Simulating geometric uncertainties of impervious areas based on image segmentation accuracy metrics

Simulation d'erreurs de géométrie sur les zones artificialisées s'appuyant sur des mesures de qualité de segmentation d'images

Laurent, V. ; Saint Geours, N. ; Bailly, J.S. ; Chery, J.P.

Type de document
Communication scientifique avec actes
Langue
Anglais
Affiliation de l'auteur
IRSTEA MONTPELLIER UMR TETIS FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; AGROPARISTECH UMR TETIS MONTPELLIER FRA ; AGROPARISTECH UMR TETIS MONTPELLIER FRA
Année
2014
Résumé / Abstract
Urban sprawl monitoring is important for developing land management policies at various spatial scales. Segmentation and classification of satellite images allows obtaining polygons of impervious areas regularly over large areas, e.g. as has been implemented for the region Languedoc‐Roussillon in the south of France using 5 m RapidEye images. Starting from the results of this previous study, we aim to: i) evaluate the geometric and thematic accuracy of the impervious polygons (S) using segmentation accuracy metrics, and ii) use these metrics to simulate polygons having the same level of uncertainty. A manual segmentation (M) was used to evaluate the accuracy. After matching the polygons, the distance (d) and azimuth (a) of each vertex of M to the closest segment of the boundary of S was calculated. Spherically correlated random fields of d and a were used to randomly move the vertices of S. Realistic simulations of impervious polygons were obtained.
Congrès
GEOBIA 2014, 21/05/2014 - 24/05/2014, Thessaloniki, GRC
Document d'origine
South-Eastern European Journal of Earth Observation and Geomatics, GEOBIA 2014, Advancements, trends and challenges, Gitas, I.; Mallinis, G.; Patias, P.; Stathakis, D. & Zalidis, G. (Eds.)
Editeur
Gitas, I.; Mallinis, G.; Patias, P.; Stathakis, D. & Zalidis, G.

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