Sixteen years ago, Franklin estimated that about 80% of data contain geo-referenced
information. To date, the availability of geographic data and information is growing,
together with the capacity of users to operate with IT tools and instruments. Spatial
data infrastructures are growing and allow a wide number of users to rely on them.
This growth has not been fully coupled to an increase of knowledge to support spatial
decisions. Spatial analytical techniques, geographical analysis and modelling methods
are therefore required to analyse data and to facilitate the decision process at all
levels. Old geographical issues can find an answer thanks to new methods and instruments,
while new issues are developing, challenging researchers towards new solutions.
This volume aims to contribute to the development of new techniques and methods
to improve the process of knowledge acquisition.
Sixteen years ago, Franklin estimated that about 80% of data contain geo-referenced
information. To date, the availability of geographic data and information is growing,
together with the capacity of users to operate with IT tools and instruments. Spatial
data infrastructures are growing and allow a wide number of users to rely on them.
This growth has not been fully coupled to an increase of knowledge to support spatial
decisions. Spatial analytical techniques, geographical analysis and modelling methods
are therefore required to analyse data and to facilitate the decision process at all
levels. Old geographical issues can find an answer thanks to new methods and instruments,
while new issues are developing, challenging researchers towards new solutions.
This volume aims to contribute to the development of new techniques and methods
to improve the process of knowledge acquisition. The Geocomputational expression
is related to the development and the application of new theories, methods and tools
in order to provide better solutions to complex geographical problems.
