scholarly journals Geo Spatial Analysis for Tsunami Risk Mapping

2019 ◽  
Author(s):  
Abu Bakar Sambah ◽  
Fusanori Miura
Keyword(s):  
Spatial Analysis ◽  
Risk Mapping ◽  
Tsunami Risk

scholarly journals Heat risk mapping through spatial analysis of remotely-sensed data and socioeconomic vulnerability in Hermosillo, México

Urban Climate ◽  
2020 ◽  
Vol 31 ◽  
pp. 100576
Author(s):  
Javier Navarro-Estupiñan ◽  
Agustín Robles-Morua ◽  
Rolando Díaz-Caravantes ◽  
Enrique R. Vivoni
Keyword(s):  
Spatial Analysis ◽  
Remotely Sensed ◽  
Risk Mapping ◽  
Remotely Sensed Data ◽  
Socioeconomic Vulnerability ◽  
Heat Risk

scholarly journals Tsunami risk mapping simulation for Malaysia

2011 ◽  
Author(s):  
S. Y. Teh ◽  
H. L. Koh ◽  
Y. T. Moh ◽  
D. L. DeAngelis ◽  
J. Jiang
Keyword(s):  
Risk Mapping ◽  
Tsunami Risk

scholarly journals Tsunami Risk Mapping of Lumajang District Using Geographic Information System (GIS)

2017 ◽  
Vol 3 (6) ◽  
Author(s):  
Amien Widodo ◽  
Dwa Desa Warnana ◽  
Juan Pandu Gya Nur Rochman ◽  
Firman Syaifuddin ◽  
Erik Sapta Perbawa ◽  
...  
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
Risk Mapping ◽  
Tsunami Risk

scholarly journals Groundwater Vulnerability and Risk Mapping Based on Residence Time Distributions: Spatial Analysis for the Estimation of Lumped Parameters

2015 ◽  
Vol 29 (15) ◽  
pp. 5489-5504 ◽  
Author(s):  
M. Dedewanou ◽  
S. Binet ◽  
J. L. Rouet ◽  
Y. Coquet ◽  
A. Bruand ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Residence Time ◽  
Groundwater Vulnerability ◽  
Risk Mapping ◽  
Residence Time Distributions ◽  
Lumped Parameters

scholarly journals TSUNAMI MODELLING AND RISK MAPPING FOR EAST COAST OF SABAH, MALAYSIA

2011 ◽  
Vol 1 (32) ◽  
pp. 55 ◽  
Author(s):  
Claus Pedersen ◽  
Ziauddin Abdul Latif ◽  
Caroline Lai
Keyword(s):  
Overland Flow ◽  
East Coast ◽  
Regional Scale ◽  
Risk Mapping ◽  
Hazard Mapping ◽  
Flow Modelling ◽  
Topographic Data ◽  
Data Limitations ◽  
Tsunami Risk ◽  
Main Population

A tsunami risk mapping study for the east coast of the state of Sabah, Malaysia, has been initiated by the Government of Malaysia. The main objective is to produce tsunami risk maps that can be taken into account in local planning for the coastal zone. The study covers a coastline of more than a thousand kilometers which generally is sparsely populated outside the main population centers. The study is regional in character, but with additional focus on the main population centers. The paper outlines the overall steps of hazard mapping through source identification and modelling followed by tsunami wave propagation and potential modelling of overland flow. Modelling challenges related to sparse bathymetry data, limitations to resolution due to the large coverage required combined with a complex bathymetry with coral reefs, islands and outcrops is discussed. Data and model resolution for overland flow modelling is discussed. For the present study, it was found that the inaccuracies in the topographic data is of similar magnitude to the expected inundation levels, and caution has to be exercised in deriving hazard levels from the overland flow modelling. For a regional scale risk mapping exercise, and in the absence of very detailed topographic data, it may be preferable to use the wave height along the coastline as a hazard indicator rather than potentially inaccurate inundation levels and overland flow velocities.

scholarly journals Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models

2013 ◽  
Vol 8 (1) ◽  
pp. 97 ◽  
Author(s):  
Ronaldo G. C. Scholte ◽  
Nadine Schur ◽  
Maria E. Bavia ◽  
Edgar M. Carvalho ◽  
Frédérique Chammartin ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Risk Mapping ◽  
Helminth Infections ◽  
Geostatistical Models

scholarly journals Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa

Parasitology ◽  
2009 ◽  
Vol 136 (13) ◽  
pp. 1683-1693 ◽  
Author(s):  
C. Simoonga ◽  
J. Utzinger ◽  
S. Brooker ◽  
P. Vounatsou ◽  
C. C. Appleton ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Intermediate Host ◽  
Disease Risk ◽  
Risk Mapping ◽  
Transmission Dynamics ◽  
Geographical Information ◽  
Quality Data ◽  
Parasitic Infections ◽  
Host Snail

SUMMARYBeginning in 1970, the potential of remote sensing (RS) techniques, coupled with geographical information systems (GIS), to improve our understanding of the epidemiology and control of schistosomiasis in Africa, has steadily grown. In our current review, working definitions of RS, GIS and spatial analysis are given, and applications made to date with RS and GIS for the epidemiology and ecology of schistosomiasis in Africa are summarised. Progress has been made in mapping the prevalence of infection in humans and the distribution of intermediate host snails. More recently, Bayesian geostatistical modelling approaches have been utilized for predicting the prevalence and intensity of infection at different scales. However, a number of challenges remain; hence new research is needed to overcome these limitations. First, greater spatial and temporal resolution seems important to improve risk mapping and understanding of transmission dynamics at the local scale. Second, more realistic risk profiling can be achieved by taking into account information on people's socio-economic status; furthermore, future efforts should incorporate data on domestic access to clean water and adequate sanitation, as well as behavioural and educational issues. Third, high-quality data on intermediate host snail distribution should facilitate validation of infection risk maps and modelling transmission dynamics. Finally, more emphasis should be placed on risk mapping and prediction of multiple species parasitic infections in an effort to integrate disease risk mapping and to enhance the cost-effectiveness of their control.

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds

2018 ◽  
Vol 117 (5) ◽  
pp. 1613-1620 ◽  
Author(s):  
Abel Villa-Mancera ◽  
César Pastelín-Rojas ◽  
Jaime Olivares-Pérez ◽  
Alejandro Córdova-Izquierdo ◽  
Alejandro Reynoso-Palomar
Keyword(s):  
Spatial Analysis ◽  
Risk Mapping ◽  
Bulk Tank Milk ◽  
Ostertagia Ostertagi ◽  
Bulk Tank ◽  
Cattle Herds ◽  
Predictive Risk ◽  
Predictive Risk Mapping ◽  
Production Losses
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