An updated methodology for sediment distribution maps using conditional strings in Arc GIS 10.X

2021 ◽  
Vol 14 (20) ◽  
Author(s):  
Rachna Pillai ◽  
Nisha Nayakkam Valappil ◽  
Dinesh Aynipulli Chulli Parambil
Keyword(s):  
Sediment Distribution ◽  
Distribution Maps ◽  
Arc Gis

Groundwater Quality Assessment Using Geospatial Techniques and WQI in North East of Adama Town, Oromia Region, Ethiopia

2020 ◽  
Vol 3 (1) ◽  
pp. 22-36 ◽  
Author(s):  
Shankar Karuppannan ◽  
Nafyad Serre Kawo
Keyword(s):  
Groundwater Quality ◽  
Sustainable Use ◽  
World Health ◽  
Geospatial Techniques ◽  
Distribution Maps ◽  
North East ◽  
Drinking And Irrigation ◽  
Groundwater Samples ◽  
Arc Gis ◽  
Health Organization

Assessment of groundwater quality is vital for the sustainable use of the resources for domestic and agricultural purposes. In this study spatial variation of physicochemical parameters were analyzed for Northeast Adama Town. Water Quality Index (WQI) and irrigation indices were used to determine the suitability of groundwater for drinking and irrigation purposes, respectively. Further, the physical-chemical results were compared with the Ethiopian standards and the World Health Organization (WHO) standards for drinking and public health. Using GIS interpolation methods in Arc GIS 10.3.1, spatial distribution maps of pH, TDS, EC, Cl−, HCO32−, SO42−, Ca2+, Mg2+, Na+ and K+, RSC, SAR, Na% were prepared. Results indicated that except ASTU well 2, all samples are below the desirable limits of WHO. The WQI results indicated that 85% of samples and 15% of samples were in good and poor categories, respectively. Irrigation indices show that the most groundwater samples have excellent water classes, indicating that they are suitable for irrigation purposes.

scholarly journals Seafloor sediment classification of the Sylt Outer Reef, German Bight from 2016 -2018 using ensemble modelling 

2021 ◽  
Author(s):  
Daphnie Galvez ◽  
Svenja Papenmeier ◽  
Alexander Bartholomä ◽  
Karen Helen Wiltshire
Keyword(s):  
German Bight ◽  
Predictive Accuracy ◽  
Small Sample Size ◽  
Probabilistic Approach ◽  
Small Sample ◽  
Outer Reef ◽  
Sediment Distribution ◽  
Ensemble Modelling ◽  
Distribution Maps ◽  
Modelling Techniques

<p>Recent studies on seafloor mapping have presented different modelling methods to map and classify marine sediment distribution. However, are these methods classify different sediment classes the same way? And how do we choose the right model for a certain set of sediment classes? In this study, we aim to address these issues by using ensemble modelling to map the distribution of different sediment class on a dynamic, shallow continental shelf. Our data were derived from side-scan mosaics and multibeam data repeatedly collected from 2016 to 2018 in the Sylt Outer Reef (German Bight). We used a probabilistic approach for each class separately and then compared the predicted probability for each class, to see which class is more likely to be assigned to the location. Each sediment class was predicted using a combination of different classification modelling techniques, and then the result of these models was ensembled to produced one final prediction. This approach avoids selecting one single method, limits model selection bias and can provide information on the trends and variation across models.  Furthermore, we also looked on the temporal changes in sediment distributions by comparing the sediment class predictions from 2016 to 2018.</p><p>Our analysis suggest that combining different modelling techniques  (i.e. random forest, boosting regression trees etc.) provide higher predictive accuracy than using one single modelling method. The resulting sediment distribution maps are more objective and are produced faster than manual delineated maps often considered by stakeholders. We also identify some limitations in having small sample size and we proposed that by combining certain models and choosing the proper amount of pseudo-absence or background data can address this issue.</p>

scholarly journals Urban air quality evaluation over Kut city using field survey and Geomatic techniques

2018 ◽  
Vol 162 ◽  
pp. 05023
Author(s):  
Zainab Mohammed ◽  
Abdulrazzak. Ziboon ◽  
Ali Kamal ◽  
Mahdi Alfaraj
Keyword(s):  
Air Pollution ◽  
Global Positioning System ◽  
Air Pollutants ◽  
Suspended Particle ◽  
Portable Equipment ◽  
Distribution Maps ◽  
Pollutant Concentrations ◽  
Global Positioning ◽  
Arc Gis ◽  
Exhaust Energy

Air pollution is caused by various sources such as cars exhaust, energy sources, petrol stations, industrial activities, and other sources. The aim of this study was to measure some air pollutants gases, representing the results by Arc GIS maps over AL-Kut city and finding the ways for reducing them. Twenty samples have been taken using Global Positioning System (GPS) for measuring the main air pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), total suspended particle (TSP), and particulate matters (PMs). The measurements were carried out by several specialized portable equipment at afive months starting from November 2015 to March 2016. The distribution maps resulted from ArcGIS 10.2, display that the highest concentrations of air pollutants were in the center and north of the study area. The highest concentrations of pollutants were in November and March, whereas lower concentrations observed during January period. The average monthly concentrations of (TSP) measured during the study period was (504.4 μg/m3, 359.5 μg/m3, 32.2 μg/m3, 324.8 μg/m3, and 392.45 μg/m3) from November 2015 to March 2016, these results were significantly higher than the permissible allowable limits of the Iraqi national (350 μg/m3) and international allowable limits (150 μg/m3), except for January is founded (32.2 μg/m3) within the acceptable limits due to heavy rainfall. the averages monthly concentrations of (CO), (6.567, 5.165, 4.08, 5.454 and 7.25 ppm) were lower than standards limits for five months, comparing with the Iraqi National limits (35 ppm) and WHO Limits (9 ppm). Pollutant concentrations such as (O3), were within acceptable limits of Iraqi and WHO limits at all period of study, while other air pollution gasses such as (SO2 and NO2), their concentrations over the study area were within the Iraqi national limits but slightly over the WHO limits.

scholarly journals An evaluation of compiled single-beam bathymetry data as a basis for regional sediment and biotope mapping

2013 ◽  
Vol 71 (4) ◽  
pp. 867-881 ◽  
Author(s):  
Sigrid Elvenes ◽  
Margaret F. J. Dolan ◽  
Pål Buhl-Mortensen ◽  
Valérie K. Bellec
Keyword(s):  
Scientific Information ◽  
Video Data ◽  
Sediment Grain Size ◽  
Sediment Distribution ◽  
Single Beam ◽  
Distribution Maps ◽  
Full Coverage ◽  
Performance Statistics ◽  
And Performance ◽  
Multibeam Data

Abstract Maps of surficial sediment distribution and benthic habitats or biotopes provide invaluable information for ocean management and are at the core of many seabed mapping initiatives, including Norway's national offshore mapping programme MAREANO (www.mareano.no). Access to high-quality multibeam echosounder data (bathymetry and backscatter) has been central to many of MAREANO's mapping activities, but in order to maximize the cost-effectiveness of future mapping and ensure timely delivery of scientific information, seabed mappers worldwide may increasingly need to look to existing bathymetry data as a basis for thematic maps. This study examines the potential of compiled single-beam bathymetry data for sediment and biotope mapping. We simulate a mapping scenario where full coverage multibeam data are not available, but where existing bathymetry datasets are supplemented by limited multibeam data to provide the basis for thematic map interpretation and modelling. Encouraging results of sediment interpretation from the compiled bathymetry dataset suggest that production of sediment grain size distribution maps is feasible at a 1:250 000 scale or coarser, depending on the quality of available data. Biotope modelling made use of full-coverage predictor variables based on (i) multibeam data, and (ii) compiled single-beam data supplemented by limited multibeam data. Using the same response variable (biotope point observations obtained from video data), the performance of the respective models could be assessed. Biotope distribution maps based on the two datasets are visually similar, and performance statistics also indicate there is little difference between the models, providing a comparable level of information for regional management purposes. However, whilst our results suggest that using compiled bathymetry data with limited multibeam is viable as a basis for regional sediment and biotope mapping, it is not a substitute. Backscatter data and the better feature resolution provided by multibeam data remain of great value for these and other purposes.

Butterfly-hostplant fidelity, vagrancy and measuring mobility from distribution maps

Ecography ◽  
2001 ◽  
Vol 24 (5) ◽  
pp. 497-504 ◽  
Author(s):  
Laurence M. Cook ◽  
Roger L. H. Dennis ◽  
Peter B. Hardy
Keyword(s):  
Distribution Maps

Prevalence and geographic distribution of haemophilia in Costa Rica

2010 ◽  
Vol 30 (S 01) ◽  
pp. S28-S31 ◽  
Author(s):  
J. Arroyo ◽  
L. Salazar-Sánchez ◽  
G. Jiménez-Cruz ◽  
P. Chaverri ◽  
E. Arrieta-Bolaños ◽  
...  
Keyword(s):  
Costa Rica ◽  
Survival Rates ◽  
Coagulation Factors ◽  
Developed Countries ◽  
Health Centers ◽  
Distribution Analysis ◽  
Distribution Maps ◽  
Immunodeficiency Virus ◽  
The Many ◽  
Low Prevalence

SummaryHaemophilia is the most frequent hereditary haemorrhagic illness and it is due to the deficiency of coagulation factors VIII (haemophilia A, HA) or IX (haemophilia B, HB).The prevalence of this disease varies according to the country, those having better survival rates having also higher prevalences. Specifically in Costa Rica, there are around 130 HA and 30 HB families. This study reports the prevalence and a spatial distribution analysis of both types of the disease in this country. The prevalence of haemophilia in this country is 7 cases per 100 000 men, for HA it is 6 cases per 100 000 and for HB it is 1 case per 100 000 male inhabitants. The prevalence of this disease is low when compared with other populations. This low prevalence could be due to the many patients that have died because of infection with human immunodeficiency virus during the 1980s. The prevalence of haemophilia in Costa Rica is almost one half of that present in developed countries. Nevertheless, the ratio between HA and HB follows world tendency: 5 : 1. In this study, nationwide geographical distribution maps were drawn in order to visualize the origin of severe cases and how this influences the pattern of distribution for both types of haemophilia. By means of these maps, it was possible to state that there is no association between the sites of maximum prevalence of mutated alleles and ethnicity. With this study, haemophilia prevalence distribution maps can be used to improve efforts for the establishment of hemophilia clinics or specialized health centers in those areas which hold the highest prevalences in this country. Also, this knowledge can be applied to improve treatment skills and offer the possibility of developing focused genetic counseling for these populations.

Evaluation of Capacity of Salandi Reservoir Using Remote Sensing Data Along With Qgis Software

2018 ◽  
Vol 6 (8) ◽  
pp. 339
Author(s):  
Rupali Dhal ◽  
D. P. Satapathy
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Project Work ◽  
Space Technology ◽  
Reservoir Water ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Spread Area ◽  
Water Spread

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.

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