Ruth Kerry - Academia.edu (original) (raw)
Papers by Ruth Kerry
Arabian Journal of Geosciences
Estimating sediment load of rivers is one of the major problems in river engineering that has bee... more Estimating sediment load of rivers is one of the major problems in river engineering that has been using various data mining algorithms and variables. It is desirable to obtain accurate estimates of sediment load while using techniques that limit computational intensity when datasets are large. This study investigates the usefulness of geo-morphometric factors and machine learning (ML) models for predicting suspended sediment load (SSL) in several river basins in Lorestan and Gilan, Iran. Six ML models, namely, multiple linear regression (MLR), artificial neural networks (ANN), K-nearest neighbor (KNN), Gaussian processes (GP), support vector machines (SVM), and evolutionary support vector machines (ESVM), were evaluated for estimating minimum and average SSL for the study regions. Geo-morphometric parameters and river discharge data were utilized as the main predictors in modeling process. In addition, an attribute reduction technique was applied to decrease the algorithm complexit...
Paddy and Water Environment
Land Degradation & Development
Agronomy
Land use change and soil organic carbon stock (SOCS) depletion over time is one of the predominan... more Land use change and soil organic carbon stock (SOCS) depletion over time is one of the predominant worldwide environmental problems related to global warming and the need to secure food production for an increasing world population. In our research, satellite images from 1988 and 2018 were analyzed for a 177.48 km2 region in Kurdistan Province, Iran. Across the study area. 186 disturbed and undisturbed soil samples were collected at two depths (0–20 cm and 20–50 cm). Bulk density (BD), soil organic carbon (SOC), rock fragments (RockF) and SOCS were measured. Random forest was used to model the spatial variability of SOCS. Land use was mapped with supervised classification and maximum likelihood approaches. The Kappa index and overall accuracy of the supervised classification and maximum likelihood land use maps varied between 83% and 88% and 78% and 85%, respectively. The area of forest and high-quality rangeland covered 5286 ha in 1988 and decreased by almost 30% by 2018. Most of t...
Soil quality assessment based on crop yields and identification of key indicators of it can be us... more Soil quality assessment based on crop yields and identification of key indicators of it can be used for better management of agricultural production. In the current research, the weighted additive soil quality index (SQIw), factor analysis (FA) and multiple linear regression (MLR) method are used to assess the soil quality of rainfed winter wheat fields with two soil orders on 53.20 km2 of agricultural land in western Iran. A total of 18 soil quality indicators were determined for 100 soil samples (0-20 cm depth) from two soil orders (Inceptisols and Entisols). The soil properties measured were: pH, soil texture, organic carbon (OC), cation exchange capacity (CEC), electrical conductivity (EC), soil microbial respiration (SMR), carbonate calcium equivalent (CCE), soil porosity (SP), bulk density (BD), exchangeable sodium percentage (ESP), mean weight diameter (MWD), available potassium (AK), total nitrogen (TN), available phosphorus (AP), available Fe (AFe), available Zn (AZn), avai...
Arabian Journal of Geosciences
International Journal of Environmental Research and Public Health
Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a la... more Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a large burden on public health in Utah (UT), a high-altitude state in the Great Basin Desert, USA. This warrants an investigation of the characteristics of the counties with the highest asthma burden within UT to improve allocation of health resources and for planning. The relations between several predictor environmental, health behavior and socio-economic variables and two health outcome variables, AAP and AER visits, were investigated for UT’s 29 counties. Non-parametric statistical comparison tests, correlation and linear regression analysis were used to determine the factors significantly associated with AER visits and AAP. Regression kriging with Utah small area data (USAD) as well as socio-economic and pollution data enabled local Moran’s I cluster analysis and the investigation of moving correlations between health outcomes and risk factors. Results showed the importance of desert/m...
Agronomy
Land suitability assessment is essential for increasing production and planning a sustainable agr... more Land suitability assessment is essential for increasing production and planning a sustainable agricultural system, but such information is commonly scarce in the semi-arid regions of Iran. Therefore, our aim is to assess land suitability for two main crops (i.e., rain-fed wheat and barley) based on the Food and Agriculture Organization (FAO) “land suitability assessment framework” for 65 km2 of agricultural land in Kurdistan province, Iran. Soil samples were collected from genetic layers of 100 soil profiles and the physical-chemical properties of the soil samples were analyzed. Topography and climate data were also recorded. After calculating the land suitability classes for the two crops, they were mapped using machine learning (ML) and traditional approaches. The maps predicted by the two approaches revealed notable differences. For example, in the case of rain-fed wheat, results showed the higher accuracy of ML-based land suitability maps compared to the maps obtained by traditi...
Applied Spatial Analysis and Policy
Scientific Reports
Spatial autocorrelation in the residuals of spatial environmental models can be due to missing co... more Spatial autocorrelation in the residuals of spatial environmental models can be due to missing covariate information. In many cases, this spatial autocorrelation can be accounted for by using covariates from multiple scales. Here, we propose a data-driven, objective and systematic method for deriving the relevant range of scales, with distinct upper and lower scale limits, for spatial modelling with machine learning and evaluated its effect on modelling accuracy. We also tested an approach that uses the variogram to see whether such an effective scale space can be approximated a priori and at smaller computational cost. Results showed that modelling with an effective scale space can improve spatial modelling with machine learning and that there is a strong correlation between properties of the variogram and the relevant range of scales. Hence, the variogram of a soil property can be used for a priori approximations of the effective scale space for contextual spatial modelling and is therefore an important analytical tool not only in geostatistics, but also for analyzing structural dependencies in contextual spatial modelling.
Drug and Alcohol Dependence
Bulletin of environmental contamination and toxicology, Jan 16, 2018
The Kushk Pb-Zn mine is located in Central Iran and it has been in operation for the last 75 year... more The Kushk Pb-Zn mine is located in Central Iran and it has been in operation for the last 75 years. To investigate the role of wind dispersion of heavy metal pollutants from the mine area, dust samples were collected during 1 year and topsoil samples were collected around the mine. Results showed that the topsoil is polluted with Pb and Zn to about 1500 m away from the mine. It was also found that there was not a significant difference between the metal concentrations in topsoil and dust samples. The Pb and Zn concentrations in the dust samples exceeded 200 mg kg and their lateral dispersion via wind was estimated to be about 4 km away from the mine. It has been shown that a combination of mining activities and mechanical dispersion via water and wind have caused lateral movement of heavy metals in this area.
Crop Protection
Aflatoxin is a mycotoxin produced by the Aspergillus flavus fungi that can severely contaminate c... more Aflatoxin is a mycotoxin produced by the Aspergillus flavus fungi that can severely contaminate corn grain. The U.S. Food and Drug Administration (FDA) have set a limit of 20 ppb, total aflatoxin, for interstate commerce of food and feed as it can induce liver cancer in humans and animals. Contamination is exacerbated by high temperatures, drought conditions and lighttextured soil which are all common in Georgia (GA). Lack of irrigation infrastructure can further amplify drought stress and aflatoxin contamination. Accurate aflatoxin assessment requires the collection of multiple corn samples, is expensive and conducted at harvest which does not allow for the use of in-season mitigation strategies to reduce the risk. Given the expense of measurement and the consequences of crop loss, an important goal for agricultural extension services is the prediction and identification of years and counties at higher risk of aflatoxin contamination. This would allow growers to deploy management tactics to reduce risk and to reduce unnecessary expense on aflatoxin testing. In this research, aflatoxin levels were analysed
PLOS ONE
The population density of wildlife reservoirs contributes to disease transmission risk for domest... more The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission.
Arabian Journal of Geosciences
Estimating sediment load of rivers is one of the major problems in river engineering that has bee... more Estimating sediment load of rivers is one of the major problems in river engineering that has been using various data mining algorithms and variables. It is desirable to obtain accurate estimates of sediment load while using techniques that limit computational intensity when datasets are large. This study investigates the usefulness of geo-morphometric factors and machine learning (ML) models for predicting suspended sediment load (SSL) in several river basins in Lorestan and Gilan, Iran. Six ML models, namely, multiple linear regression (MLR), artificial neural networks (ANN), K-nearest neighbor (KNN), Gaussian processes (GP), support vector machines (SVM), and evolutionary support vector machines (ESVM), were evaluated for estimating minimum and average SSL for the study regions. Geo-morphometric parameters and river discharge data were utilized as the main predictors in modeling process. In addition, an attribute reduction technique was applied to decrease the algorithm complexit...
Paddy and Water Environment
Land Degradation & Development
Agronomy
Land use change and soil organic carbon stock (SOCS) depletion over time is one of the predominan... more Land use change and soil organic carbon stock (SOCS) depletion over time is one of the predominant worldwide environmental problems related to global warming and the need to secure food production for an increasing world population. In our research, satellite images from 1988 and 2018 were analyzed for a 177.48 km2 region in Kurdistan Province, Iran. Across the study area. 186 disturbed and undisturbed soil samples were collected at two depths (0–20 cm and 20–50 cm). Bulk density (BD), soil organic carbon (SOC), rock fragments (RockF) and SOCS were measured. Random forest was used to model the spatial variability of SOCS. Land use was mapped with supervised classification and maximum likelihood approaches. The Kappa index and overall accuracy of the supervised classification and maximum likelihood land use maps varied between 83% and 88% and 78% and 85%, respectively. The area of forest and high-quality rangeland covered 5286 ha in 1988 and decreased by almost 30% by 2018. Most of t...
Soil quality assessment based on crop yields and identification of key indicators of it can be us... more Soil quality assessment based on crop yields and identification of key indicators of it can be used for better management of agricultural production. In the current research, the weighted additive soil quality index (SQIw), factor analysis (FA) and multiple linear regression (MLR) method are used to assess the soil quality of rainfed winter wheat fields with two soil orders on 53.20 km2 of agricultural land in western Iran. A total of 18 soil quality indicators were determined for 100 soil samples (0-20 cm depth) from two soil orders (Inceptisols and Entisols). The soil properties measured were: pH, soil texture, organic carbon (OC), cation exchange capacity (CEC), electrical conductivity (EC), soil microbial respiration (SMR), carbonate calcium equivalent (CCE), soil porosity (SP), bulk density (BD), exchangeable sodium percentage (ESP), mean weight diameter (MWD), available potassium (AK), total nitrogen (TN), available phosphorus (AP), available Fe (AFe), available Zn (AZn), avai...
Arabian Journal of Geosciences
International Journal of Environmental Research and Public Health
Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a la... more Rising adult asthma prevalence (AAP) rates and asthma emergency room (AER) visits constitute a large burden on public health in Utah (UT), a high-altitude state in the Great Basin Desert, USA. This warrants an investigation of the characteristics of the counties with the highest asthma burden within UT to improve allocation of health resources and for planning. The relations between several predictor environmental, health behavior and socio-economic variables and two health outcome variables, AAP and AER visits, were investigated for UT’s 29 counties. Non-parametric statistical comparison tests, correlation and linear regression analysis were used to determine the factors significantly associated with AER visits and AAP. Regression kriging with Utah small area data (USAD) as well as socio-economic and pollution data enabled local Moran’s I cluster analysis and the investigation of moving correlations between health outcomes and risk factors. Results showed the importance of desert/m...
Agronomy
Land suitability assessment is essential for increasing production and planning a sustainable agr... more Land suitability assessment is essential for increasing production and planning a sustainable agricultural system, but such information is commonly scarce in the semi-arid regions of Iran. Therefore, our aim is to assess land suitability for two main crops (i.e., rain-fed wheat and barley) based on the Food and Agriculture Organization (FAO) “land suitability assessment framework” for 65 km2 of agricultural land in Kurdistan province, Iran. Soil samples were collected from genetic layers of 100 soil profiles and the physical-chemical properties of the soil samples were analyzed. Topography and climate data were also recorded. After calculating the land suitability classes for the two crops, they were mapped using machine learning (ML) and traditional approaches. The maps predicted by the two approaches revealed notable differences. For example, in the case of rain-fed wheat, results showed the higher accuracy of ML-based land suitability maps compared to the maps obtained by traditi...
Applied Spatial Analysis and Policy
Scientific Reports
Spatial autocorrelation in the residuals of spatial environmental models can be due to missing co... more Spatial autocorrelation in the residuals of spatial environmental models can be due to missing covariate information. In many cases, this spatial autocorrelation can be accounted for by using covariates from multiple scales. Here, we propose a data-driven, objective and systematic method for deriving the relevant range of scales, with distinct upper and lower scale limits, for spatial modelling with machine learning and evaluated its effect on modelling accuracy. We also tested an approach that uses the variogram to see whether such an effective scale space can be approximated a priori and at smaller computational cost. Results showed that modelling with an effective scale space can improve spatial modelling with machine learning and that there is a strong correlation between properties of the variogram and the relevant range of scales. Hence, the variogram of a soil property can be used for a priori approximations of the effective scale space for contextual spatial modelling and is therefore an important analytical tool not only in geostatistics, but also for analyzing structural dependencies in contextual spatial modelling.
Drug and Alcohol Dependence
Bulletin of environmental contamination and toxicology, Jan 16, 2018
The Kushk Pb-Zn mine is located in Central Iran and it has been in operation for the last 75 year... more The Kushk Pb-Zn mine is located in Central Iran and it has been in operation for the last 75 years. To investigate the role of wind dispersion of heavy metal pollutants from the mine area, dust samples were collected during 1 year and topsoil samples were collected around the mine. Results showed that the topsoil is polluted with Pb and Zn to about 1500 m away from the mine. It was also found that there was not a significant difference between the metal concentrations in topsoil and dust samples. The Pb and Zn concentrations in the dust samples exceeded 200 mg kg and their lateral dispersion via wind was estimated to be about 4 km away from the mine. It has been shown that a combination of mining activities and mechanical dispersion via water and wind have caused lateral movement of heavy metals in this area.
Crop Protection
Aflatoxin is a mycotoxin produced by the Aspergillus flavus fungi that can severely contaminate c... more Aflatoxin is a mycotoxin produced by the Aspergillus flavus fungi that can severely contaminate corn grain. The U.S. Food and Drug Administration (FDA) have set a limit of 20 ppb, total aflatoxin, for interstate commerce of food and feed as it can induce liver cancer in humans and animals. Contamination is exacerbated by high temperatures, drought conditions and lighttextured soil which are all common in Georgia (GA). Lack of irrigation infrastructure can further amplify drought stress and aflatoxin contamination. Accurate aflatoxin assessment requires the collection of multiple corn samples, is expensive and conducted at harvest which does not allow for the use of in-season mitigation strategies to reduce the risk. Given the expense of measurement and the consequences of crop loss, an important goal for agricultural extension services is the prediction and identification of years and counties at higher risk of aflatoxin contamination. This would allow growers to deploy management tactics to reduce risk and to reduce unnecessary expense on aflatoxin testing. In this research, aflatoxin levels were analysed
PLOS ONE
The population density of wildlife reservoirs contributes to disease transmission risk for domest... more The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission.