Geospatial Variability Research Articles

Quantifying diurnal and seasonal variation of surface urban heat island intensity and its associated determinants across different climatic zones over Indian cities

ABSTRACT Surface urban heat island (SUHI) is a major anthropogenic alteration of Earth’s surface and can influence the local thermal environment by altering the surface energy flux balances. Researchers have paid much attention to SUHI studies in the last decades; still, its geospatial variability over a larger area is poorly understood. Detailed research is required to understand the mechanism and dynamics of SUHI along with its different driving variables. Hence in this study, we quantified the diurnal, seasonal, and interannual variation of SUHI intensity (SUHII) over 150 major Indian cities situated over different climatic zones using MODIS data from 2003 to 2018. The results reveal urban cool islands occurrence over the hot desert, hot steppe, and tropical monsoon climatic zone during daytime in both summer (−0.25 to −0.17°C) and winter (−0.33 to 0.17°C) season. In contrast, nighttime SUHII shows clear evidence of positive urban heat island irrespective of climatic region and seasonal variation of 0.48–1°C in summer and 0.46–1.32°C in winter is seen. The Mann–Kendall and Sen’s slope estimator tests are used to detect the trend of the SUHII during the study period, which suggests a higher percentage of cities showing an increasing trend of SUHII for urban heat islands than the cities of the urban cool island. Pearson’s correlation and stepwise multiple linear regression model determine the possible SUHII controlling variable over different climatic zones. During the daytime, the SUHII’s distribution is controlled by vegetation, evapotranspiration, and thermal inertia in the summer/winter season. Whereas, it is linked tightly to built-up intensity, white sky albedo, and thermal inertia in both seasons during nighttime. Overall, we found that the stepwise multiple linear regression model can explain the SUHII variance more in the daytime (>0.8) than in nighttime (>0.7, except for tropical cities) and more in understanding the SUHII behaviors for cool cities as compared to hot cities. Moreover, this study also quantifies the significant control of thermal inertia and soil moisture in understating urban heat and cool island behavior over different climatic zones.

Particulate matter exposure predicts residence in high-risk areas for community acquired pneumonia among hospitalized children.

Particulate matter exposure is a risk factor for lower respiratory tract infection in children. Here, we investigated the geospatial patterns of community-acquired pneumonia and the impact of PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) on geospatial variability of pneumonia in children. We performed a retrospective analysis of prospectively collected population-based surveillance study data of community-acquired pneumonia hospitalizations among children <18 years residing in the Memphis metropolitan area, who were enrolled in the Centers for Disease Control and Prevention sponsored Etiology of Pneumonia in the Community (EPIC) study from January 2010 to June 2012. The outcome measure, residence in high- and low-risk areas for community-acquired pneumonia, was determined by calculating pneumonia incidence rates and performing cluster analysis to identify areas with higher/lower than expected rates of community-acquired pneumonia for the population at risk. High PM2.5 was defined as exposure to PM2.5 concentrations greater than the mean value (>10.75 μg/m3), and low PM2.5 is defined as exposure to PM2.5 concentrations less than or equal to the mean value (≤10.75 μg/m3). We also assessed the effects of age, sex, race/ethnicity, history of wheezing, insurance type, tobacco smoke exposure, bacterial etiology, and viral etiology of infection. Of 810 (96.1%) subjects with radiographic community-acquired pneumonia, who resided in the Memphis metropolitan area and had addresses which were successfully geocoded (Supplementary Figure F2), 220 (27.2%) patients were identified to be from high- (n = 126) or low-risk (n = 94) community-acquired pneumonia areas. Community-acquired pneumonia in Memphis metropolitan area had a non-homogenous geospatial pattern. PM2.5 was associated with residence in high-risk areas for community-acquired pneumonia. In addition, children with private insurance and bacterial, as opposed to viral, etiology of infection had a decreased risk of residence in a high-risk area for community-acquired pneumonia. The results from this paper suggest that environmental exposures as well as social risk factors are associated with childhood pneumonia.

Geospatial Variability and Distribution of Rainfall and Temperature Extreme Indices in the Jimma Zone, Southwest Ethiopia

Abstract Floods, droughts, and heat waves are becoming increasingly common in Ethiopia due to the increasing frequency and intensity of extreme weather events, devastating the country's massive rain-fed agricultural sector. The purpose of the study was to examine the geographic distribution and volatility of extreme rainfall and temperature indicators in the Jimma zone of the regional state of Ormomia, Ethiopia. The historical data for the study zone was collected from 10 observation sites. Rainfall and temperature indicators were extracted from a daily data set using the Climpact2 software. For further analysis and mapping, twelve relevant indicators were selected and subjected to descriptive statistics, MANOVA and linear regression tests. The results show that four indicators of rainfall: CDD, R10m, R95P and R99P and four temperature indicators: TN10P, TN90P, TX10P and TX10P show a large statistical variability (CV> 30%). Their geographic distribution also varied across the study area, with TNx, TX10p, TXn, TXx and CDD dominated the eastern part and TN10P and TNn dominated the western parts of the study area. The TN90P and TX90P also dominated the central part of the study area. The results of the trend analysis also show positive and negative trends. TN10P and TX10P decreased significantly (P <0.05), while TN90P, TXn and TXx all showed significant increases in time trends (P <0.05). Some of the indicators; CDD, R95P, R99P, TX90P and TNx all showed non-significantly increasing trend, while R10m and TNn both showed non-significantly decreasing trend. The study, therefore, explicitly shows which and where extreme rainfall and temperature indicators in the study area vary and are significantly higher. We propose that improving environmental and forest development strategies remains imperative.

Is the source of domestic water associated with the risk of malaria infection? Spatial variability and a mixed-effects multilevel analysis

BackgroundThere is a dearth of information on the relationship between domestic water source and malaria infection in malaria-endemic regions such as Tanzania. This study examined the geospatial variability and association between domestic water source and malaria prevalence in Tanzania. MethodsWe analyzed data from a sample of 6707 children, aged 6–59 months, from the 2017 Tanzania Malaria Indicator Survey. The outcome variable was the result of malaria testing (positive or negative) and the main explanatory variable was domestic water source (piped or non-piped). Random effect variables were administrative region and geographical zone. ArcGIS 10.7 was used to create geospatial distribution maps. A STATA MP 14.0 was used to fit a mixed-effects multilevel logistic regression to examine the factors associated with malaria prevalence. ResultsThe prevalence of malaria and non-piped domestic water source was respectively 7.3% and 59.6%. The regions and zones with a higher prevalence of malaria also had a higher percentage of non-piped water. There was a statistically significant variation in the risk of malaria across the regions (variance = 1.27; 95% CI, 0.40−4.07) and zones (variance = 4.75; 95% CI, 1.46−15.46). The final fixed-effects model showed that non-piped domestic water was significantly associated with malaria prevalence (adjusted odds ratio (AOR) = 2.18; 95% CI, 1.64−2.89; P < 0.001). ConclusionsA non-piped source of domestic water was independently associated with positive testing for malaria. Moreover, regions with a high percentage of non-piped domestic water had a correspondingly high prevalence of malaria.

The southern rural health and mortality penalty: A review of regional health inequities in the United States.

Rural-urban differences in morbidity and mortality across the United States have been well documented and termed the "rural mortality penalty". However, research studies frequently treat rural areas as homogeneous and often do not account for geospatial variability in rural health risks by both county, state, region, race, and sex within the United States. Additionally, people living in the rural South of the US have higher rates of morbidity and mortality compared to both their urban counterparts and other rural areas. Of those living in southern rural communities, people of color experience higher rates of death and disease compared to white populations. Although there is a wealth of research that uses individual-level behaviors to explain rural-urban health disparities, there is less focus on how community and structural factors influence these differences. This review focuses on the "southern rural health penalty", a term coined by the authors, which refers to the high rate of mortality and morbidity in southern rural areas in the USA compared to both urban areas and non-southern rural places. We use macrosocial determinants of health to explain possible reasons for the "southern rural health penalty". This review can guide future research on rural health between southern and non-southern populations in the US and examine if macrosocial determinants of health can explain health disparities within southern rural populations.

WRF-Simulated Springtime Low-Level Jets over Iowa: Implications for Wind Energy

High-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize the frequency, intensity, height, and duration of springtime low-level jets (LLJ) and their implications for wind energy resource assessment and planning in Iowa. The time evolution of short-duration LLJ is analyzed to understand wind behavior around LLJ events and to illustrate their importance for high-frequency (few hours) variability in wind speeds and rotor plane turbulent kinetic energy (TKE). During spring, the LLJ core height has a spatiotemporal mean value of 217 m, but the LLJ depth means it frequently intersects typical wind turbine rotor planes. Nearly one-quarter of LLJ exhibit a maximum within the height interval 50-150 m AGL. LLJ profiles are found to have higher mean wind speeds across typical wind turbine rotor planes than non-LLJ profiles and to exhibit lower values of TKE. LLJ occur under stable stratification (i.e. positive Richardson numbers) and are associated with low TKE and the occurrence of high vertical wind shear. The frequency and duration of LLJ exhibit geospatial variability across Iowa with highest values in the northeast of the state. Analyses of daytime and night-time LLJ indicate topographic variability is an important factor in the development of LLJ.

Spatial characteristics and temporal evolution of the relationship between PM2.5 and aerosol optical depth over the eastern USA during 2003–2017

Abstract Previous research has proposed use of satellite-retrieved aerosol optical depth (AOD) to generate geospatial assessments of near-surface PM2.5 mass concentrations and potentially to provide air quality forecasts. Spatiotemporal variability in PM2.5–AOD relationships over the eastern United States of America are analyzed using surface observations, satellite data, reanalysis data, and WRF-Chem simulations. Three primary metrics are analyzed: eta (η, the ratio of PM2.5 to AOD), the correlation coefficient (ρ) between daily values of PM2.5 to AOD, and hit rate (θ, defined as co-occurrence of high PM2.5 and AOD). It is shown that mean daily η exhibits substantial geospatial variability and a pronounced seasonal cycle. η computed for 301 EPA stations ranges from 21 to 155 μg m−3 and has a domain-wide median value of 70 μg m−3. Larger values of η occur in winter and fall. There is also evidence of diurnal variability in η. Lower values are derived in analyses using AOD from Terra (i.e. the morning overpass) than when AOD from the MODIS instrument onboard Aqua (i.e. the afternoon overpass). The spatial median η from Terra is 70 vs. 93 μg m−3 from Aqua. A majority of sites exhibit statistically significant lower values of η, ρ, and θ during 2013–2017 than 2003–2007, indicating a declining association between AOD and PM2.5. This has implications for the potential to use remotely-sensed AOD to generate geospatial estimates of near-surface PM2.5. The spatial distribution of η across the 301 locations exhibits a negative dependence on planetary boundary layer height and 10 m wind speed and a positive dependence on integrated humidity in lower troposphere, urban fraction, 2 m temperature, and vegetation coverage. Simulations with WRF-Chem indicate model-derived estimates of η, ρ, and θ are highly dependent on the aerosol scheme employed but the model captures some of the spatial variability and the correct dependence of η on meteorological and land use causes of that variability.

Geospatial immune variability illuminates differential evolution of lung adenocarcinoma.

Remarkable progress in molecular analyses has improved our understanding of the evolution of cancer cells toward immune escape1-5. However, the spatial configurations of immune and stromal cells, which may shed light on the evolution of immune escape across tumor geographical locations, remain unaddressed. We integrated multiregion exome and RNA-sequencing (RNA-seq) data with spatial histology mapped by deep learning in 100 patients with non-small cell lung cancer from the TRACERx cohort6. Cancer subclones derived from immune cold regions were more closely related in mutation space, diversifying more recently than subclones from immune hot regions. In TRACERx and in an independent multisample cohort of 970 patients with lung adenocarcinoma, tumors with more than one immune cold region had a higher risk of relapse, independently of tumor size, stage and number of samples per patient. In lung adenocarcinoma, but not lung squamous cell carcinoma, geometrical irregularity and complexity of the cancer-stromal cell interface significantly increased in tumor regions without disruption of antigen presentation. Decreased lymphocyte accumulation in adjacent stroma was observed in tumors with low clonal neoantigen burden. Collectively, immune geospatial variability elucidates tumor ecological constraints that may shape the emergence of immune-evading subclones and aggressive clinical phenotypes.

ТРИНІТАРНИЙ ПІДХІД ДО РОЗУМІННЯ ПРЕДМЕТА ДОСЛІДЖЕННЯ СУСПІЛЬНОЇ ГЕОГРАФІЇ

The article uses inductive and deductive approaches to justify the trinitarian approach to understanding the subject of research in human geography. In the framework of the inductive approach the feasibility and the features of formulation of this subject for a sample of thirty candidate dissertations on the speciality “Economic and Social Geography” are studied. The substantive conclusions about the actual non-unitary nature of the research subject in the dissertations and the need to improve its wording have been made. Proposed trinitarian understanding of the subject of study of social geography, as the unity of the three components: the geospheric interdependence of terrestrial phenomena, geospatial variability of social phenomena and the geotorial organization of society. These components generally correspond to the points of the subject of research in specific human-geographical works and generalize them. Each of the components of the subject of research has been characterized and their content is disclosed. The first component is the study of natural and social prerequisites and factors of the investigated object, its factor and resultant features, the essential laws and regularities of deterministic or statistical interrelationships between the investigated features at each point of the geospatial. The second component is the study of the spatial characteristics of the propagation of the phenomena studied, the study of the features of the phenomena under study in different places of the geospatial. The third component is the study of the relative positioning in the space of the earth's surface, geospatial connections and flows, territorial formations and the functioning of these entities, that is, knowledge of the geotorial organization of society includes knowledge of geopositionality, georelation, geointegration, geofunctionality. Separately, the problem of the functional aspect in social geography is considered and the conclusion about its necessary presence in all three components of the trinitary subject of research is made. In the framework of the deductive approach, three cognitive dichotomies are proposed and considered: knowledge of the phenomenon – knowledge of the essence, extra-spatial cognition – spatial cognition, qualitative knowledge – quantitative cognition. The close connection between the components of the trinitarian approach with combinations of alternatives to cognitive dichotomies and the patterns of such a connection are shown. An appropriate classification of laws and regularities of human geography is proposed based on the Trinitarian approach to understanding the subject of its research. The proposed structure of mathematical social geography, which corresponds to the trinitarian understanding of the subject of research, and the corresponding mathematical-geographical models are determined. In the framework of the second block of, the classifications of centrography methods are proposed.

Ocean Circulation in the Western Gulf of Mexico Using Self‐Organizing Maps

AbstractThe ocean circulation in the western Gulf of Mexico is influenced by Loop Current eddies (LCEs), which affect the thermohaline structure and distribution of environmental variables as well as the design and management of offshore structures and maritime activities. In this study, we assess the ocean circulation and its variability by applying dual self‐organizing maps (SOMs) to a 20‐year data set (1993–2012) of salinity and currents at a depth of 200 m from a Hybrid Coordinate Ocean Model. The geospatial variability is characterized via a 7 × 7 SOM, which is further grouped into seven patterns, while the temporal variability is characterized as six distinct regions using a 2 × 3 SOM. The influence of LCEs on the upper slope occurs along the 200‐m isobath, a zone under constant pressure by strong currents from impacting eddies. The temporal pattern variability also reveals a clear zone of LCE impact on the continental slope (between latitudes 22°N and 25°N) and a dominant offshore transport pattern around latitudes 25°N to 26°N. A rectified wavelet power spectral analysis reveals a frequency of LCE impact oscillating around four to five months with an estimated ring lifespan of 1 year.

Hybrid Resiliency-Stressor Conceptual Framework for Informing Decision Support Tools and Addressing Environmental Injustice and Health Inequities.

While structural factors may drive health inequities, certain health-promoting attributes of one’s “place” known as salutogens may further moderate the cumulative impacts of exposures to socio-environmental stressors that behave as pathogens. Understanding the synergistic relationship between socio-environmental stressors and resilience factors is a critical component in reducing health inequities; however, the catalyst for this concept relies on community-engaged research approaches to ultimately strengthen resiliency and promote health. Furthermore, this concept has not been fully integrated into environmental justice and cumulative risk assessment screening tools designed to identify geospatial variability in environmental factors that may be associated with health inequities. As a result, we propose a hybrid resiliency-stressor conceptual framework to inform the development of environmental justice and cumulative risk assessment screening tools that can detect environmental inequities and opportunities for resilience in vulnerable populations. We explore the relationship between actual exposures to socio-environmental stressors, perceptions of stressors, and one’s physiological and psychological stress response to environmental stimuli, which collectively may perpetuate health inequities by increasing allostatic load and initiating disease onset. This comprehensive framework expands the scope of existing screening tools to inform action-based solutions that rely on community-engaged research efforts to increase resiliency and promote positive health outcomes.

Geospatial Distribution of Some Phosphorus and Potassium Forms as Influenced by Period of Irrigation in the Kano River and the Hadejia Valley Irrigation Schemes, Nigeria.

This study was carried out at Kano River Irrigation Project (KRIP) (latitudes 11º 36ʹ 0.05ʺ N to 11º 49ʹ 57.97ʺ N and longitudes 8º 28ʹ 17.02ʺ E to 8º 29ʹ 41.82ʺ E) and Hadejia Valley Irrigation Project (HVIP) (latitudes 12º 17ʹ 48.75ʺ N to 12º 24ʹ 58.28ʺ N and longitudes 9º 51ʹ 31.29ʺ E to 10º 2ʹ17.42ʺ E). The soils are largely deep, well-drained Calcic Luvisols. The aim was to assess the geospatial distribution of some plant-nutrition related forms of P and K. A total of 37 and 19 irrigation sectors were identified in KRIP and HVIP respectively. Google earth was used to tag 109 and 41 sampling points randomly within both developed and undeveloped sectors of KRIP and HVIP respectively. With the aid of projects’ sitemaps, the sectors were demarcated into six periods of irrigation: 0 years (Non -irrigated), 1-10 years, 10-19 years, 20-29 years, 30-39 years and ≥ 40 years as applicable. GPS was used to track the tagged points at the time of sampling. Sur- face soil samples were collected by augering to 30 cm depth with fabricated steel augers. Samples were analyzed for physical and chemical properties. Available (AP) and total (TP) forms of P as well as water-soluble (WSK), exchangeable (Ex. K) and non-exchangeable (NEK) forms of K were analyzed. Basic soil prop- erties were compared by ANOVA using JMP version 12. Geostatistical analysis and Geospatial variability of various forms of P and K were performed with the GS+ software (version 10). Ordinary Kriging was used for the spatial interpola- tion. Texturally, the soils of the KRIP was sandy loam while that of the HIVP was predominantly sandy clayey loam. The pH (mean = 6.68) and EC (mean = 0.21 dsm-1) values across the sites indicated that despite the years of irrigation the areas are not under immediate salinization risk. There was no specific pattern of distribution of basic cations in both the two schemes. There is an observable tendency in the distribution of the forms of P and K evaluated of their being at higher concentrations in longer-periods irrigated lands in both the scheme. The nugget to sill ratio revealed a strong spatial dependence (&lt; 25 %) for WSK. Moderately spatial dependence (25 to 75 %) was observed for available P, total P, noN-exchangeable K and exchangeable potassium. It was concluded that there may be a stronger influence of the irrigation method on the spatial distribution of the forms of the nutrients over other factors such as parent material and weathering.

The geographic variation and spatiotemporal distribution of hepatitis C virus infection in Libya: 2007\u20132016

BackgroundHepatitis C Virus infection has been considered an important hidden pandemic in developing countries, particularly in Africa. It varies greatly from one region to another and even within districts of the same region. Macroscopic geospatial analysis has become an important scientific tool for identifying the density and clustering of HCV infection and provides epidemiological information for planning interventions and control strategies. The application of these parameters provides a better knowledge of the hepatitis C virus infection prevalence at the national level and can help to implement pertinent strategies to address the HCV-related burdens. This study aims to determine the geographical variability of HCV infection in Libya and to identify the hot spots within regions and districts of the country, and to analyze the population-based demographic determinants involved and outline the intervention programs needed.MethodsDisease mapping and spatial analysis were conducted using geographic information data available on all documented cases of HCV infections in Libya between 2007 and 2016. Spatial autocorrelation was tested using Moran’s Index, which determines and measures the degree of clustering and dispersion of HCV infection in a country.ResultsA total 114,928 HCV infection cases during a ten-year period with accurate geographic information were studied. Ages ranged between 16 and 50 years and the male to female ratio was 2:1. HCV infection was unevenly distributed in Libya, and its incidence increased steadily over the study period. Several hot spots and cold spots were found mainly in the southern and eastern regions of the country.ConclusionHCV infection in Libya was geographically variable, with several hot spots particularly in eastern and southern Libya associated with different demographic determinants. Future intervention planning should consider the geospatial variability and risk factors involved.

Geospatial Variability and Ecological Amplitudes of Plants along Nutrient Gradients in Imo River Wetland

Geospatial Variability and Ecological Amplitudes of Plants along Nutrient Gradients in Imo River Wetland

Geo-spatial variability in soil health of Biwan watershed located at Mewat district of Haryana, India

A study was carried out to evaluate the geo-spatial variability of soil health parameters in Biwan watershed located in the Mewat district of Haryana in 2012-13. The main objective of this study was to determine spatial variability of selected soil health parameters that influence crop growth and yield. Soil samples (100) with GPS co-ordinates were collected on random basis from Tapkan, Biwan, Shonkh, Palla and Palladi villages of Biwan watershed during pre-monsoon period (May 2012). Soil health parameters such as pH2, electrical conductivity (EC2), organic carbon, available NPK and micronutrient (Zn, Fe, Cu and Mn) were analyzed from each sample by the standard methods. The spatial variability maps for different soil health parameters were prepared through GIS software (ArcGIS 9.0). Results indicated that the pH2 (6.0-8.59) and EC2 (&lt;1.0 dS/m) were normal in about 80% of soil samples in watershed area. Comparatively, higher soil salinity was observed in Palladi village. Organic carbon and available nitrogen were low in the soils of whole watershed. The available phosphorous was low in 57% soil samples and rest was in medium. The lower concentration of available phosphorous was in most of the part of watershed, whereas medium concentration was in some part of Biwan and Palladi villages. The available potassium was low in 23%, medium in 67% and high in 10% soil samples. The higher concentration of available potassium was in some parts of Biwan, Shonkh and Palla villages. The Zn concentration was deficient (&lt;0.6 mg/kg) in 70% of soil samples and 30% samples were in sufficient. The higher concentration of Zn was in Tapkan and Palladi villages. 84% soil samples showed the iron (Fe) deficiency. The sufficient Fe concentration was in the scattered patches of the watershed. The Cu and Mn concentrations in most of the soils of Biwan watershed were sufficient. It was concluded from the study that the soil health of Biwan watershed was poor.

Estimating the uncertainty from sampling in pollution crime investigation: The importance of metrology in the forensic interpretation of environmental data

The forensic interpretation of environmental analytical data is usually challenging due to the high geospatial variability of these data. The measurements’ uncertainty includes contributions from the sampling and from the sample handling and preparation processes. These contributions are often disregarded in analytical techniques results’ quality assurance. A pollution crime investigation case was used to carry out a methodology able to address these uncertainties in two different environmental compartments, freshwater sediments and landfill leachate. The methodology used to estimate the uncertainty was the duplicate method (that replicates predefined steps of the measurement procedure in order to assess its precision) and the parameters used to investigate the pollution were metals (Cr, Cu, Ni, and Zn) in the leachate, the suspect source, and in the sediment, the possible sink. The metal analysis results were compared to statutory limits and it was demonstrated that Cr and Ni concentrations in sediment samples exceeded the threshold levels at all sites downstream the pollution sources, considering the expanded uncertainty U of the measurements and a probability of contamination >0.975, at most sites. Cu and Zn concentrations were above the statutory limits at two sites, but the classification was inconclusive considering the uncertainties of the measurements. Metal analyses in leachate revealed that Cr concentrations were above the statutory limits with a probability of contamination >0.975 in all leachate ponds while the Cu, Ni and Zn probability of contamination was below 0.025. The results demonstrated that the estimation of the sampling uncertainty, which was the dominant component of the combined uncertainty, is required for a comprehensive interpretation of the environmental analyses results, particularly in forensic cases.

Rationale and mechanics for peak natural catastrophe variance swaps in insurance

The geospatial variability, clustering and dependence of natural catastrophe loss for (re)insured risks are well-known physical realities for insurance industry practitioners and academics. These realities create complex underlying risks for (re)insurance policy underwriting, capital reserving and portfolio management, all of which are reasonably hard to measure and difficult to quantify. The quantitative measurements of such underlying risk factors are also known as second order risks. They are traditionally evaluated and hedged using statistical models for variance and volatility and involve specific complexities in modelling and managing both, volatility and correlation. This technical study explores the motivation, structuring and detailed mechanics for using what we call a 'peak natural catastrophe risk variance swap contract' adapted to provide reinsurance cover for a property and business interruption insurance portfolio. We use known natural catastrophe event historical and modelled loss data to structure, price and test the sensitivities of the swap contract.

A procedure for modeling the deposits of kaolin raw materials based on the comprehensive analysis of quality indicators

determining of whiteness based on using a flatbed scanner with subsequent processing of color pixel coordinates, which combined high productivity, affordable price and acceptable accuracy, which, for the case of applying the flatbed scanner Epson Perfection V200 Photo (Japan), matches the accuracy of basic techniques. To enhance effectiveness of the implementation of the developed procedure, we created an algorithm and realized it in the software Whiteness for determining the whiteness of primary kaolins using a scanned image of the sample. We established main types of correlation relationship between quality indicators of kaolins for Zhezhelivsky and Velyko-Gadominetsky deposit. The constructed models of correlation pairs provide a possibility to develop integrated indicators of deposit quality that will make it possible to simplify the process of building a model of geospatial variability of quality indicators and improve effectiveness of quality control at separate technological areas of a deposit. We improved efficiency of mathematical modeling of geospatial variability of quality indicators to control technological processes of extraction and processing of primary kaolins, based on determining the optimal models of variograms for various areas of research using a devised plane criterion. We established directions that are characterized by maximal values of correlation degree and anisotropy indicators, and found the ranges of autocorrelation of data for selected quality indicators. We developed a procedure for a geostatistical calculation of reserves at Velyko-Gadominetsky deposit of primary kaolins taking into account the grade differentiation to improve effectiveness of quality control over raw materials. The main types of interrelations between quality indicators of kaolins are established. We determined the volume of kaolin field at Velyko-Gadominetsky deposit by industries and grades. A procedure is proposed to estimate an error in determining the volume of operations performed at a deposit to enhance efficiency of control processes in the exploration of deposits. The implementation of the developed procedures to determine the volume of Velyko Gadominetsky deposit of primary kaolins with respect to the grade differentiation using the proposed methodology is characterized by minimal values of relative mean-weighted error in determining the total amount of grade, which ranges from 0.001 % to 1.067 %.

Land Use Change Trajectories for Wetland Management (Mogi-Gua&amp;#231;u Floodplan River, Southern Brazil)

Natural and anthropogenic factors are responsible for changes in wetland function and structure. This research deals with the complexity of interactions among flood attributes, climatic data and land use trajectories to track the impact of land use changes for wetland management, over 30 years (1984- 2014). This paper presents a multi-temporal analysis of a floodplain to know the inter-annual ecohydrological variability, including extraordinary events of floods and droughts, using indicators of hydrological regime. It also presents a quantitative description of the geospatial variability in the Mogi Gua&#231u wetland components to assess the changes in the conversion, replacement, of wetland landscapes by anthropic growth activities. Flood attributes and anthropogenic pressures have altered temporal habitat variability in changes on the river course, in sandbars extent, and oxbow lake genesis and extinction, with a decline in the biota dependent on these habitats. These results have significant implications of the quick expansion of anthropogenic activities and provide key information about the impact of land use changes on the wetland function and structure. It is an objective tool to help the environmental management of wetland areas.

Geo-spatial Variability Assessment of Water Pollutants Concentration in Mariut Lake, Egypt

Geo-spatial Variability Assessment of Water Pollutants Concentration in Mariut Lake, Egypt