scholarly journals Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Amare Sewnet Minale ◽  
Kalkidan Alemu
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Satellite Image ◽  
Malaria Risk ◽  
Health Facilities ◽  
Geographical Information ◽  
Bahir Dar ◽  
Risk Map ◽  
Very High

The main objective of this study was to develop a malaria risk map for Bahir Dar City, Amhara, which is situated south of Lake Tana on the Ethiopian plateau. Rainfall, temperature, altitude, slope and land use/land cover (LULC), as well as proximity measures to lake, river and health facilities, were investigated using remote sensing and geographical information systems. The LULC variable was derived from a 2012 SPOT satellite image by supervised classification, while 30-m spatial resolution measurements of altitude and slope came from the Shuttle Radar Topography Mission. Metrological data were collected from the National Meteorological Agency, Bahir Dar branch. These separate datasets, represented as layers in the computer, were combined using weighted, multi-criteria evaluations. The outcome shows that rainfall, temperature, slope, elevation, distance from the lake and distance from the river influenced the malaria hazard the study area by 35%, 15%, 10%, 7%, 5% and 3%, respectively, resulting in a map showing five areas with different levels of malaria hazard: very high (11.2%); high (14.5%); moderate (63.3%); low (6%); and none (5%). The malaria risk map, based on this hazard map plus additional information on proximity to health facilities and current LULC conditions, shows that Bahir Dar City has areas with very high (15%); high (65%); moderate (8%); and low (5%) levels of malaria risk, with only 2% of the land completely riskfree. Such risk maps are essential for planning, implementing, monitoring and evaluating disease control as well as for contemplating prevention and elimination of epidemiological hazards from endemic areas.

Modeling air pollution-related hospital admissions employing remote sensing and geographical information systems.

2021 ◽  
pp. 118502
Author(s):  
Tavera Busso Iván ◽  
Rodríguez Núñez Martín ◽  
Amarillo Ana Carolina ◽  
Mettan Fabricio ◽  
Carreras Hebe Alejandra
Keyword(s):  
Remote Sensing ◽  
Air Pollution ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Hospital Admissions ◽  
Geographical Information

scholarly journals Analogue aerial-photopraphs external orientation reconstruction based on geoportal data

2011 ◽  
Vol 30 (3) ◽  
pp. 13-18
Author(s):  
Piotr Dzieszko
Keyword(s):  
Information Systems ◽  
High Resolution ◽  
Data Acquisition ◽  
Geographical Information Systems ◽  
Fast Growth ◽  
Geographical Information ◽  
Source Data ◽  
Effective Choice ◽  
Field Works ◽  
Very High

Analogue aerial-photopraphs external orientation reconstruction based on geoportal data For acquisition of source data for geoinformation analyses is necessary to do some field works. This way of data acquisition is time-consuming. In this case, photogrammetric and remote sensed methods can be more effective choice. Especially orthophotomap extracting is more effective process in creation of geodata. It is good foundation for further analysis and nice extension of existing geographical information systems. Despite fast growth of photogrammetry there are plenty of analogue, archival airphotos which can be used for geoinformation analysis. They are quiet up to date and scanned in very high resolution which means they can be used for really reliable analysis. The problem is very important because many of analogue, archival air photos do not contain photogrammetric warp. The aim of this paper is expression of applicability of geoportal webpage, which is part of INSPIRE directive, that can be used for external orientation reconstruction when there is no other georeference data.

scholarly journals Numerical Modeling for Gully Erosion in the North of Algeria based on Data of Remote Sensing and Geographic Information Systems

2017 ◽  
Vol 25 (1) ◽  
pp. 37-63
Author(s):  
mohammad abbas daoudi mohammad abbas daoudi
Keyword(s):  
Remote Sensing ◽  
Multivariate Analysis ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Univariate Analysis ◽  
Probabilistic Approach ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Erosion Risk ◽  
The North

The problems of soil erosion are largely widespread in the countries of the Mediterranean basin. The process of gullying is a complex phenomenon with disastrous consequences. It particularly affects northern Algeria, decreasing the potentialities of the water tanks, reducing cultivable lands availability and degrading infrastructures. Therefore, this work studies the analysis and the prediction of gullying erosion by using a probabilistic approach based on multisource data. The objective of this search is to answer to the three following questions: i) which factors support the process of gullying ? ii) how does a process of gullying develop? iii) which are the zones favourable to gullying ? Works are undertaken on the catchment area of the Isser River. We focused the applications on the upstream part of the basin. In this research, we study a North-South transect which corresponds to three under-basins slopes. The choice of these tests areas answers to four criteria defined in our method: the representativeness, the homogeneity, the availability of former data and, finally, the accessibility. After the completion of the multisource data, modelling and multivariate analysis for the prediction of gullying. The combination factor-process by the univariate analysis allows on the one hand, to highlight the variables controlling the process of gullying, and on the other hand, to analyse the variables on a hierarchical basis and to know their degree of influence. The multivariate analysis, by the logistic regression model (LRM), enabled us to select the significant variables and to locate the most favourable zones for the process of gullying. The validation of the models is evaluated using the curves of lift spin. The results suggest that the factors highlighted by the model to be most influential on gullying erosion are: the lithology, the slope, the morphopedology, the rainfall erosivity and the land cover. The synthesis of this approach is illustrated in the form of charts of gullying erosion risk maps in four classes of probability. The assessment of the study shows the fundamental interest of this approach using geographical information systems and remote sensing, in particular for the watersheds of the southern Mediterranean, with the possibility of extending this methodology to other regions.

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