E. Schwalbe

Hemispheric image modeling and analysis techniques for solar radiation determination in forest ecosystems.

Hemispheric image processing with the goal of solar radiation determination from ground-based fisheye images is a valuable tool for silvicultural analysis in forest ecosystems. The basic idea of the technique is taking a hemispheric crown image with a camera equipped with a 180° fisheye lens, segmenting the image in order to identify solar radiation relevant open sky areas, and then merging the open sky area with a radiation and sun-path model in order to compute the total annual or seasonal solar radiation for a plant. The results of hemispheric image processing can be used to quantitatively evaluate the growth chances of ground vegetation (e.g., tree regeneration) in forest ecosystems. This paper shows steps towards the operationalization and optimization of the method. As a prerequisite to support geometric handling and georeferencing of hemispheric images, an equi-angular camera model is shown to describe the imaging geometry of fisheye lenses. The model is extended by a set of additional parameters to handle deviations from the ideal model. In practical tests, a precision potential of 0.1 pixels could be obtained with off-the-shelf fisheye lenses. In addition, a method for handling the effects of chromatic aberration, which may amount to several pixels in fisheye lens systems, is discussed. The central topic of the paper is the development of a versatile method for segmenting hemispheric forest crown images. The method is based on linear segmentoriented classification on radial profiles. It combines global thresholding techniques with local image analysis to ensure a reliable segmentation in different types of forest under various cloud conditions. Sub-pixel classification is incorporated to optimize the accuracy of the method. The performance of the developed method is validated in a number of practical tests.

Photogrammetric Techniques for the Determination of Spatio-temporal Velocity Fields at Glaciar San Rafael, Chile

Glaciar San Rafael in the Northern Patagonia Icefield, with a length of 46 km and an ice area of 722 km2, is the lowest latitude tidewater outlet glacier in the world and one of the fastest and most productive glaciers in southern South America in terms of iceberg flux. Spatio-temporal velocity fields in the region of the glacier front were determined from monoscopic terrestrial image sequences recorded by an inter-vallometer mode high-resolution digital camera over several days. In these image sequences, a large number of glacier surface points were tracked by subpixel accuracy feature tracking techniques. Scaling and georeferencing of the trajectories obtained from image space tracking was performed using a multi-station GPS-supported photogrammetric network. The technique allows for tracking hundreds of glacier surface points at a measurement accuracy in the order of one decimeter, for typical glacier movement rates, and an almost arbitrarily high temporal resolution. The results show velocities of up to 16 meters per day.

Determination of spatio-temporal velocity fields at Grey Glacier using terrestrial image sequences and optical satellite imagery

Since several years most glaciers all over the world are showing increasing retreat, thinning and acceleration. To understand and model the phenomena as well as to predict the future development of ice fields and glaciers, glaciologists need different data that describe the glaciers condition. Therein, an important issue is the determination of velocity fields. These can be derived using remote sensing as well as terrestrial methods. In the paper we introduce both a terrestrial image sequence as well as a satellite image-based technique for the analysis of the motion behaviour of Grey Glacier in the Southern Patagonian Icefield.

Determination of high resolution spatio-temporal glacier motion fields from time-lapse sequences

This paper presents a comprehensive method for the determination of glacier surface motion vector fields at high spatial and temporal resolution. These vector fields can be derived from monocular terrestrial camera image sequences and are a valuable data source for glaciological analysis of the motion behaviour of glaciers. The measurement concepts for the acquisition of image sequences are presented, and an automated monoscopic image sequence processing chain is developed. Motion vector fields can be derived with high precision by applying automatic subpixel-accuracy image matching techniques on grey value patterns in the image sequences. Well-established matching techniques have been adapted to the special characteristics of the glacier data in order to achieve high reliability in automatic image sequence processing, including the handling of moving shadows as well as motion effects induced by small instabilities in the camera set-up. Suitable geo-referencing techniques were developed to transform image measurements into a reference coordinate system. The result of monoscopic image sequence analysis is a dense raster of glacier surface point trajectories for each image sequence. Each translation vector component in these trajectories can be determined with an accuracy of a few centimetres for points at a distance of several kilometres from the camera. Extensive practical validation experiments have shown that motion vector and trajectory fields derived from monocular image sequences can be used for the determination of high-resolution velocity fields of glaciers, including the analysis of tidal effects on glacier movement, the investigation of a glacier’s motion behaviour during calving events, the determination of the position and migration of the grounding line and the detection of subglacial channels during glacier lake outburst floods.

Photogrammetric monitoring concept for remote landslide endangered areas using multi-temporal aerial imagery

Natural disasters like landslides or floods can be significant dangers to life, nature and infrastructure in the affected areas. Especially in regions with permanent potential risks of such weather-induced phenomena, an effective monitoring system can reduce the risk of major damages. In the case of Punta Arenas (Southern Chile) landslides irregularly block and dam the nearby river Las Minas and thus cause catastrophic floods of the Chilean city. To prevent such landslide triggered hazards, the paper focuses on photogrammetric landslide detection and analysis using multi-temporal aerial images to reliably detect major geomorphological changes. As example, datasets from 2014 and 2015 of the river Las Minas have been compared in order to detect volume changes. For this purpose, multi-temporal 3D point clouds were generated and georeferenced. The registration of the point clouds was conducted applying ICP techniques to compensate potential point cloud deformations.