Photogrammetric modeling of underwater environments

Underwater photogrammetry provides an efficient nondestructive means for measurement in environments with limited accessibility. With the growing use of consumer cameras, its application is becoming easier, thus benefiting a wide variety of disciplines. However, utilizing cameras for underwater photogrammetry poses some nontrivial modeling problems due to refraction effect and the extension of the imaging system into a unit of both the camera and the protecting housing device. This paper studies the effect that the underwater environment has on the photogrammetric process, and proposes a model for describing the geometric distortions and for estimating the additional parameters involved. The proposed model accounts not only for the multimedia effect, but also for inaccuracies related to the setting of the camera and housing device. The paper shows that only a small number of additional parameters is needed to model both elements and to preserve the collinearity relation. The results show that no unique setup is needed for estimating the additional parameters and that the estimation is insensitive to noise or first approximations. Experiments show that high levels of accuracy can be achieved.     

Sinkhole characterization in the Dead Sea area using airborne laser scanning

Since the early 1980s, the Dead Sea coast has undergone a near catastrophic land deterioration as a result of a rapid lake-level drop. One conspicuous expression of this deterioration is the formation of sinkholes fields that puncture the coastal plains. The evolution of sinkholes along nearly 70-km strip has brought to a halt the regional development in this well-known and toured area and destroyed existing infrastructures. Great efforts are being invested in understanding the phenomena and in development of monitoring techniques. We report in this paper the application of airborne laser scanning for characterization of sinkholes. We demonstrate first the appropriateness of laser scanning for this task and its ability to provide detailed 3D information on this phenomenon. We describe then an autonomous means for their extraction over large regions and with high level of accuracy. Extraction is followed by their detailed geometric characterization. Using this high-resolution data, we show how sinkholes of 0.5 m radius and 25 cm depth can be detected from airborne platforms as well as the geomorphic features surrounding them. These sinkhole measures account for their embryonic stage, allowing tracking them at an early phase of their creation.     

ANALYSIS OF Cu, Cd, Co AND Ni IN SURFACE WATER OF THE KUROSHIO AREA IN THE EAST CHINA SEA

Study of 1986 and 1987 heavy metal distribution in surface water of the Kuroshio area in the East China Sea showed regional and slight seasonal variations in distribution and concentration . Heavy metal levels in Taiwan Strait, the sea area north of Taiwan and the continental shelf are higher than those in the main axis of the Kuroshio . Dissolved Cu in summer and winter decreases with the increase of salinity , but dissolved Cd has no obvious change with salinity .     

Detection of gullies in roughly textured terrain using airborne laser scanning data

Airborne laser scanning data contain information about surface features, some of which are of subtle form. These features are usually embedded within the terrain, and rarely form distinct shape-transition to their surroundings. While some efforts have been made in extracting linear elements from laser scanning data, attention was mostly turned to dominant elements that are very clear and distinct. We present in this paper a detection model for gullies of various dimensions using airborne laser scanning data. Gullies are regarded as one of the main landform-reshaping agents, having a pejorative effect on the environment and on regional development. They are commonly observed along receding lakes as a common response to water-level drop. The paper demonstrates how a multi-scale approach enables the extraction of various gully forms, from well developed to subtle. It then proposes an optimization driven model for handling fragmentation in the detection. Results show that using the proposed model, gully networks can be reconstructed and ∼30 cm deep features can be identified and separated from their surroundings using moderate point density data.     

Extracting spatial patterns in bicycle routes from crowdsourced data

Much is done nowadays to provide cyclists with safe and sustainable road infrastructure. Its development requires the investigation of road usage and interactions between traffic commuters. This article is focused on exploiting crowdsourced user‐generated data, namely GPS trajectories collected by cyclists and road network infrastructure generated by citizens, to extract and analyze spatial patterns and road‐type use of cyclists in urban environments. Since user‐generated data shows data‐deficiencies, we introduce tailored spatial data‐handling processes for which several algorithms are developed and implemented. These include data filtering and segmentation, map‐matching and spatial arrangement of GPS trajectories with the road network. A spatial analysis and a characterization of road‐type use are then carried out to investigate and identify specific spatial patterns of cycle routes. The proposed analysis was applied to the cities of Amsterdam (The Netherlands) and Osnabrück (Germany), proving its feasibility and reliability in mining road‐type use and extracting pattern information and preferences. This information can help users who wish to explore friendlier and more interesting cycle patterns, based on collective usage, as well as city planners and transportation experts wishing to pinpoint areas most in need of further development and planning.