Abstract:

The advances in modeling the natural processes responsible for geographic processes are strongly related to the quality, availability and temporal and spatial scale of the data, such as in the cases of forests, benthic habitats, soil mapping and coastal features. They are generally studied by remote sensing techniques, analysis of statistical surveys, field data integrated with historical maps and satellite remote sensing, which is also valuable for providing cost-effective information. However, simpler, cheaper and more accessible sources of information would be of special interest for large-scale studies in which large areas are analyzed. Among other options, Google Earth has received much attention during last years. It hosts high-resolution imagery and allows the development of practical methods for studying the regions of interest in which a coarser resolution is insufficient. Google Earth has been recognized for its potential to significantly improve the visualization and dissemination of scientific data since its origin in the year 2005.

In this work, we describe our experience using Google Earth imagery to generate an extensive database of large-scale coastal features. In particular, we have focused our attention on:
(1) shoreline undulations (SU), which can be defined as medium to large spatial-scale shoreline features that have alongshore dimensions ranging from hundreds to thousands of meters and cross-shore widths ranging from tens to hundreds of meters; and
(2) embayed beaches, which are beaches bounded by human constraints or natural rocky coasts.

The resolution for the sites analyzed in this work was <1m/ pixel, although certain images had a resolution on the order of cm/pixel. During the conference, the methodology used to define the database will be presented, as well as the main results obtained after the application of data mining techniques to the information included in the database.

Moreover, the potential of using this type of studies and methodologies to introduce graduate students into research will be also discussed. In this work, students were the responsible for identifying the coastal features and extracting the geometrical and wave climate information from different sources. The supervisors checked their work, and they introduced them into the whole research processes: from the obtaining of the data and its treatment, to the dissemination of the results.

With our experience, we conclude that Google Earth has a sound potential as a new research tool, being the definition of databases a new research methodology of special interest for many Earth Sciences. Given it simplicity and low cost, it constitutes also a good method to introduce graduate student into research, since they can participate in all the research processes.

Keywords:

Database, Google Earth, Coastal features, Graduate students.