Automatic processing of orthophotos to determine the imperviousness of catchments


For many tasks in urban drainage (master planning, rainfall-runoff modelling etc.) more or less detailed information (e.g. percentage of roads, roofs and green spaces or only the whole impervious area) about the land-cover of the investigated catchment is necessary. Until now these data are manually acquired from maps, arial photographs and by on site inspection. This manual determination is time-consuming and hence expensive especially for large catchments with high imperviousness.

The present method was developed at the department of engineering science of EAWAG. It achieved good results compared to a manual digitalisation. Newer investigations with high-resolution satellite images (IKONOS) also show good results.

Aim of the study

The aim was to develop a processing of the color and infra-red images as automated as possible to determine the imperviousness in urban catchments and to test the procedure in practice in collaboration with an engineering company.


The following presented automatic determination of surface types from aerial photographs only allows the discrimination between impervious and pervious areas.

Multispectral Classification

A digital color aerial image or an orthophoto (a georeferenced and geometrically corrected aerial image that fits the map) is the basis for the classification. The digital image consists of squared image points (pixels) of a certain ground resolution (0.2 - 1.5 m). The digital image is created from a scan of an analogue aerial image (23x23 cm) or directly shot with a digital camera. Each pixel contains a color information in the form of three numbers which represent the brightness values of the base colors red, green and blue (RGB). Satellite and infrared images has additional brightness values from other spectral ranges (so-called channels)  of the electromagnetic radiation (near or far infrared, thermal radiation).

A multispectral classification is used to assign each pixel to a land-cover class based on its color or spectral information. A brightness distribution for each spectral range is determined by analyzing multiple regions (training sites) of pixels for each ground class by hand. Based on these brightness distributions each pixel of the orthophoto is assigned to a land-cover class by means of the maximum likelihood method. In a next step the land-cover classes are aggregated to two classes «pervious» and «impervious». Figure 1 and 2 show the original orthophoto and classification result. 

Fig.1: original color orthophoto

Fig.2: classification
(green: pervious, red: impervious, black: shadow)


The method was tested in various catchments. The differences to a determination by manual digitizing of the impervious areas are less than 10%.

Collaboration with following companies

André Rotzetter + Partner AG, Zug
Swissphoto Vermessung AG, Watt