A belvízelöntések térképezését megalapozó adatgyűjtés és a belvízképződés modellezése neurális hálózattal

Collecte de données pour la représentation cartographique et la modélisation des excès d'eaux continentales à l'aide d'un reseau artificiel de drainage

Auteurs :
SZATMÁRI, J.
TOBAK, Z.
VAN LEEUWEN, B.
DOLLESCHALL, J.

Description :
Inland excess water is a recurring problem on the Great Hungarian Plain. Large tracts of land are covered with water due to a lack of runoff and insufficient absorption capability of the soil or upwelling of groundwater. Laser altimeter scanning (ALS) data and stereo aerial photographs were acquired from three different study areas in the Maros-Körös Interfluve. The ALS data and three dimensional vectors (breaklines) that were derived from aerial photographs were employed to create a 70 km2 digital elevation model (DEM), which incorporates natural landforms essential for inland excess water modeling and can not be identified on the DEM-5 model of Hungary. A framework has been developed to integrate the robust capabilities of a GIS for geographical analyses and of artificial neural networks to classify large, complex, non-linear datasets. The framework uses the DEM and GIS layers to identify inland excess water. - (AM)


Type de document :
Article de périodique

Source :
Földrajzi kõzlemények, issn : 0015-5411, 2011, vol. 135, n°. 4, p. 351-363, nombre de pages : 13, Références bibliographiques : 19 ref.

Date :
2011

Editeur :
Pays édition : Hongrie, Budapest, Magyar Földrajzi Társaság