Dasymetric modeling and uncertainty

Auteur(s) et Affiliation(s)

NAGLE, N.N.

Dept. of Geography, Univ. of Tennessee, Knoxville, Etats-Unis

BUTTENFIELD, B.P.

Dept of Geography , Univ. of Colorado, Boulder, Etats-Unis

LEYK, S.

Dept of Geography , Univ. of Colorado, Boulder, Etats-Unis

SPIELMAN, S.

Dept of Geography , Univ. of Colorado, Boulder, Etats-Unis

Description :
This article presents a new dasymetric methodology—the penalized maximum entropy dasymetric model that enables sources of uncertainty to be represented and modeled. It allows a rich array of data to be included, with disparate spatial resolutions, attribute resolutions, and uncertainties. It also allows a rich array of data to be included, with disparate spatial resolutions, attribute resolutions, and uncertainties. It concludes by presenting an application that that includes household-level survey data combined with higher spatial resolution data such as from census tracts, block groups, and land cover classifications in Davidson County, Tennessee.

Type de document :
Article de périodique

Source :
Annals of the Association of American Geographers, issn : 0004-5608, 2014, vol. 104, n°. 1, p. 80-95, nombre de pages : 16, Références bibliographiques : 2 p.

Date :
2014

Editeur :
Pays édition : Etats-Unis, Washington, DC, Association of American Geographers

Langue :
Anglais