Bundle Adjustment with Self–Calibration Using Straight Lines

Increased use of digital imagery has facilitated the opportunity to use features, in addition to points, in photogrammetric applications. Straight lines are often present in object space, and prior research has focused on incorporating straight–line constraints into bundle adjustment for frame imagery. In the research reported in this paper, object–space straight lines are used in a bundle adjustment with self–calibration. The perspective projection of straight lines in the object space produces straight lines in the image space in the absence of distortions. Any deviations from straightness in the image space are attributed to various distortion sources, such as radial and decentric lens distortions. Before incorporating straight lines into a bundle adjustment with self–calibration, the representation and perspective transformation of straight lines between image space and object space should be addressed. In this investigation, images of straight lines are represented as a sequence of points along the image line. Also, two points along the object–space straight line are used to represent that line. The perspective relationship between image– and object–space lines is incorporated in a mathematical constraint. The underlying principle in this constraint is that the vector from the perspective centre to an image point on a straight–line feature lies on the plane defined by the perspective centre and the two object points defining the straight line. This constraint has been embedded in a software application for bundle adjustment with self–calibration that can incorporate point as well as straight–line features. Experiments with simulated and real data have proved the feasibility and the efficiency of the algorithm proposed.     

Interactive Analysis Using Voronoi Diagrams: Algorithms to Support Dynamic Update from a Generic Triangle-based Data Structure

This paper describes a series of dynamic update methods that can be applied to a family of Voronoi diagram types, so that changes can be updated incrementally, without the usual recourse to complete reconstruction of their underlying data structure. More efficient incremental update methods are described for the ordinary Voronoi diagram, the farthest-point Voronoi diagram, the order- k Voronoi diagram and the ordered order- k Voronoi diagram. A discussion is also given of one case where incremental update is not practical, that of the multiplicatively weighted Voronoi diagram. Update methods rely on a previously reported generic, triangle-based data structure (Gahegan and Lee 2000) from which local topology can be dynamically reconstructed following changes to the underlying pointset. An application, which implements these ideas, is available for download via the Internet as proof of concept. Results show that the algorithmic complexity of dynamic update methods vary considerably according to the Voronoi type, but offer in all cases (except the multiplicatively weighted Voronoi diagram) a substantial increase in performance, enabling Voronoi methods to address larger pointsets and more complex modelling problems without incurring too great a computational burden.     

Ocean color reveals phase shift between marine plants and yellow substance

Daily high-resolution Sea-viewing Wide Field-of-view Sensor (SeaWiFS) images of the central North Atlantic Ocean (1998-2003) show that temporal changes in the absorption coefficient of colored dissolved organic matter (CDOM) or "yellow substance" follow changes in phytoplankton pigment absorption coefficient in time. CDOM peaks (between January and March) and troughs (late summer and fall) followed pigment peaks and troughs by approximately two and four weeks, respectively. This phase shift is additional strong evidence that CDOM in the marine environment is derived from phytoplankton degradation. The common assumption of linear covariation between chlorophyll and CDOM is a simplification even in this ocean gyre. Due to the temporal changes in CDOM, chlorophyll concentration estimated based on traditional remote sensing band-ratio algorithms may be overestimated by about 10% during the spring bloom and underestimated by a similar 10% during the fall. These observations are only possible through use of synoptic, precise, accurate, and frequent measurements afforded by space-based sensors because in situ technologies cannot provide the required sensitivity or synoptic coverage to observe these natural phenomena.     

Spatial and temporal change in landslide hazard by future climate change scenarios using probabilistic-based frequency ratio model

The aims of this study were to apply, verify and compare a frequency ratio model for landslide hazards, considering future climate change and using a geographic information system in Inje, Korea. Data for the future climate change scenario (A1B), topography, soil, forest, land cover and geology were collected, processed and compiled in a spatial database. The probability of landslides in the study area in target years in the future was then calculated assuming that landslides are triggered by a daily rainfall threshold. Landslide hazard maps were developed for the two study areas, and the frequency ratio for one area was applied to the other area as a cross-check of methodological validity. Verification results for the target years in the future were 82.32–84.69%. The study results, showing landslide hazards in future years, can be used to help develop landslide management plans.     

Effects of climate change on forests of the eastern United States

A multi‐phased approach was used to estimate potential impacts of climate change on forests of the eastern United States. Phase I was at community‐level and Phase II examined selected species, both using three 2 x CO₂ climate scenarios. Geographic information systems (GIS) and statistical modeling techniques were used to manipulate and analyze climate and vegetation data, and model vegetation responses to climate change. The first two stages of the study indicated possible large‐scale alteration of forest communities by future climate change. Although results varied among climate models, several trends were apparent. In northern states of the study area, ranges of several conifers declined significantly and ranges of oaks and hickories moved northward. In central states, ranges of sugar maple and tulip poplar became much smaller, with concomitant increases in ranges of southern oaks and loblolly pine. In . southern states, American beech declined and ranges of southern oaks increased northward. This paper discusses results of the first two phases and current progress of the third phase.     

Characterization of reservoir sediment under water with differential pressure-sensored flat dilatometer and piezo-penetrometer

The unusually strong typhoons and heavy rainfalls occurred recently in Taiwan have caused major landslides in many reservoir catch basins. The debris from these landslides eventually settled in the reservoir and turned into mud. From soil mechanics point of view, the mud immediately in front of the dam where the reservoir is usually the deepest is a very young, normally consolidated or under-consolidated fine-grained soil. The engineering properties of the reservoir mud are important parameters in the planning and design of schemes to remove the mud. Yet, our knowledge in this regard is very limited. For some of the major reservoirs in Taiwan, the mud is often under more than 40 m of water. How to conduct effective geotechnical site characterization under these circumstances is a challenge. The authors developed techniques to incorporate differential pressure measurements in flat dilatometer (ΔDMT) and piezo-penetrometer (ΔPu) tests to facilitate in situ measurements under water in a reservoir. A series of field ΔDMT and ΔPu tests along with representative soil sampling were conducted at Tsengwen Reservoir in southern Taiwan. The paper describes the techniques of ΔDMT and ΔPu tests, interpretation of available test data to obtain the engineering properties of the reservoir mud, and discusses implications in the future site characterization of reservoir mud.     

Preliminary availability assessment to support single-frequency SBAS development in the Korean region

Satellite-Based Augmentation Systems (SBASs) enhance the global navigation satellite system (GNSS) to support all phases of flight by providing required accuracy, integrity, continuity, and availability. The Korean SBAS program was recently initiated to develop a single-frequency SBAS aiming to provide Approach Procedure with Vertical guidance (APV)-I Safety-of-Life (SoL) service to aviation users by 2022 within the Korean region. We assess the preliminary availability of the single-frequency SBAS which will be deployed in the Korean peninsula. The resulting system performance shall be used as a baseline to design system components and specifications. The fundamental components of SBAS architecture, SBAS monitor network, geostationary earth orbiting satellite parameters, and ionospheric grid point mask, are defined and their effects on system performance are investigated. Ionospheric correction and integrity algorithm parameters including an ionospheric irregularity threat model are determined using data collected from the Korean GNSS network. The coverage of 99.9 % availability for APV-I service increases from approximately 70 % for the baseline case to 100 % when SBAS monitor stations are expanded to overseas. Even with the expanded monitor network, however, 90 % and less than 95 % availability for LPV-200 service can be achieved only in a very limited region.     

Assessment of the adequacy of the regional relationships between catchment attributes and catchment response dynamics,calibrated by a multi‐objective approach

This study aimed to evaluate the effectiveness of the regionalization method on the basis of a combination of a parsimonious model structure and a multi‐objective calibration technique. For this study, 12 gauged catchments in the Republic of Korea were used. The parsimonious model structure, requiring minimal input data, was used to avoid adverse effects arising from model complexity, over‐parameterization and data requirements. The IHACRES rainfall‐runoff model was applied to represent the dynamic response characteristics of catchments in Korea. A multi‐objective approach was adopted to reduce the predictive uncertainty arising from the calibration of a rainfall‐runoff model, by increasing the amount of information retrieved from the available data. The regional relationships (or models) between the model parameters and the catchment attributes were established via a multiple regression approach, incorporating correlation analysis and stepwise regression on linear and logarithmic scales. The impacts of the parameters, calibrated by the multi‐objective approach, on the adequacy of regional relationships were assessed by comparison with impacts obtained by the single‐objective approach. The regional relationships were well defined, despite limited available data. The drainage area, the effective soil depth, the mean catchment slope and the catchment gradient appeared to be the main factors for describing the hydrologic response characteristics in the areas studied. The overall model performance of the regional models based on the multi‐objective approach was good, producing reasonable results for high and low flows and for the overall water balance, simultaneously. The regional models based on the single‐objective approach yielded accurate predictions in high flows but showed limited predictive capability for low flows and the overall water balance. This was due to the optimal model parameter estimates when using a single‐objective measure. The parameters calibrated by the single‐objective approach decreased the predictability of the regional models. Copyright © 2013 John Wiley & Sons, Ltd.     

Analysis of bacterial diversity and metals in produced water, seawater and sediments from an offshore oil and gas production platform

Produced water is one of the largest waste products routinely discharged into the ocean from offshore oil and gas platforms. This study analyzed bacterial communities and metals in the produced water, surrounding seawater, and sediment around the Thebaud platform. The bacterial community within the produced water was different from the seawater (SAB = 13.3), but the discharge had no detectable effect on the bacterial communities in the seawater (SAB > 97). In contrast, genomic analysis of sediments revealed that the bacterial community from 250 m was different (SAB = 70) from other locations further from the discharge, suggesting that the produced water had a detectable effect on the bacterial community in the sediment closest to the discharge. These near-field sediments contained elevated concentrations of manganese and iron that are associated with the produced water effluent. The results suggested that the discharge of produced water has influenced the bacterial community structure of sediments adjacent to the platform.     

Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.