Global Positioning System Coordinates Research Articles

Rates and risk factors for human cutaneous anthrax in the country of Georgia: National surveillance data, 2008–2015

IntroductionAnthrax is endemic in the country of Georgia. The most common cutaneous anthrax form accounts for 95% of anthrax cases and often is self-resolving. Humans are infected from processing contaminated animal products, contacting sick animals, or by insect bites.ObjectiveWe aimed to describe the burden of human cutaneous anthrax and associated risk factors using the national surveillance data.MethodsWe extracted all human cutaneous anthrax cases from Electronic Integrated Disease Surveillance System (EIDSS) from 1 January 2008 to 31 December 2015. We conducted descriptive analyses to characterize the number of confirmed, probable and suspected cases by age groups, gender, ethnicity, year and geographic area.ResultsOut of 911 reported cutaneous anthrax cases, 299 (33%) were rejected. Out of remaining 612 cases, 437 (71%), 172 (28%), and 3 (<0.004%) were classified as confirmed, probable and suspected cases of cutaneous Anthrax, respectively; 467 (76.3%) were male. Georgians accounted for 56% (343/612) of cutaneous anthrax cases. Handling animal products (aOR 4.36, 95% CI 2.61–7.26) and living near pastoralist routes (aOR 2.74, 95%CI 1.57–4.76) were associated with cutaneous anthrax.ConclusionsThis study provides eight-year trends for cutaneous anthrax in humans in the country of Georgia. A comprehensive explanation for the observed rise and fall of the incidence rates of human cutaneous anthrax in 2008–2015 remains to be clarified but is likely associated with discontinuation of mandatory national livestock vaccination in 2008 coupled with weakened human and animal national health systems which were disrupted after the Soviet Union collapsed. Our analysis identifies living near pastoralist routes, handling animal products and travel to endemic areas within two weeks before the disease onset as risk factors for cutaneous anthrax. The evidence underscores the importance of One Health recommendations to activate anthrax awareness campaigns, supervise the destruction of known anthrax carcasses, record global position system coordinates of sites and disinfect infected soils and introduce a participatory health education tool on anthrax.

Personal and Occupational Exposure to Traffic-Related Fine Particulate Matter in Accra, Ghana

Background/Aim: Air pollution levels in fast-growing sub-Saharan African cities are among the highest in the world, but human exposure studies are limited, especially, traffic-related exposures. Our aim was to measure personal fine particulate matter (PM2.5) exposure of commercial minibus and taxi drivers (the most popular means of public transportation in Ghana’s capital), and street mobile vendors (hawkers) and street stationary vendors (vendors) in Accra, Ghana. Methods: We measured 24-hour personal PM2.5 exposure of 99 subjects, comprising 29 minibus drivers, 26 taxi drivers, 29 street vendors, and 15 street hawkers in the Accra metropolis. PM2.5 was measured both gravimetrically and continuously, with time-matched global positioning system coordinates. The instruments were placed in backpacks, which were worn by the vendors and hawkers during the 24-hour measurement period. Taxi drivers had the backpacks placed beside them near the front passenger’s seat. For the mini bus drivers, field assistants carried the backpacks on their laps at the front passenger’s seat and rode along the drivers. Results: Across all four occupational groups, average (SD) personal PM2.5 exposure was 56.4 (63.2) μg/m3; group means ranged from 26.0 μg/m3 for hawkers to 83.4 μg/m3 for taxi drivers. Individual exposure was &gt; 100 μg/m3 for some drivers. Exposure was significantly higher among drivers than vendors (78 vs 29 μg/m3; 95% CI: 28, 70; p-value &lt; 0.001). The highest exposure to the drivers occurred on major and secondary roads, although &lt; 20% of their commute time was spent there compared to minor roads and alleys. Conclusions: Our results support the need for urban air quality management plans that will address the role traffic to reduce exposure to the thousands who commute daily by minibuses and taxis or work near roadways in Accra, and when combined with policies to reduce urban biomass use, will greatly reduce urban population exposure in Accra.

Spatial distribution and habitat characterization of mosquito species during the dry season along the Mara River and its tributaries, in Kenya and Tanzania

BackgroundVector-borne diseases are increasingly becoming a major health problem among communities living along the major rivers of Africa. Although larger water bodies such as lakes and dams have been extensively researched, rivers and their tributaries have largely been ignored. This study sought to establish the spatial distribution of mosquito species during the dry season and further characterize their habitats along the Mara River and its tributaries.MethodsIn this cross-sectional survey, mosquito larvae were sampled along the Mara River, its two perennial tributaries (Amala and Nyangores), drying streams, and adjacent aquatic habitats (e.g. swamps, puddles that receive direct sunlight [open sunlit puddles], rock pools, hippo and livestock hoof prints, and vegetated pools). Each habitat was dipped 20 times using a standard dipper. Distance between breeding sites and human habitation was determined using global positioning system coordinates. The collected mosquito larvae were identified using standard taxonomic keys. Water physico-chemical parameters were measured in situ using a multiparameter meter. Mean mosquito larvae per habitat type were compared using analysis of variance and chi-square tests, while the relationship between mosquito larvae and physico-chemical parameters was evaluated using a generalized linear mixed model. The Cox-Stuart test was used to detect trends of mosquito larvae distribution. The test allowed for verification of monotonic tendency (rejection of null hypothesis of trend absence) and its variability.ResultsA total of 4001 mosquito larvae were collected, of which 2712 (67.8%) were collected from river/stream edge habitats and 1289 (32.2%) were sampled from aquatic habitats located in the terrestrial ecosystem about 50 m away from the main river/streams. Anopheles gambiae s.s, An. arabiensis, and An. funestus group, the three most potent vectors of malaria in Sub-Saharan Africa, together with other anopheline mosquitoes, were the most dominant mosquito species (70.3%), followed by Culex quinquefasciatus and Cx. pipiens complex combined (29.5%). Drying streams accounted for the highest number of larvae captured compared to the other habitat types. A stronger relationship between mosquito larvae abundance and dissolved oxygen (Z = 7.37, P ≤ 0.001), temperature (Z = 7.65, P ≤ 0.001), turbidity (Z = −5.25, P ≤ 0.001), and distance to the nearest human habitation (Z = 4.57, P ≤ 0.001), was observed.ConclusionsPresence of malaria and non-malaria mosquito larvae within the Mara River basin calls for immediate action to curtail the insurgence of vector-borne diseases within the basin. A vector control program should be conducted during the dry period, targeting drying streams shown to produce the highest number of larval mosquitoes.

Methods for sampling geographically mobile female traders in an East African market setting.

BackgroundThe role of migration in the spread of HIV in sub-Saharan Africa is well-documented. Yet migration and HIV research have often focused on HIV risks to male migrants and their partners, or migrants overall, often failing to measure the risks to women via their direct involvement in migration. Inconsistent measures of mobility, gender biases in those measures, and limited data sources for sex-specific population-based estimates of mobility have contributed to a paucity of research on the HIV prevention and care needs of migrant and highly mobile women. This study addresses an urgent need for novel methods for developing probability-based, systematic samples of highly mobile women, focusing on a population of female traders operating out of one of the largest open air markets in East Africa. Our method involves three stages: 1.) identification and mapping of all market stall locations using Global Positioning System (GPS) coordinates; 2.) using female market vendor stall GPS coordinates to build the sampling frame using replicates; and 3.) using maps and GPS data for recruitment of study participants.ResultsThe location of 6,390 vendor stalls were mapped using GPS. Of these, 4,064 stalls occupied by women (63.6%) were used to draw four replicates of 128 stalls each, and a fifth replicate of 15 pre-selected random alternates for a total of 527 stalls assigned to one of five replicates. Staff visited 323 stalls from the first three replicates and from these successfully recruited 306 female vendors into the study for a participation rate of 94.7%. Mobilization strategies and involving traders association representatives in participant recruitment were critical to the study’s success.ConclusionThe study’s high participation rate suggests that this geospatial sampling method holds promise for development of probability-based samples in other settings that serve as transport hubs for highly mobile populations.

SistematX, an Online Web-Based Cheminformatics Tool for Data Management of Secondary Metabolites.

The traditional work of a natural products researcher consists in large part of time-consuming experimental work, collecting biota to prepare and analyze extracts and to identify innovative metabolites. However, along this long scientific path, much information is lost or restricted to a specific niche. The large amounts of data already produced and the science of metabolomics reveal new questions: Are these compounds known or new? How fast can this information be obtained? To answer these and other relevant questions, an appropriate procedure to correctly store information on the data retrieved from the discovered metabolites is necessary. The SistematX (http://sistematx.ufpb.br) interface is implemented considering the following aspects: (a) the ability to search by structure, SMILES (Simplified Molecular-Input Line-Entry System) code, compound name and species; (b) the ability to save chemical structures found by searching; (c) compound data results include important characteristics for natural products chemistry; and (d) the user can find specific information for taxonomic rank (from family to species) of the plant from which the compound was isolated, the searched-for molecule, and the bibliographic reference and Global Positioning System (GPS) coordinates. The SistematX homepage allows the user to log into the data management area using a login name and password and gain access to administration pages. In this article, we introduced a modern and innovative web interface for the management of a secondary metabolite database. With its multiplatform design, it is able to be properly consulted via the internet and managed from any accredited computer. The interface provided by SistematX contains a wealth of useful information for the scientific community about natural products, highlighting the locations of species from which compounds are isolated.

Effect of GPS sample interval and paddock size on estimates of distance travelled by grazing cattle in rangeland, Australia

The distance travelled by an animal, when determined by using global positioning system (GPS) coordinates, is usually calculated assuming linear movement between the recorded coordinates. When using long sample intervals, some movement may be overlooked if linear movement between each recorded position is assumed, because of the tendency of livestock to move in meandering paths. Conversely, overestimation of the true distance travelled could occur with short sample intervals because of the accumulation of extra distance due to GPS measurement error. Data from 10 experiments were used to explore the effect of paddock size and GPS sampling rate on the calculation of distance travelled by free-ranging cattle. Shortening the sample interval increased apparent distance travelled according to a power function. As paddock size increased from &lt;1 ha to &gt;450 ha, distance travelled increased according to a logarithmic relationship; however, other variation between experiments could have affected these results. It was concluded that selecting an optimal GPS sampling interval is critical to accurately determining the distance travelled by free-ranging cattle.

Analysis of the impact of healthcare support initiatives for physically disabled people on their access to care in the city of Saint-Louis, Senegal

BackgroundPeople with disabilities represent approximately 6% of the Senegalese population. They face significant barriers to accessing health care. Although several initiatives have been implemented to improve access to health care for this vulnerable population, few studies have examined the effects of these initiatives. We conducted a mixed methods study in three neighborhoods in Saint-Louis City (Senegal) to assess the impact of health systems and social assistance programs aimed at improving access to health care for people with disabilities.MethodsData were collected from 105 people living with disabilities aged 1–49 years (or their caregivers). Interviews were also conducted with key stakeholders in the health and welfare sectors. Global Positioning System (GPS) coordinates of all the health and social services within the city were obtained. We also conducted observations in the main regional hospital, the district health center and three level-one health facilities to assess physical accessibility as well as interactions between patients living with disabilities and health and social workers. Descriptive and multivariate analyses were performed using Sphinx software. Spatial data were used to make cartographic representations of the proximity to basic social services using Arc GIS software.ResultsSeventy-nine percent of survey respondents reported difficulty obtaining treatment. Key barriers to care included the high cost of care, as well as ill-treatment by health workers. Limited human resources and low levels of financial support, combined with logistical challenges were reported to hamper the success of social welfare initiatives that aim to facilitate access to health care for people with disabilities.ConclusionOur results suggest that initiatives to increase access to health care among people with disability in Saint-Louis have had limited impact. Study findings underscore the importance of strengthening social assistance schemes within the health system and the need for social workers and health workers to collaborate to improve access to health care for people with disabilities.

Innovation or Violation? Leveraging Mobile Technology to Conduct Socially Responsible Community Research.

Mobile technology is increasingly being used to measure individuals' moods, thoughts, and behaviors in real time. Current examples include the use of smartphones to collect ecological momentary assessments (EMAs; assessments delivered "in the moment"); wearable technology to passively collect objective measures of participants' movement, physical activity, sleep, and physiological response; and smartphones and wearable devices with global positioning system (GPS) capabilities to collect precise information about where participants spend their time. Although advances in mobile technology offer exciting opportunities for measuring and modeling individuals' experiences in their natural environments, they also introduce new ethical issues. Drawing on lessons learned while collecting GPS coordinates and EMAs measuring mood, companionship, and health-risk behavior with a sample of low-income, predominantly racial/ethnic minority youth living in Chicago, this manuscript discusses ethical challenges specific to the methodology (e.g., unanticipated access to personal information) and broader concerns related to data conceptualization and interpretation (e.g., the ethics of "monitoring" low-income youth of color). While encouraging researchers to embrace innovations offered by mobile technology, this discussion highlights some of the many ethical issues that also need to be considered.

Mobile Phone Detection of Semantic Location and Its Relationship to Depression and Anxiety.

BackgroundIs someone at home, at their friend’s place, at a restaurant, or enjoying the outdoors? Knowing the semantic location of an individual matters for delivering medical interventions, recommendations, and other context-aware services. This knowledge is particularly useful in mental health care for monitoring relevant behavioral indicators to improve treatment delivery. Local search-and-discovery services such as Foursquare can be used to detect semantic locations based on the global positioning system (GPS) coordinates, but GPS alone is often inaccurate. Mobile phones can also sense other signals (such as movement, light, and sound), and the use of these signals promises to lead to a better estimation of an individual’s semantic location.ObjectiveWe aimed to examine the ability of mobile phone sensors to estimate semantic locations, and to evaluate the relationship between semantic location visit patterns and depression and anxiety.MethodsA total of 208 participants across the United States were asked to log the type of locations they visited daily, using their mobile phones for a period of 6 weeks, while their phone sensor data was recorded. Using the sensor data and Foursquare queries based on GPS coordinates, we trained models to predict these logged locations, and evaluated their prediction accuracy on participants that models had not seen during training. We also evaluated the relationship between the amount of time spent in each semantic location and depression and anxiety assessed at baseline, in the middle, and at the end of the study.ResultsWhile Foursquare queries detected true semantic locations with an average area under the curve (AUC) of 0.62, using phone sensor data alone increased the AUC to 0.84. When we used Foursquare and sensor data together, the AUC further increased to 0.88. We found some significant relationships between the time spent in certain locations and depression and anxiety, although these relationships were not consistent.ConclusionsThe accuracy of location services such as Foursquare can significantly benefit from using phone sensor data. However, our results suggest that the nature of the places people visit explains only a small part of the variation in their anxiety and depression symptoms.

Spatial variability of selected soil micronutrients under smallholder crop production in Zanyokwe, Eastern Cape, South Africa

Understanding spatial variability of soil nutrients, including that of micronutrients, is important for establishing best management practices in smallholder crop production. The objective of this study was to determine the status and spatial variability of potentially available zinc (Zn), copper (Cu), manganese (Mn) and iron (Fe) for selective management at Zanyokwe Irrigation Scheme. Soil samples were collected from the 0–20 cm depth on 50 m × 50 m grids and coordinates of the sampling points were recorded using a global positioning system (GPS). The samples were analysed for Zn, Cu, Mn and Fe after extraction with EDTA. The GPS coordinates and corresponding micronutrient values were interpolated using simple kriging to produce continuous raster surfaces, which were then reclassified, using prescribed limits, to produce soil micronutrient maps. Zinc was deficient and exhibited the highest spatial variability, within short distances. There was limited spatial variability of Cu, Mn and Fe. The study highlighted the need for the creation of management zones for Zn availability. Field studies are recommended to establish the extent to which Zn is limiting yields and nutritional quality of crops grown at the scheme.

MAPPING HEALTH FACILITY CHARACTERISTICS AND LOCATION IN RURAL TANZANIA

BACKGROUND: Optimization of care-seeking for pregnancy, delivery, and child health could reduce global maternal child mortality, especially in rural Africa. However, limited documentation of location, services, and staffing hamper facility-strengthening initiatives. OBJECTIVES: A mapping exercise collected basic information and global positioning system (GPS) data to characterize health facilities in two Tanzanian districts. DESIGN/METHODS: Research assistants administered a questionnaire about health facility information (i.e. maternal, newborn and child health (MNCH) services offered, staffing) verbally to in-charges at each site. GPS coordinates were recorded and delivery areas were photographed with Garmin Oregon 650 receivers. Frequencies were analysed in SPSS. Individual shapefiles for GPS waypoints and track logs were merged, producing single shapefiles of all health facilities and access routes. RESULTS: Over six days, 102 sites were visited, including three previously unlisted facilities. Four percent were hospitals, 10% health centres (HCs) and 85% dispensaries (91% public, 9% private). Most facilities were rural (86%) or mixed (9%). Ninety percent reported delivery capacity; 6% offered advanced delivery services (i.e. Caesarean sections, blood transfusions). 19,210 deliveries were reported in the preceding year (40% at hospitals, 19% at HCs, 41% at dispensaries); 46% of deliveries occurred at advanced delivery sites. On staff were a total of 20 medical officers for a doctor to population ratio of 1: 42,168. Other payroll staff included 95 clinical officers, 444 nurses, and 243 medical attendants. On day of survey, 50% of payroll staff were present; 22% of delivery-conducting sites lacked any mid-level health provider. Maps detailing precise location of all health facilities and road networks (including previously unknown roads) were produced. CONCLUSION: This mapping exercise combined technical and practical information, yielding creation of a useful database and functional maps. Visual representation of MNCH services was well received by project and health planners. This relatively small investment will subsequently enable higher quality of data collection and ease of project planning.

Map-Matching Poor-Quality GPS Data in Urban Environments: The pgMapMatch Package

Global Positioning System (GPS) data have become ubiquitous in many areas of transportation planning and academic research. The usefulness of GPS data often depends on the points being matched to the underlying street network – a process known as “map matching.” Formally, the map-matching problem is to identify the true path, consisting of a sequence of street edges (i.e. blocks, or segments between intersections), given a sequence of GPS coordinates. Several algorithms have been developed to map-match GPS data. However, there are three major shortcomings of existing approaches. First, some algorithms assume that the user takes the fastest route, and does not circle or deviate. This is an inappropriate assumption in contexts where drivers circle in search of a parking space or have a personal preference for a circuitous route. Second, published algorithms often leave the implementation to the user, and do not provide code or a software implementation. Third, when map-matching large datasets where the matches cannot be individually inspected, published algorithms do not provide a way to evaluate the likelihood that the match is correct. This paper presents a new map-matching algorithm that is designed for use with poor-quality, heterogeneous GPS traces in urban environments, where drivers may circle for parking and GPS quality may be affected by underground parking, tall buildings and similar obstacles. The paper is accompanied by open-source Python code that is designed to work with PostGIS spatial databases. In a test dataset that includes many poor-quality traces, our new algorithm accurately matched 87% of traces, compared to 67% in a widely available alternative.

Real Time GPS for Railway Automation System

The concept of the paper idea is to automate the railways system. We are using the idea of Global Position system(GPS) for tracking every trains and a proposed system by which every trains are personally monitored and passing necessary messages to the individual trains .The train with the GPS Module and GSM module on board. This would enable passenger can simply query the location of a train via SMS from his mobile phone but will also enable us to provide real time train tracking system. It is developed with a goal to reduce the waiting time of the passenger. The train units will response to the user mobile with the GPS coordinates of the present location of trains. There is a base station where the train movement will be displayed on a screen. The motivation for the paper came from due to the lack of control over railways in India as we hardly get to know the exact position of the train while standing at the station. Method of Metro implements modern techniques to control the railways motivate us to design a system for the complete railway system.

A wireless oxygen saturation and heart rate monitoring and alarming system based on the Qatar Early Warning Scoring system

Background: Peripheral oxygen saturation (SpO2) and heart rate (HR) are important indicators for various medical conditions such as cardiopulmonary disorders and respiratory diseases. The main objectives of this study is to design and implement a portable embedded medical system. This system wirelessly obtains SpO2 and HR data from a patient as well as his/her coordination, and sends a short messaging service (SMS) alarm to the emergency control room to contact the patient and confirm his/her health status or dispatch an ambulance in case of his/her measurements are outside the normal range based on the Qatar Early Warning Scoring (QEWS) system. Methods: The system mainly consists of a Bluetooth finger pulse oximeter, a Bluetooth-enabled microcontroller, a global positioning system (GPS) and a General Packet Radio Service (GPRS) module. It is divided into three main stages. In the first stage, the readings of SpO2 and HR are obtained from the patient in real time. During the second stage, the readings obtained are sent over Bluetooth to the signal acquisition and processing unit. The received data is processed and a decision is made whether a SMS alarm should be sent or not. The final stage is concerned with sending the alarming SMS to the emergency control room over the GPRS network based on the QEWS system. Results: The system was implemented and successfully tested as a stand-alone unit by avoiding the use of a PC or a smartphone for data processing. The transmitted SMS alarm includes the SpO2 and HR readings, the QEWS score and the GPS coordinates. Conclusions: The designed system is wireless, portable, and user-friendly. This system possibly promotes quality of care for the patient living outside hospital and could improve response time from an ambulance service point of view by determining the exact location of the patient.

Real-Time Monitoring of Vaccination Campaign Performance Using Mobile Phones - Nepal, 2016.

In 2012, the Global Vaccine Action Plan* established a goal to achieve measles and rubella elimination in five of the six World Health Organization (WHO) regions (194 countries) by 2020 (1). Measles elimination strategies aim to achieve ≥95% coverage with 2 routine doses of measles-containing vaccine (2), and implement supplementary immunization activities (SIAs)† in settings where routine coverage is low or where there are subpopulations at high risk. To ensure SIA quality and to achieve ≥95% SIA coverage nationally, rapid convenience monitoring (RCM) is used during or immediately after SIAs (3,4). The objective of RCM is to find unvaccinated children and to identify reasons for nonvaccination in areas with persons at high risk, to enable immediate implementation of corrective actions (e.g., reassigning teams to poorly vaccinated areas, modifying the timing of vaccination, or conducting mop-up vaccination activities). This report describes pilot testing of RCM using mobile phones (RCM-MP) during the second phase of an SIA in Nepal in 2016. Use of RCM-MP resulted in 87% timeliness and 94% completeness of data reporting and found that, although 95% of children were vaccinated, 42% of areas required corrective vaccination activities. RCM-MP challenges included connecting to mobile networks, small phone screen size, and capturing Global Positioning System (GPS) coordinates. Nonetheless, use of RCM-MP led to faster data transmission, analysis, and decision-making and to increased accountability among levels of the health system.

Fast initial acquisition based on estimation of uncertain regions and rectangle honeycomb spiral scanning

This paper proposes a fast initial acquisition method for light beacons realized by estimating uncertain regions and rectangle honeycomb spiral scanning. First compute with the global position system (GPS) coordinates of both terminals to obtain the azimuth angle and the pitch angle of an optical antenna, which rotates accordingly and roughly points to the light beacon. Then the uncertain regions are estimated by the measurement errors of the GPS coordinates. The optical antenna scans in the uncertain regions to lead the beacon into the field of view of the charge-coupled device and achieve initial acquisition for the beacon light. Besides, analyze the topology, the speed and the coverage areas of the rectangle honeycomb spiral scanning, conduct fast acquisition experiments with a two-dimensional platform in the estimated uncertain regions. The results verify that fast initial acquisition for beacons can be achieved with the proposed method.

Examining environmental drivers of spatial variability in aflatoxin accumulation in Kenyan maize: Potential utility in risk prediction models

Maize, a staple food in most African countries, is prone to contamination by aflatoxins, toxic secondary metabolites mainly produced by Aspergillus flavus and A. parasiticus . Aflatoxins are known to cause liver cancer, and chronic exposure has been linked to other adverse health outcomes including growth faltering in children. To mitigate exposure in maize-dependent populations, there is need to identify the factors associated with aflatoxin contamination. This is difficult, however, because of high sampling cost and lack of affordable and accurate analytical methods. Publicly available, remotely-sensed data on vegetation, precipitation, and soil properties could be useful in predicting locations at risk for aflatoxin contamination in maize. This study investigates the utility of publicly available remotely-sensed data on rainfall, vegetation cover (indicated by normalized difference vegetation index or NDVI), and soil characteristics as potential predictors of aflatoxin contamination in Kenyan maize. Aflatoxin was analyzed in maize samples (n=2466) that were collected in 2009 and 2010 at 243 local hammer mills in eastern and western Kenya. Overall, 60% of maize samples had detectable aflatoxin. Global positioning system coordinates of each mill location were linked to remotely-sensed, spatially explicit indicators of average monthly NDVI, total monthly rainfall, and soil properties. Higher rainfall and vegetation cover during the maize pre-flowering period were significantly associated with higher prevalence of aflatoxin contamination. Conversely, higher rainfall and vegetation cover during the maize flowering and post-flowering periods (not including harvest) were associated with lower prevalence of aflatoxin contamination. Water stress throughout the growing season may cause increased plant susceptibility to fungal colonization and aflatoxin accumulation. Soil organic carbon content, pH, total exchangeable bases, salinity, texture, and soil type were significantly associated with aflatoxin. In conclusion, this study shows that remotely-sensed data can be regressed on available aflatoxin data highlighting important potential predictors that could reduce the cost of data collection and the cost of aflatoxin risk forecasting models. Keywords: Aflatoxin, GIS, NDVI, soil characteristics, rainfall, mycotoxins, East Africa, Kenya

IMAGE NETWORK GENERATION OF UNCALIBRATED UAV IMAGES WITH LOW-COST GPS DATA

Abstract. The use of unmanned air vehicle (UAV) images acquired by a non-metric digital camera to establish an image network is difficult in cases without accurate camera model parameters. Although an image network can be generated by continuously calculating camera model parameters during data processing as an incremental structure from motion (SfM) methods, the process is time consuming. In this study, low-cost global position system (GPS) information is employed in image network generation to decrease computational expenses. Each image is considered as reference, and its neighbor images are determined based on GPS coordinates during processing. The reference image and its neighbor images constitute an image group, which is used to generate a free network through image matching and relative orientation. Data are then transformed from the free network coordinate system of each group into the GPS coordinate system by using the GPS coordinates of each image. After the exterior elements of each image are determined in the GPS coordinate system, the initial image network is established. Finally, self-calibration bundle adjustment constrained by GPS coordinates is conducted to refine the image network. The proposed method is validated on three fields. Results confirm that the method can achieve good image network when accurate camera model parameters are unavailable.

IMAGE NETWORK GENERATION OF UNCALIBRATED UAV IMAGES WITH LOW-COST GPS DATA

The use of unmanned air vehicle (UAV) images acquired by a non-metric digital camera to establish an image network is difficult in cases without accurate camera model parameters. Although an image network can be generated by continuously calculating camera model parameters during data processing as an incremental structure from motion (SfM) methods, the process is time consuming. In this study, low-cost global position system (GPS) information is employed in image network generation to decrease computational expenses. Each image is considered as reference, and its neighbor images are determined based on GPS coordinates during processing. The reference image and its neighbor images constitute an image group, which is used to generate a free network through image matching and relative orientation. Data are then transformed from the free network coordinate system of each group into the GPS coordinate system by using the GPS coordinates of each image. After the exterior elements of each image are determined in the GPS coordinate system, the initial image network is established. Finally, self-calibration bundle adjustment constrained by GPS coordinates is conducted to refine the image network. The proposed method is validated on three fields. Results confirm that the method can achieve good image network when accurate camera model parameters are unavailable.

Accelerometer and GPS Analysis of Trail Use and Associations with Physical Activity and Sedentary Time

PURPOSE: The combined use of accelerometers and global positioning system (GPS) devices may provide insights into how trails can support physical activity (PA) and an alternative approach for objectively measuring specific activities on trails, such as cycling. The aims of this study were to examine associations between trail use and PA and sedentary behavior (SB) and to quantify on-trail PA with accelerometer activity counts only and then with a combination of accelerometer and GPS data. METHODS: Participants (N=141, 53% female, 19-78 y), who were recruited on five trails in Massachusetts, wore an Actigraph 7164 accelerometer and a GeoStats GPS data logger concurrently for 1-4 days. Total PA (daily mean counts·min-1), and daily minutes of light (LPA=100-759 counts), moderate (MPA=760-5724), and vigorous PA (VPA≥5725), and SB (0-99) were derived from activity counts. A trail use day was defined as a day on which a participant engaged in a minimum of 2 consecutive minutes of activity on a trail as determined by GPS coordinates. Mixed linear models were used to examine whether trail use was associated with PA outcomes and SB, controlling for demographics, trail site, weekday/weekend trail use, SB for PA outcomes, and PA (all intensities) for SB outcome. Intensity of PA on trails was quantified using counts only and a combination of counts and GPS speed. Ainsworth’s compendium was used to classify intensity based on the metabolic equivalent levels for different cycling speeds. RESULTS: Trail use had positive associations with LPA (β=7.7 min·d-1, p=0.04), MPA (β=28.3 min·d-1, p<.0001), and total PA (β=522 counts·min-1, p<.0001). Trail use was not associated with VPA or SB. Minutes of activity on trails classified as VPA increased by 346% when counts and GPS speed were used to define intensity, compared to using activity counts only. On-trail LPA, MPA, and SB decreased by 15%, 91%, and 85%, respectively. CONCLUSION: Adults accumulated more LPA, MPA, and total PA on days when they used trails, indicating the importance of these resources for supporting regular PA. The combination of GPS and accelerometer data may be useful for classifying PA intensity on trails where individuals are likely to be cycling. Supported by funding from the Active Living Research Program, the Robert Wood Johnson Foundation.