Modelling Uncertainty of Stream Networks Derived from Elevation Data Using Two Free Softwares: R and SAGA - Observatoire des Sciences de l'Univers de Rennes Accéder directement au contenu
Article Dans Une Revue Journal of Geographic Information System Année : 2012

Modelling Uncertainty of Stream Networks Derived from Elevation Data Using Two Free Softwares: R and SAGA

Résumé

Stream networks are considered important units in many environmental decision making processes. The extraction of streams using digital elevation models (DEMs) presents many advantages. However it is very sensitive to the uncer-tainty of the elevation datasets used. The main aim of this paper is to implement geostatistical simulations and assess the propagated uncertainty and map the error of location streams. First, point sampled elevations are used to fit a variogram model. Next two hundred DEM realizations are generated using conditional sequential Gaussian simulation; the stream network map is extracted for each of these realizations, and the collection of stream networks is analyzed to quantify the error propagation. At each grid cell, the probability of the occurrence of a stream and the propagated error are estimated. The more probable stream network are delineated and compared with the digital stream network derived from topographic map. The method is illustrated using a small dataset (8742 sampled elevations) for Anaguid Saharan platform. All computations are run in two free softwares: R and SAGA. R is used to fit variogram and to run sequential Gaussian simulation. SAGA is used to extract streams via RSAGA library.
Fichier principal
Vignette du fichier
JGIS20120200010_78489235.pdf (1.69 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

insu-00789933 , version 1 (07-05-2021)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Hammadi Achour, Noamen Rebai, Jean van den Driessche, Samir Bouaziz. Modelling Uncertainty of Stream Networks Derived from Elevation Data Using Two Free Softwares: R and SAGA. Journal of Geographic Information System, 2012, 4, pp.153-160. ⟨10.4236/jgis.2012.42020⟩. ⟨insu-00789933⟩
93 Consultations
30 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More