integrate elements of the landscape into calculation algorithms in an increasingly detailed fashion.
Their efficient use cannot be obtained other than with a schematization of reality. Nowadays, the
main problems reside in this schematization or modelization. It is now essential to orient research
on the utilization of space through the notion of objects and the relationship between objects.
As far as remote sensing per se is concerned, the improvement in utilization should not only
be expected from an improvement in the technical characteristics (for example better resolution),
but also from a better use of the available information. Often the potential resolution becomes too
fine in relation to the objective and it might be useful to accept some degradation of the image in
order to obtain the desired results. The search for the optimal resolution, in relation to the
objective of the study should be a more fundamental and systematic preoccupation and become a
prerequisite of each application.
Many applications start from the idea that is possible to delimit areas that have
homogeneous hydrological behaviours. The difficulties reside not only in tracing the boundaries
of these areas but also in their definition. In fact, it is not easy to choose the criteria to be used for
the definition of these zones, knowing that homogeneity does not correspond to reality. So, it is
possible to match each type of image with a segmentation of space based upon homogeneous
units defined by visual characteristics, but the segmentation of space should also have a
functional meaning related to the studied processes.
On the other hand, the ease of image processing software and of associated applications
presents a certain danger. It is now possible to classify images in an anarchic fashion, without
field checks, without control or relation to the thematic objective. It is possible to rapidly