PRACTISE – Photo Rectification And ClassificaTIon SoftwarE (V.1.0)

Abstract

Terrestrial photography is a cost-effective and easy-to-use method for measuring and monitoring spatially distributed land surface variables. It can be used to continuously investigate remote and often inaccessible terrain. We focus on the observation of snow cover patterns in high mountainous areas. The high temporal and spatial resolution of the photographs have various applications, for example validating spatially distributed snow hydrological models. However, the analysis of a photograph requires a preceding georectification of the digital camera image. To accelerate and simplify the analysis, we have developed the "Photo Rectification And ClassificaTIon SoftwarE" (PRACTISE) that is available as a Matlab code. The routine requires a digital camera image, the camera location and its orientation, as well as a digital elevation model (DEM) as input. If the viewing orientation and position of the camera are not precisely known, an optional optimisation routine using ground control points (GCPs) helps to identify the missing parameters. PRACTISE also calculates a viewshed using the DEM and the camera position. The visible DEM pixels are utilised to georeference the photograph which is subsequently classified. The resulting georeferenced and classified image can be directly compared to other georeferenced data and can be used within any geoinformation system. The Matlab routine was tested using observations of the north-eastern slope of the Schneefernerkopf, Zugspitze, Germany. The results obtained show that PRACTISE is a fast and user-friendly tool, able to derive the microscale variability of snow cover extent in high alpine terrain, but can also easily be adapted to other land surface applications

PRACTISE – Photo Rectification And ClassificaTIon SoftwarE (V.2.1)

“…The high spatial resolution of the photograph snow cover maps is very valuable, as snow cover strongly varies over time and space and an accurate description in models is difficult (Blöschl et al, 1991;Winstral and Marks, 2002;Bernhardt and Schulz, 2010). The high temporal resolution of the terrestrial camera systems, for example on an hourly basis, further enhances the probability of at least one suitable photograph per day, despite the frequently occurring cloud and precipitation events at high altitudes (Härer et al, 2013).…”

“…Parajka et al, 2012 for an overview). The advantages of terrestrial photography are that this technique has a high accuracy, is non-invasive, and provides spatially distributed snow cover data in a high temporal and spatial resolution (Aschenwald et al, 2001;Hinkler et al, 2002;Corripio et al, 2004;Schmidt et al, 2009;Parajka et al, 2012;Härer et al, 2013). The decreasing costs of digital cameras and camera lenses with no or minimal distortion, as well as the potential use of terrestrial photography in remote and hostile environments due to technical advancements in off-grid power supply and data transfer also need to be mentioned here.…”

“…Corripio (2004) and Corripio et al (2004) presented a software tool that eased the georectification process, utilizing the animation and rendering technique by Watt and Watt (1992). This also formed the basis for the Photo Rectification And ClassificaTIon SoftwarE (PRACTISE V.1.0; Härer et al, 2013). Though, the formulations for the calculation of the 3-D rotation and projection are slightly different to Corripio (2004) and Corripio et al (2004).…”

“…The combined value is referred to as T t . In addition, interior orientation parameters of the camera are necessary, such as the focal length f , as well as the sensor dimensions: height h and width w (Härer et al, 2013). The ver- tical and horizontal dimensions of the photograph (N v and N h ) are also needed for the georectification.…”

“…Sect. 3.1 and Härer et al, 2013). If the satellite image module is in use, radiometrically and geometrically corrected data of Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), or Landsat 8 Operational Land Imager (OLI) can be processed.…”