Geographic Region Of Interest Research Articles

Plate tectonics, long-distance dispersals and chance introductions can explain many trans-Pacific disjunctions

Several diatom species, including Cymbella amplificata, C. janischii and Navicula aurora, are largely restricted to Asia and western North America. These disjunctions likely represent recent long-distance dispersals or chance introductions. The two continents also support clusters of diatom species in several fossil and extant genera. One of these genera, Gomphosinica, is exclusive to the two continents but includes only one species in common. This suggests that these disjunct clusters of species arose from common precursors that underwent radiations while being separated for millennia. The divergence of these lineages likely began more than 25 Ma when island arcs of Asian (Siberian) origin docked on North America. The Asian/North American connection is not restricted to diatoms; vascular plants and dinosaur fossils also exhibit this connection. Differences between diatom floras east and west of the Rocky Mountains, as first noted by Ehrenberg, can be explained by differences in Earth history and geology. Researchers interested in diatom biogeography would do well to become familiar with the tectonic history and geology of their geographic regions of interest. Some cases of ‘invasive’ or ‘alien’ diatoms may simply be that changing conditions allowed existing but latent species to prosper and become apparent to the unaided eye.

An environmental exploration system for visual scenario analysis of regional hydro-meteorological systems

We propose a framework for the 3D exploration of heterogeneous environmental data within a geographical region of interest. Based on Unity, the system can be built for a variety of platforms and works both on regular machines as well as in virtual reality environments, where it can be considered a basis for a virtual geographic environment. Focussing on the catchment of the Müglitz River in south-eastern Germany, a large collection of observation data acquired via a wide range of measurement devices has been integrated in a geographical reference frame for the region. Results of area-wide numerical simulations for both groundwater and soil moisture have been added to the scene and allow for the exploration of the delayed consequences of transient phenomena such as heavy rainfall events and their impact on the catchment scale. This study focusses on the concurrent visualisation and synchronised animation of multiple area wide datasets from different environmental compartments. The resulting application allows to explore the region of interest during specific hydrological events for an assessment of the interrelation of processes. As such, it offers the opportunity for knowledge transfer between researchers of different domains as well as for outreach to an interested public.

Sweet tweets! Evaluating a new approach for probability-based sampling of Twitter

As survey costs continue to rise and response rates decline, researchers are seeking more cost-effective ways to collect, analyze and process social and public opinion data. These issues have created an opportunity and interest in expanding the fit-for-purpose paradigm to include alternate sources such as passively collected sensor data and social media data. However, methods for accessing, sourcing and sampling social media data are just now being developed. In fact, there has been a small but growing body of literature focusing on comparing different Twitter data access methods through either the elaborate firehose or the free Twitter search or streaming APIs. Missing from the literature is a good understanding of how to randomly sample Tweets to produce datasets that are representative of the daily discourse, especially within geographical regions of interest, without requiring a census of all Tweets. This understanding is necessary for producing quality estimates of public opinion from social media sources such as Twitter. To address this gap, we propose and test the Velocity-Based Estimation for Sampling Tweets (VBEST) algorithm for selecting a probability based sample of tweets. We compare the performance of VBEST sample estimates to other methods of accessing Twitter through the Search API on the distribution of total Tweets as well as COVID-19 keyword incidence and frequency and find that the VBEST samples produce consistent and relatively low levels of overall bias compared to common methods of access through the Search API across many experimental conditions.

Error Propagation in Satellite Multi-Image Geometry

This paper describes an investigation of the source of geospatial error in digital surface models (DSMs) constructed from multiple satellite images. In this study the uncertainty in surface geometry is separated into two spatial components; global error that affects the absolute position of the surface, and local error that varies from surface point to surface point. The global error component is caused by inaccuracy in the satellite imaging process, mainly due to uncertainty in the satellite position and orientation (pose) during image collection. A key result of the investigation is a new algorithm for determining the absolute geoposition of the DSM that takes into account the pose covariance of each satellite during image collection. This covariance information is used to weigh the evidence from each image in the computation of the global position of the DSM. The use of covariance information significantly decreases the overall uncertainty in global position. The paper also describes an approach to the prediction of local error in the DSM surface. The observed variance in surface position within a single stereo surface reconstruction defines the local horizontal error. The variance in the fused set of elevations from multiple stereo pairs at a single DSM location defines the local vertical error. These accuracy predictions are compared to ground truth provided by LiDAR scans of the same geographic region of interest.

Literature review and comparative analysis of inland waterways transport: “Container on Barge”

Container on Barge (COB) facilitates intermodal transportation by transporting shipping containers on barge tows. COB has seen rapid expansion globally over the past 20 years, providing a cost-efficient, environmentally friendly, and congestion-reducing mode of container transportation. European countries have led COB transportation in both study and application over the past two decades. However, increasing interest is observed in both the USA and Asia. In this literature review and comparative analysis, 135 COB-focused peer-reviewed articles are reviewed and analyzed to systematically describe the development and current status of COB transportation research. The relevant literature is analyzed to reveal publication rates and titles, geographical regions of interest, research questions, applied methodologies, advantages of COB transportation, and key success factors. The aim of our effort is to provide information on various aspects of COB development among different regions in the world and to summarize the existing literature to support and guide future COB development.

Model-Based Geostatistical Methods Enable Efficient Design and Analysis of Prevalence Surveys for Soil-Transmitted Helminth Infection and Other Neglected Tropical Diseases.

Maps of the geographical variation in prevalence play an important role in large-scale programs for the control of neglected tropical diseases. Precontrol mapping is needed to establish the appropriate control intervention in each area of the country in question. Mapping is also needed postintervention to measure the success of control efforts. In the absence of comprehensive disease registries, mapping efforts can be informed by 2 kinds of data: empirical estimates of local prevalence obtained by testing individuals from a sample of communities within the geographical region of interest, and digital images of environmental factors that are predictive of local prevalence. In this article, we focus on the design and analysis of impact surveys, that is, prevalence surveys that are conducted postintervention with the aim of informing decisions on what further intervention, if any, is needed to achieve elimination of the disease as a public health problem. We show that geospatial statistical methods enable prevalence surveys to be designed and analyzed as efficiently as possible so as to make best use of hard-won field data. We use 3 case studies based on data from soil-transmitted helminth impact surveys in Kenya, Sierra Leone, and Zimbabwe to compare the predictive performance of model-based geostatistics with methods described in current World Health Organization (WHO) guidelines. In all 3 cases, we find that model-based geostatistics substantially outperforms the current WHO guidelines, delivering improved precision for reduced field-sampling effort. We argue from experience that similar improvements will hold for prevalence mapping of other neglected tropical diseases.

Multivariate Forecasting of Road Accidents Based on Geographically Separated Data

As road accidents are the leading cause of death for young adults all over the world, it is necessary for the police to evaluate the accident circumstances carefully in order to take appropriate prevention measures. The circumstances of an accident vary in their frequency over time and depend on the local conditions at the accident site. An evaluation under geographical and temporal aspects is therefore necessary. On the basis of the time series, we investigate the various accident circumstances, which show interdependencies with each other, and their influence on the number of accidents. Moreover, a multivariate forecasting is used to indicate the future progression of accidents in different geographical regions. Forecast values are determined with a special extension of the ARIMA method. In order to identify geographical regions of interest, we present two different concepts for segmentation of accident data, which allow the adaptation of police measures to local characteristics.

Congestion-Aware Geocast Routing in Vehicular Delay-Tolerant Networks

Vehicular Delay-Tolerant Networks (VDTNs) are networks of vehicles that communicate wirelessly, where there are no permanent end-to-end connections. VDTNs have a highly variable topology, with frequent partitions, and possibly low node density. Thus, delay-tolerant routing adopts a store-carry-and-forward message transfer paradigm, where messages have a useful Time-To-Live (TTL) and are stored until a good contact opportunity arises. Multiple message replicas can be generated to improve delivery probability at the cost of increasing network congestion. In this paper, we propose the V-GRADIENT geocast routing protocol that monitors node density, buffer occupancy, and interest in geocast groups, to adapt the forwarding techniques used dynamically, to disseminate messages within the geographic region of interest. Simulation results show that the V-GRADIENT is capable of controlling network congestion and efficiently delivering messages resulting in better delivery ratios, lower latencies, and a small increase in overhead when compared with existing protocols.

Biological Anthropology of Latin America: Historical Development and Recent Advances

Despite significant positive developments within topics of biological anthropology, archaeology, and related academic areas in Latin America, we noted a lack of coordination and communication among them. Available publications provide syntheses within different areas of biological anthropology, yet few have attempted integration of the distinct subfields. We decided to address the development and current issues of most major areas of Latin American biological anthropology in a single volume with chapters by distinguished, experienced scholars who live and work in Latin America, are knowledgeable about the topics, have published extensively on them, and who were recommended by specialists within six geographical regions of interest: Brazil and northeastern South America, Mexico, Central America, the Caribbean, northwestern South America, and southern South America. Six subdisciplines within biological anthropology were defined for academic coverage: (1) biodemography and epidemiology; (2) bioarchaeology and skeletal biology; (3) paleopathology; (4) forensic anthropology; (5) population genetics; and (6) growth, development, health, and nutrition. Though these six subdisciplines overlap to an extent, each offers a distinct history of development and presents unique issues to address. Chapters generally cover topics of history, the state of knowledge, methodological perspective, and areas in need of additional research. Although the text is in English, abstracts in English, Spanish, and Portuguese are included.

Cross-comparison of cloud liquid water path derived from observations by two space-borne and one ground-based instrument in northern Europe

Abstract. Cloud liquid water path (LWP) is one of the target atmospheric parameters retrieved remotely from ground-based and space-borne platforms using different observation methods and processing algorithms. Validation of LWP retrievals is a complicated task since a cloud cover is characterised by strong temporal and spatial variability while remote sensing methods have different temporal and spatial resolutions. An attempt has been made to compare and analyse the collocated LWP data delivered by two satellite instruments SEVIRI and AVHRR together with the data derived from microwave observations by the ground-based radiometer RPG-HATPRO. The geographical region of interest is the vicinity of St. Petersburg, Russia, where the RPG-HATPRO radiometer is operating. The study is focused on two problems. The first one is the so-called scale difference problem, which originates from dissimilar spatial resolutions of measurements. The second problem refers to the land–sea LWP gradient. The radiometric site is located 2.5 km from the coastline where the effects of the LWP gradient are pronounced. A good agreement of data obtained at the microwave radiometer location by all three instruments (HATPRO, SEVIRI, and AVHRR) during warm and cold seasons is demonstrated (the largest correlation coefficient 0.93 was detected for HATPRO and AVHRR datasets). The analysis showed no bias of the SEVIRI results with respect to HATPRO data and a large positive bias (0.013–0.017 kg m−2) of the AVHRR results for both warm and cold seasons. The analysis of LWP maps plotted on the basis of the SEVIRI and AVHRR measurements over land and water surfaces in the vicinity of St. Petersburg revealed the unexpectedly high LWP values delivered by AVHRR during the cold season over the Neva River bay and over the Saimaa Lake and the abnormal land–sea LWP gradient in these areas. For the detailed evaluation of atmospheric state and ice cover in the considered geographical regions during the periods of ground-based and satellite measurements, reanalysis data were used. It is shown that the most probable reason for the observed artefacts in the AVHRR measurements over water and ice surfaces is the coarse resolution of the land–sea and snow–ice masks used by the AVHRR retrieval algorithm. The influence of a cloud field inhomogeneity on the agreement between the satellite and the ground-based data is studied. For this purpose, the simple estimate of the LWP temporal variability is used as a measure of the spatial inhomogeneity. It has been demonstrated that both instruments are equally sensitive to the inhomogeneity of a cloud field despite the fact that they have different spatial resolutions.

Comparison of msp genotyping and a 24 SNP molecular assay for differentiating Plasmodium falciparum recrudescence from reinfection

BackgroundCurrent World Health Organization guidelines for conducting anti-malarial drug efficacy clinical trials recommend genotyping Plasmodium falciparum genes msp1 and msp2 to distinguish recrudescence from reinfection. A more recently developed potential alternative to this method is a molecular genotyping assay based on a panel of 24 single nucleotide polymorphism (SNP) markers.MethodsPerformance parameters of these two genotyping methods were compared using data from two recently completed drug efficacy trials. Blood samples from two anti-malarial therapeutic trials were analysed by both msp genotyping and the 24 SNP assay. Additionally, to conserve time and resources, the statistical program R was used to select the most informative SNPs for a set of unrelated Malawian samples to develop a truncated SNP-based assay for the region surrounding Blantyre, Malawi. The ability of this truncated assay to distinguish reinfection from recrudescence when compared to the full 24 SNP assay was then analysed using data from the therapeutic trials.ResultsA total of 360 samples were analysed; 66 for concordance of msp and SNP barcoding methodologies, and 294 for assessing the most informative of the 24 SNP markers. SNP genotyping performed comparably to msp genotyping, with only one case of disagreement among the 50 interpretable results, where the SNP assay identified the sample as reinfection and the msp typing as recrudescence. Furthermore, SNP typing was more robust; only 6% of samples were uninterpretable by SNP typing, compared to 19.7% when msp genotyping was used. For discriminating reinfection from recrudescence, a truncated 6 SNP assay was found to perform at 95.1% the accuracy of the full 24 SNP bar code.ConclusionsThe use of SNP analysis has similar sensitivity to the standard msp genotyping in determining recrudescence from reinfection. Although more expensive, SNP typing is faster and less work intensive. Limiting the assay to those SNPs most informative in the geographical region of interest may further decrease the workload and the cost, making this technique a feasible and affordable alternative in drug efficacy trials.

Tidal wave propagation along The Mekong deltaic coast

A two-dimensional, barotropic numerical model was employed to investigate the dynamics of tidal wave propagation in the South China Sea with a particular interest for its characteristics along the Mekong deltaic coast. The study indicates that tidal waves propagate from the Pacific Ocean into the South China Sea mainly through the Luzon Strait (LS), where the K1 diurnal tide dominates due to a quarter wavelength resonance in this semi-enclosed basin, and that the incoming tidal waves from the Celebes open boundary play a more important role than those from the Andaman and Flores open boundaries. Previous studies have not explained why both adjacent seas including the South China Sea and the Gulf of Thailand are dominated by a diurnal tide, while a semidiurnal tide dominates along the eastern Mekong deltaic coast. By means of Green's law, continental shelf tidal resonance theory and standing wave theory, this study clarifies that the large amplified M2 semidiurnal amplitude leading to a prevailing mixed semidiurnal tide is caused not only by the shoaling effect and the continental shelf oscillation resonance phenomenon but also by the position on the standing wave anti-node line. Moreover, the finding of radial tidal currents occurring along the southern Mekong estuarine coast has not been revealed in earlier studies. Based on a number of numerical, geometrically schematised experiments, we suggest that the interaction between the large amplified amplitude near the shoreline associated with the adjacent low amplitude band system, causing convex hydraulic gradients of tidal amplitude due to basin geometry as well as sloping topography, is the mechanism for developing these radial tidal current systems. The results reveal that wind monsoon climate could cause either damped or amplified tidal amplitudes around the Mekong deltaic coast of which approximately 2–3 cm is due to the changing atmospheric pressure, the tangential stress of wind over the water surface and wind enhanced bottom friction. Also, this study suggests that the tidal generating forces should be considered to achieve accurate model results depending on the geographical region of interest. Findings achieved from this study contribute to a deeper insight of tidal wave propagation from a deep ocean to a shallow flat basin similar to the South China Sea and its Mekong deltaic coast.

Obtaining the distribution of quiescent periods directly from the power spectral densities of Sea waves

There is a growing practical interest in the ability to increase the sea states at which marine operations can be safely undertaken by exploiting the quiescent periods that are well known to exist under a wide range of sea conditions. While the actual prediction of quiescent periods at sea for the control of operations is a deterministic process, the long term planning of future maritime tasks that rely on these quiescent periods is a statistical process involving the anticipated quiescence properties of the forecasted sea conditions in the geographical region of interest. It is in principle possible to obtain such data in tabular form either large scale simulation or from field data. However, such simulations are computationally intensive and libraries of appropriate field data are not common. Thus, it is clearly attractive to develop techniques that exploit standard wave spectral models for describing the quiescence statistics directly from such spectra. The present study focuses upon such techniques and is a first step towards the production of a computationally low-cost quiescence prediction tool and compares its efficacy against simulations. Two significant properties emerge for a large class of wave spectral models that encompasses the ubiquitous Neumann and Pierson Moskowitz or Bretschneider forms. Firstly, the auto-correlation function of the wave profile that are required to produce the quiescence property can be obtained analytically in terms of standard special functions. This considerably reduces the computational cost making desktop computer-based planning tools a reality. Secondly, for each class of these parametric spectra, the probability of a given number of consecutive wave heights (normalised to the significant wave heights) less than some critical value is in fact independent of absolute wave height. Thus, for a broad class of practically interesting wave spectra all that is required to obtain the statistical distribution of the quiescent periods is simple rescaling.

An Integrated Online Dynamic Security Assessment System for Improved Situational Awareness and Economic Operation

The ever-increasing penetration of centralized and distributed renewable energy, power electronics-based transmission equipment and loads, advanced protection and control systems, storage devices and new power market rules all contribute to the growing dynamics and stochastic behaviors being observed in today's grid operation. Understanding operational risks and providing prompt control actions are of great importance to ensure secure and economic operation of a bulk power system. In this paper, a novel integrated online dynamic security assessment system (DSAS) is developed that intakes real-time EMS snapshots combining both bus/branch and node/breaker network models, performs dynamic contingency analysis under various conditions, calculates real-time transfer limits, and provides online control suggestions to mitigate operational risks. Several unique and innovative features are developed to address practical challenges, including: (1) real-time stitching of power flow information from both node/breaker and bus/branch models covering different geographical regions of interest; (2) online corrections and enhancements to power flow and dynamic models; (3) equipment-name-based modelling approaches for complex contingencies and control systems; and (5) distributed computing capabilities for significant computational speed enhancement. The developed DSAS has been deployed in the control center of State Grid Jiangsu Electric Power Company with hundreds of HVAC and 8 (U)HVDC transmission lines, which has been running reliably since Sept. 2018, achieving satisfactory performance in improving situational awareness and economic operation of the power grid.

Satellite SST-Based Coral Disease Outbreak Predictions for the Hawaiian Archipelago

Predicting wildlife disease risk is essential for effective monitoring and management, especially for geographically expansive ecosystems such as coral reefs in the Hawaiian archipelago. Warming ocean temperature has increased coral disease outbreaks contributing to declines in coral cover worldwide. In this study we investigated seasonal effects of thermal stress on the prevalence of the three most widespread coral diseases in Hawai’i: Montipora white syndrome, Porites growth anomalies and Porites tissue loss syndrome. To predict outbreak likelihood we compared disease prevalence from surveys conducted between 2004 and 2015 from 18 Hawaiian Islands and atolls with biotic (e.g., coral density) and abiotic (satellite-derived sea surface temperature metrics) variables using boosted regression trees. To date, the only coral disease forecast models available were developed for Acropora white syndrome on the Great Barrier Reef (GBR). Given the complexities of disease etiology, differences in host demography and environmental conditions across reef regions, it is important to refine and adapt such models for different diseases and geographic regions of interest. Similar to the Acropora white syndrome models, anomalously warm conditions were important for predicting Montipora white syndrome, possibly due to a relationship between thermal stress and a compromised host immune system. However, coral density and winter conditions were the most important predictors of all three coral diseases in this study, enabling development of a forecasting system that can predict regions of elevated disease risk up to six months before an expected outbreak. Our research indicates satellite-derived systems for forecasting disease outbreaks can be appropriately adapted from the GBR tools and applied for a variety of diseases in a new region. These models can be used to enhance management capacity to prepare for and respond to emerging coral diseases throughout Hawai’i and can be modified for other diseases and regions around the world.

Modelling cluster detection in spatial scan statistics: Formation of a spatial Poisson scanning window and an ADHD case study

In this article we present a testing procedure for spatial scan statistics when the underlying population characteristics are not known. Specifically, the test procedure is designed for the situation when the number of affected cases in the population is random. We further assume that the number of contaminated case in the geographic region of interest follows a Poisson distribution. Then, under the null assumption of no cluster, we prove that the scanning window detecting contaminated cases is indeed a specific homogeneous spatial Poisson point process on the zones that constitute the region of interest. We then proceed to formulate an effective cluster detection testing procedure together with confidence intervals for the parameters of interests. We apply our procedure to the interesting and intensive real case study of detecting clusters of school-aged children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) in the State of Kuwait. We observe that geographic boundaries defining ethno-social groups are significant in determining ADHD prevalence among school-aged children in the State of Kuwait.

A composite state method for ensemble data assimilation with multiple limited-area models

Limited-area models (LAMs) allow high-resolution forecasts to be made for geographic regions of interest when resources are limited. Typically, boundary conditions for these models are provided through one-way boundary coupling from a coarser resolution global model. Here, data assimilation is considered in a situation in which a global model supplies boundary conditions to multiple LAMs. The data assimilation method presented combines information from all of the models to construct a single ‘composite state’, on which data assimilation is subsequently performed. The analysis composite state is then used to form the initial conditions of the global model and all of the LAMs for the next forecast cycle. The method is tested by using numerical experiments with simple, chaotic models. The results of the experiments show that there is a clear forecast benefit to allowing LAM states to influence one another during the analysis. In addition, adding LAM information at analysis time has a strong positive impact on global model forecast performance, even at points not covered by the LAMs.

Tidal Wave Propagation in the Yellow Sea

To investigate the near-field and far-field hydrodynamic conditions along the Jiangsu Coast in large scale, a two-dimensional tided wave model which covers the Bohai Sea, the Yellow Sea and the East China Sea is developed and validated. After a brief review of previous models, some influencing factors, such as tide generating force, river discharges as well as shoreline changes due to land reclamation, are examined in this study. We suggest that whether these factors should be considered in the model depends on the different purposes and geographical regions of interest. Then, a series of experiments are designed to further investigate the previously proposed important factors of influence [i.e. local bathymetry and the role of Shandong Peninsula (SDP)] on the tided motions in the Yellow Sea. The numerical experimental results show that the interaction between the tidal wave system in the northern Yellow Sea and the incoming tidal wave plays a main role on the formation of the rotating tidal wave system in the southern Yellow Sea, whereas the role of geometric position of the SDP is secondary. With respect to the tidal current, it is found that the radial shape of it is independent of the local bathymetry, but may be generated by the convergent tidal wave formed by the meeting of the rotating tidal wave in the southern Yellow Sea and the incoming tidal wave from the East China Sea. Furthermore, a certain water depth is crucial for the intensity of current velocity to generate the special topography of radial sand ridges.

An exact reanalysis technique for storm surge and tides in a geographic region of interest

Understanding the effects of storm surge in hurricane-prone regions is necessary for protecting public and lifeline services and improving resilience. While coastal ocean hydrodynamic models like ADCIRC may be used to assess the extent of inundation, the computational cost may be prohibitive since many local changes corresponding to design and failure scenarios would ideally be considered. We present an exact reanalysis technique and corresponding implementation that enable the assessment of local subdomain changes with less computational effort than would be required by a complete resimulation of the full domain. So long as the subdomain is large enough to fully contain the altered hydrodynamics, changes may be made and simulations performed within it without the need to calculate new boundary values. Accurate results are obtained even when subdomain boundary conditions are forced only intermittently, and convergence is demonstrated by progressively increasing the frequency at which they are applied. Descriptions of the overall methodology, performance results, and accuracy, as well as case studies, are presented.

Elicitation of erosional signature of a tropical river basin with high-resolution stereo data

The launch of Cartosat-1 turns into a new era for user communities of remote sensing and mapping. Generation of digital elevation model (DEM) of a particular geographic region of interest is the primary goal and advantage of Cartosat-1 mission. To generate the most accurate DEM from Cartosat-1 stereo data, 34 GCP points were used, and 122 tie points are automatically extracted with the aid of LPS-2011. Here, an attempt has been made to study the quantitative hypsometric analysis of six sub-watersheds of the Kuttiyadi River Basin (676 km2) with a humid tropical setting, using Cartosat-1 DEM. An extension, CalHypso, an add-on tool to ArcGIS 9.2, was utilized to synthesize hypsometric data from Cartosat-1 DEM which reflects the erosional signature of sub-watersheds based on geological stages of development. From hypsometric analysis, it is found that three sub-watersheds are in old stage, and the remaining three are of mature stage.