Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets     

Sudhir Kumar Singh  Szilárd Szabó  George P. Petropoulos  Manika Gupta  Tanvir Islam 《国际地球制图》2017,32(2):113-127

Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem.  相似文献   

<Emphasis Type="Italic">Clostridium difficile</Emphasis> infection incidence prediction in hospitals (CDIIPH): a predictive model based on decision tree and fuzzy techniques     

Gyan?Chhipi-ShresthaEmail author  Julie?Mori  Kasun?Hewage  Rehan?Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(2):417-430

Several risk factors associated with the increased likelihood of healthcare-associated Clostridium difficile infection (CDI) have been identified in the literature. These risk factors are mainly related to age, previous CDI, antimicrobial exposure, and prior hospitalization. No model is available in the published literature that can be used to predict the CDI incidence using healthcare administration data. However, the administrative data can be imprecise and may challenge the building of classical statistical models. Fuzzy set theory can deal with the imprecision inherent in such data. This research aimed to develop a model based on deterministic and fuzzy mathematical techniques for the prediction of hospital-associated CDI by using the explanatory variables controllable by hospitals and health authority administration. Retrospective data on CDI incidence and other administrative data obtained from 22 hospitals within a regional health authority in British Columbia were used to develop a decision tree (deterministic technique based) and a fuzzy synthetic evaluation model (fuzzy technique based). The decision tree model had a higher prediction accuracy than that of the fuzzy based model. However, among the common results predicted by two models, 72 % were correct. Therefore, this relationship was used to combine their results to increase the precision and the strength of evidence of the prediction. These models were further used to develop an Excel-based tool called C. difficile Infection Incidence Prediction in Hospitals (CDIIPH). The tool can be utilized by health authorities and hospitals to predict the magnitude of CDI incidence in the following quarter.  相似文献   

Intentional contamination of water distribution networks: developing indicators for sensitivity and vulnerability assessments     

Amir?NafiEmail author  Eric?Crastes  Rehan?Sadiq  Denis?Gilbert  Olivier?Piller 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):527-544

Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors.  相似文献   

Development of a predictive model for <Emphasis Type="Italic">Clostridium difficile</Emphasis> infection incidence in hospitals using Gaussian mixture model and Dempster–Shafer theory     

Bingyi Kang  Gyan Chhipi-Shrestha  Yong Deng  Kasun Hewage  Rehan Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1743-1758

Clostridium difficile infection is one of the major patient safety concerns in hospitals worldwide. Clostridium difficile infection can have high economic burden to patients, hospitals, and government. Limited work has been done in the area of predictive modeling. In this article, A new predictive model based on Gaussian mixture model and Dempster–Shafter theory is proposed to predict Clostridium difficile infection incidence in hospitals. First, the Gaussian mixture model and expectation–maximization algorithms are used to generate explicit probability criteria of risk factors based on the given data. Second, Dempster–Shafter theory is used to predict the Clostridium difficile infection incidence based on the generated probability criteria that have different beliefs attributing to their different credits. The main procedure includes (1) generate the probability criteria model using Gaussian mixture model and expectation–maximization algorithm; (2) determine the credit of the probability criteria; (3) generate the basic probability assignment; (4) discount the evidences; (5) aggregate the evidences using Dempster combining rule; (6) predict Clostridium difficile infection incidence using pignistic probability transformation. Results show that the model has a higher accuracy than an existing model. The proposed model can generate the criteria ratings of risk factors automatically, which would potentially prevent the imprecision caused by the subjective judgement of experts. The proposed model can assist risk managers and hospital administrators in the prediction and control of Clostridium difficile infection incidence with optimizing their resources.  相似文献   

Comparative study of fuzzy evidential reasoning and fuzzy rule-based approaches: an illustration for water quality assessment in distribution networks     

E. Aghaarabi  F. Aminravan  R. Sadiq  M. Hoorfar  M. J. Rodriguez  H. Najjaran 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(3):655-679

This paper presents the use of two multi-criteria decision-making (MCDM) frameworks based on hierarchical fuzzy inference engines for the purpose of assessing drinking water quality in distribution networks. Incommensurable and uncertain water quality parameters (WQPs) at various sampling locations of the water distribution network (WDN) are monitored. Two classes of WQPs including microbial and physicochemical parameters are considered. Partial, incomplete and subjective information on WQPs introduce uncertainty to the water quality assessment process. Likewise, conflicting WQPs result in a partially reliable assessment of the quality associated with drinking water. The proposed methodology is based on two hierarchical inference engines tuned using historical data on WQPs in the WDN and expert knowledge. Each inference engine acts as a decision-making agent specialized in assessing one aspect of quality associated with drinking water. The MCDM frameworks were developed to assess the microbial and physicochemical aspects of water quality assessment. The MCDM frameworks are based on either fuzzy evidential or fuzzy rule-based inference. Both frameworks can interpret and communicate the relative quality associated with drinking water, while the second is superior in capturing the nonlinear relationships between the WQPs and estimated water quality. More comprehensive rules will have to be generated prior to reliable water quality assessment in real-case situations. The examples presented here serve to demonstrate the proposed frameworks. Both frameworks were tested through historical data available for a WDN, and a comparison was made based on their performance in assessing levels of water quality at various sampling locations of the network.  相似文献   

Quantifying influence of weather indices on PM_{2.5} based on relation map     

Jie Liu  Yunpeng Li  Rehan Sadiq  Yong Deng 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(6):1323-1331

Many researches have been conducted on the health influence of Particle Matter with diameters less than 2.5 microns (PM \(_{2.5}\) ). There are also some researches on the cause of PM \(_{2.5}\) . However, such research generally focuses on the economic and political aspect of the environment issue. In this paper, a data-analysis approach of the PM \(_{2.5}\) issue is raised to offer a new viewpoint of this problem. The applied method extracts the relations of air quality system record as a relation map, which illustrates the influence among the parameters in a graph. The method successfully fitted the weather record, and derived from it the influencers of PM \(_{2.5}\) . The result shows that the average temperature, average barometric pressure and concentration of Ozone are all factors that have an influence on the concentration of PM \(_{2.5}.\) A short justification of it is also provided.  相似文献   

Statistical landslide susceptibility assessment of the Mansehra and Torghar districts,Khyber Pakhtunkhwa Province,Pakistan     

Jewgenij Torizin  Michael Fuchs  Adnan Alam Awan  Ijaz Ahmad  Sardar Saeed Akhtar  Simon Sadiq  Asif Razzak  Daniel Weggenmann  Faseeh Fawad  Nimra Khalid  Faisan Sabir  Ahsan Jamal Khan 《Natural Hazards》2017,87(2):757-771

This paper presents laboratory experiments and numerical simulations of effects of submerged obstacles on tsunami-like solitary wave and its run-up. This study was carried out for the breaking and non-breaking solitary waves on 1:19.85 uniform slope which contains a submerged obstacle. New laboratory experiments are performed to describe the mitigation of tsunami amplitude and run-up under the effect of submerged obstacles. We are based on experimental results obtained to validate the numerical model. The numerical modeling using COULWAVE aims essentially to show the effect of the obstacle on the shape of solitary wave and the limit of this effect. Using a multiple nonlinear regression, we have determined a model to estimate height of run-up according to the amplitude of the wave and the obstacle peak depth.  相似文献   

BIBLIOGRAPHY—BIBLIOGRAPHIE     

Jiahu Wang  Li Li  Jonathan J. Gourley  Sadiq I. Khan  Koray K. Yilmaz 《水文科学杂志》2013,58(1):84-98

Abstract

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST's distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing via three feedback mechanisms; and (3) representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs). The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture. Furthermore, the representation of soil moisture variability and routing processes at the sub-grid scale enables the CREST model to be readily scalable to multi-scale modelling research. This paper presents the model development and demonstrates its applicability for a case study in the Nzoia basin located in Lake Victoria, Africa.

Citation Wang, J., Yang, H., Li, L., Gourley, J. J., Sadiq, I. K., Yilmaz, K. K., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., Limaye, A. S., Korme, T. &; Okello, L. (2011) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol. Sci. J. 56(1), 84–98.  相似文献   

An introspective glance into damage assessment: challenges and lessons learned from the Paso Robles (San Simeon) earthquake     

David McEntire  Jill Souza  Matthew Lloyd Collins  Ekong J. Peters  Abdul-Akeem Sadiq 《Natural Hazards》2012,61(3):1389-1409

This paper underscores the importance of damage assessment and recognizes the direct effect it has on post-disaster response and recovery operations. The paper first explores the literature on this subject, including the history, types, methods, and problems relating to damage assessment. After discussing the employed research methodology, the paper uses the Paso Robles (San Simeon, California) earthquake as a case study to illustrate the challenges and successes with regard to damage assessment. Logistics, politics, information management, coordination, preparedness, and other topics are discussed in this section. The paper concludes with lessons and opportunities for research and its application.  相似文献   

Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators     

Rehan Sadiq  Solomon Tesfamariam 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(4):495-505

Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (ASCE J Environ Eng 126(5):451–455, 2000) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and sensitivity of the proposed approach.  相似文献