Automatic classification of aerial imagery for urban hydrological applications

verfasst von

A. Paul, C. Yang, U. Breitkopf, Y. Liu, Z. Wang, F. Rottensteiner, M. Wallner, A. Verworn, C. Heipke

Abstract

In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order to assess whether the capacity of the sewers is sufficient to avoid surcharge within certain return periods, precipitation is transformed into runoff. The transformation of precipitation into runoff requires knowledge about the proportion of drainage-effective areas and their spatial distribution in the catchment area. Common simulation methods use the coefficient of imperviousness as an important parameter to estimate the overland flow, which subsequently contributes to the pipe flow. The coefficient of imperviousness is the percentage of area covered by impervious surfaces such as roofs or road surfaces. It is still common practice to assign the coefficient of imperviousness for each particular land parcel manually by visual interpretation of aerial images. Based on classification results of these imagery we contribute to an objective automatic determination of the coefficient of imperviousness. In this context we compare two classification techniques: Random Forests (RF) and Conditional Random Fields (CRF). Experimental results performed on an urban test area show good results and confirm that the automated derivation of the coefficient of imperviousness, apart from being more objective and, thus, reproducible, delivers more accurate results than the interactive estimation. We achieve an overall accuracy of about 85% for both classifiers. The root mean square error of the differences of the coefficient of imperviousness compared to the reference is 4.4% for the CRF-based classification, and 3.8% for the RF-based classification.

Organisationseinheit(en)

Institut für Photogrammetrie und Geoinformation

Externe Organisation(en)

Bpi Hannover - Beratende Ingenieure

Typ

Konferenzaufsatz in Fachzeitschrift

Journal

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Band

42

Seiten

1355-1362

Anzahl der Seiten

8

ISSN

1682-1750

Publikationsdatum

30.04.2018

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Information systems, Geografie, Planung und Entwicklung

Ziele für nachhaltige Entwicklung

SDG 15 – Lebensraum Land

Elektronische Version(en)

https://doi.org/10.5194/isprs-archives-XLII-3-1355-2018 (Zugang: Offen)
https://doi.org/10.15488/3753 (Zugang: Offen)