Keywords

gis, automatic modelling, interoperable web map

Start Date

1-7-2012 12:00 AM

Abstract

The Natural Processes Monitoring Team from the Doñana Biological Station (EBD), systematically acquires data on more than 100 indicators of ecological processes and the status of many fauna and flora species in Doñana National Park, one of the most important protected wetlands in Europe, covering 54000 Ha. This information is available on a website as tabular data and trend charts. A detailed analysis is necessary in order to interpret this information and provide decision-making criteria for the management of the natural area. The purpose of this paper is to improve public access to the information collected in the monitoring program and at the same time increase its quality. The proposed methodology integrates spatial interpolation methods, multivariate linear and logistic regression models (including the use of remote sensing images as predictors) and hybrid tools of these methodologies into a Geographic Information System (GIS) based model to generate predictive maps of ecological parameters. The information on the distribution, abundance, population structure and densities of different terrestrial and aquatic species, biophysical parameters and also their corresponding validation methodologies were used in the automatic generation of continuous maps of the distribution and abundance of the species in the study region.

COinS
 
Jul 1st, 12:00 AM

Automatic modelling and continuous map generation from georeferenced species census data in an interoperable GIS environment

The Natural Processes Monitoring Team from the Doñana Biological Station (EBD), systematically acquires data on more than 100 indicators of ecological processes and the status of many fauna and flora species in Doñana National Park, one of the most important protected wetlands in Europe, covering 54000 Ha. This information is available on a website as tabular data and trend charts. A detailed analysis is necessary in order to interpret this information and provide decision-making criteria for the management of the natural area. The purpose of this paper is to improve public access to the information collected in the monitoring program and at the same time increase its quality. The proposed methodology integrates spatial interpolation methods, multivariate linear and logistic regression models (including the use of remote sensing images as predictors) and hybrid tools of these methodologies into a Geographic Information System (GIS) based model to generate predictive maps of ecological parameters. The information on the distribution, abundance, population structure and densities of different terrestrial and aquatic species, biophysical parameters and also their corresponding validation methodologies were used in the automatic generation of continuous maps of the distribution and abundance of the species in the study region.