Arc Geographic Information System Research Articles

Delineation of Groundwater Potential Zones Using Remote Sensing and Gis Techniques of Phewa Watershed (Nepal)

Groundwater is the primary source of water in the study region, both for domestic and agricultural needs. The main objective of this research is to identify the groundwater potential zones via remote sensing (RS) and Geographic information system (GIS), which is essential in evaluating, preserving, and monitoring various groundwater-related development programs. Man-made pressures include over-exploitation of groundwater and climate changes have led to a strain on groundwater resources. As the use of consumable water increases for human consumption, agriculture, industrial growth, municipal, and pharmaceutical needs to evaluate the groundwater potential and aquifer productivity also increase. Groundwater inspections have been historically done by field survey method, which is inefficient or not practical in terms of time and resources. Arc GIS software is utilized to manipulate datasets. The LULC map of the study area will be developed using Landsat 8 satellite data. A soil map and rainfall map will be created using the data sources from USGS, a Parent soil map will creates using the data from NARC and slope map, lineament density and drainage density from ASTER from earth data. Seven thematic maps will be applied, each with appropriate weight and rank assigned based on its characteristics and connection with groundwater. All the thematic layers combine into a GIS domain, and weight values are put to the attribute table for each polygon. The groundwater potential zone map will be classified into different zones, i.e., very poor, poor, moderate, good, and very good. These results will help hydrogeologists, decision-makers, planners, and local authorities formulate better groundwater resource planning in the Phewa watershed area.

Distribution, Sources, and Health Risk of Polycyclic Aromatic Hydrocarbons in Farmland Soil of Helan, China

With the development of industry and agriculture, polycyclic aromatic hydrocarbons (PAHs) in the agricultural sector have gradually increased to different degrees, leading to an escalation in environmental pollution. In turn, this escalation has presented a significant possibility of endangering agricultural practices on farmland and has had a serious impact on regional sustainable development. Therefore, a total of 117 samples of soil were gathered to research the pollution level, distribution, sources, and health risk of PAHs in Helan farmland soils. A reference was used for the identification and quantification of PAH content using high-performance liquid chromatography (HPLC) with an ultraviolet detector, and their spatial distribution was analyzed utilizing the Arc Geographic Information System (ArcGIS). The source of PAHs was analyzed by absolute principal component scores/multiple linear regression (APCS-MLR). The lifetime cancer risk increment model and Monte Carlo sensitivity analysis were used to assess the potential health hazards to humans associated with PAHs in soil. Within the current study area, PAHs were higher in the northwest. The results showed that the total content of PAHs in Helan farmland soil ranged from 17.82 to 1544.73 ng·g−1 with a mean of 408.18 ng·g−1, which indicated the middle degree of pollution in farmland soil. The verification results of the APCS-MLR model showed that the correlation coefficient between the measured values and the predicted values ranged from 0.661 to 0.984, which suggested that the APCS-MLR model demonstrated favorable suitability for conducting source analysis of PAHs in the soil within the study region. Based on the contribution of PAHs from each source, the main sources of PAHs in Helan farmland soil were the combustion source (biomass, diesel, and natural gas combustion) and the transportation source (gasoline for vehicles and traffic exhaust emissions). The health risks’ estimation showed that PAHs in farmland soil did not have potential health risks for adults but represented a carcinogenic risk for children via the main exposure pathway of ingestion with the mean intake of 1.28 × 10−5. Meanwhile, the carcinogenic risks (CRs) of dermal contact for the mean value of adults (9.32 × 10−7) was found to be higher than that for children (3.18 × 10−8). From the Monte Carlo simulation, the soil particle uptake rate was the most sensitive to the health risks of children and adults with risk probabilities of 26% and 52%, and the risk probabilities from body weight were −11% and −1%, whose negative value indicated that the increase in body weight could reduce the health risks to human. These findings could provide reference for the study of soil organic pollution in Helan farmland soil and contribute significantly to the preservation of the ecological environment, maintaining human health and safety, and promoting the sustainable development of regional farmland.

Exploration of Species Diversity as Ecological Conditions Vary to Determine the Possible Areas for Collecting Tree Seeds in Amhara Region, Ethiopia

The aim of this study was to determine the forest species trees and shrubs that occur in the Amhara region, Ethiopia, for determining the possible areas for collecting seeds and propagations to meet genetic conservation and use programs as well as the recovery of degraded areas. The study was conducted at Fudi Natural Forest in Fagta Lekoma district, Amhara region, northwestern Ethiopia. Using geographic information systems (GISs), the points of presence of species were plotted on the USGS SRTM map (GTOPO30) at 1 : 250,000 scale (USGS, 2018) using Arc GIS 10.1 software (ESRI, 2011). The map has been cropped and presented only for the citizens that contained points of presence of the species. Figures were generated in the JPG format for each species individually, presenting the distribution of each according to the altitude of the region. The maps were elaborated using multiple linear regressions, relating the bioclimatic variables with the numerical models of latitude, longitude, and altitude. Descriptive statistical analysis was initially performed. This was followed by performing a normality test to observe the data distribution. In the region, 1250 individuals of 32 families and 46 species were surveyed. The families most found in the northeast, north, northwest, southwest, southeast, and west regions were Mimosoideae, Euphorbiaceae, Celastraceae, and Rubiaceae.

Analytical Review of the Software for Creating a City Information Model

Introduction. The article describes a forward-looking technology in the field of construction industry and urban management – CIM (City Information Modeling) – an information model of a city. Emergence of the information modelling have led to the possibility to create the 3D models not only of individual objects, but also of a city as a whole with its buildings, infrastructure, geological and environmental factors. But creation and maintenance of the city models require the software tools. The aim of the present research is to make a review of the available software, describe its properties and field of application. CIM application capacities are also defined. The tasks, which can be solved by means of such a model, are described. The result of using GIS technologies in creating a city information model with respect to the data on housing stock energy efficiency level is shown.Materials and Methods. Within the research, an analytical review of the existing software for creating an information model of a city was carried out, the works of the scientists, who contributed to the issue of urban modeling, were studied. The information sources useful for further research were identified. Geo-information systems ARC GIS 10.1 ESRI were used to create a city information model.Results. A city information model can be described as a replication of the historical and cultural, socio-economic and religious events and phenomena; the three-dimensional models, geo-information virtual systems created by means of the space-based processing and information technologies, including BIM (Building Information Modeling) and GIS (Geographic Information Systems). The software complexes, which function based on the analysis of the valid data and creation of design entities, are used to create the information models of the urban territories. The major companies importing the urban modeling software, Autodesk and Bentley, offer both BIM and CIM tools.Discussion and Conclusions. The term "Smart City" has become especially popular due to development of BIM technologies. This is an innovative approach based on the digital technologies application, which directly affects the activities and efficiency of provided services and rising the city living standard. For solving the thematic problems, there exist the focused technologies and tools of the modern urban environment development. The main task of the "Smart City" is enhancement of the comfort standard of the residents’ living. This task is solved by creating a city information model integrating the information about the terrain, buildings and structures, roads, green spaces, etc.

Evaluation of noise pollution of industrial cities in Ghaziabad by noise map using ARC GIS

Industrial Noise pollution means noise pollution that is clashing and intolerable that occurs in most of the factories. Sound occurs in intolerable form only when it becomes offensive and when it becomes more than a limit that it is known as “noise pollution”. A Geographic Information System (GIS) is a system that generate, be head of, investigate, and maps all forms of information given. GIS joins information to a map, combine location information (where data are to be) with all forms of illustrative information (what data is like present there). This leads to starting point for mapping and investigation that is used in technology and almost every in every industrial factories. Noise maps are implementes to evaluate the effects of noise pollution. In this paper, evaluation of noise pollution of two industries are done which are located in different areas of ghaziabad city. Both industries are machine manufacturing industries. With the aid of a sound level meter (SL-4010), the noise data is gathered. In April, May, and June 2023, measurements are made for both industries in three time periods: 8 a. m. to 10 a. m., 12 p. m. to 2 p. m., and 4 p. m. to 6 p. m. Sound meters were used to measure the noise levels in terms of L10, L50, L90, LAeq, and LNP. As the data observed of both industries from april to june the value of LEQ in morning time (8am-10am) is 73. 96 dB to 79. 26 dB, in afternoon time (12pm-2pm) is 70. 15 dB to 78. 20 and in evening time (4pm-6pm) is 75. 87 dB to 80. 89 dB. As it is observed that industries are producing higher noise pollution beyound a limit set by CPCB.

Assessment of Soil Fertility through GIS Techniques and Thematic Mapping in Rice Growing Areas of Jagtial District in Telangana State, India

Survey was conducted in Jagtial district of Telangana state to identify the soil fertility status of rice growing areas. Soil fertility is one of the major limiting factor for maintaining sustainability in crop yields. Totally 90 surface soil samples collected from the selected rice cultivated farmers’ field. Collected soil samples were tested for texture, pH, EC, organic carbon, available N, P, K and S in order to identify the nutrient status in soils and develop the corrective measures. The soil fertility maps generated through Global Positioning System (GPS) and Arc Geographic Information System (GIS) software to formulate balanced fertilizer recommendations and to understand the spatial variability of nutrients in soil. Survey results showed that the sand was ranged from 44 to 80% and that of silt was 3 to 20 % while the range of clay was 13 to 42% and varied three textural classes viz., sandy clay loam, sandy loam and loamy sand. Soil pH was neutral to slightly alkaline (6.8 to 8.2), electrical conductivity rated as non-saline (0.23 to 0.69 dS m-1), organic carbon was low-medium (0.3 to 0.6%), available-N was low (101 to 195 kg ha-1), available-P was high (26.8 to 61.5 kg ha-1), available-K was medium to high (120 to 449 kg ha-1) and available-S was medium to high (10.0 to 26.8 mg kg-1). Among these organic carbon (%) and available-N were important constraints in soil fertility in rice growing areas of Jagtial district of Telangana state.

GIS Based Monitoring of Critical Area Upstream Watershed of PB. Soedirman Reservoir, Central Java, Indonesia

Upstream watershed has an important role as a conservation area to protect environmental functions for life. The damage of upstream watersheds causes various environmental problems such as soil erosion, landslides, river sedimentation, flooding, and others. Monitoring of upstream watersheds is important to control potential environmental damage. This study used a geographic information system (GIS) for monitoring the critical area upstream of the study site. The aim of this study is to identify critical areas in the watershed by using GIS. Six indicators presented in raster maps such as annual rainfall, soil type, land use type, land slope, population density, and water quality were used to determine the critical area. These indicators were then quantitatively analyzed by using spatial analysis tools of Arc GIS 10.6. Five classes of the critical category were used in this study namely very low, low, moderate, high, and very high. The result showed that 61.74% of the study site was covered by a low class of critical areas. Meanwhile, 37.89% and 0.36% of the study site were covered by moderate and high class critical areas, respectively. Areas with moderate and high class critical areas were found in the eastern part of the study site. The findings of this study provide a reference for determining priority areas for conservation planning.

Preliminary study of sea water intrusion using geographic information system in Temon, Kulon Progo, Yogyakarta, Indonesia

Temon Sub Districts is an administrative area of Kulon Progo Regency, which borders the South Sea (Indian Ocean). The Temon Sub District is directly adjacent to the waters, so it potentially experiences intrusion like other coastal areas in Indonesia. Therefore, groundwater conditions related to the phenomenon of water intrusion need to be identified. The purpose of this study was to estimate seawater intrusion using a geographic information system (GIS) and water quality variables in the Temon Subs Districts. In this study, we used data on electrical conductivity (EC), total dissolved solids (TDS), and groundwater salinity. The sampling was carried out using a systematic random sampling method. Meanwhile, the data analysis was carried out in a qualitative descriptive manner using the spatial interpolation feature in the Arc GIS 10.8 software. Based on the research results, it is suspected that seawater intrusion has occurred in several locations in Temon Sub Districts. The highest suspected seawater intrusion was found in the vicinity of Jangkaran Village, Kalidengen Village, and Plumbon Village. The EC, TDS, and salinity values suggested that around 26% or 9.68 km2 of the area has intruded. This research is expected to enrich references regarding the mapping of seawater intrusion in coastal areas.

Application of Geo-informatics for Soil Erosion Mapping

Soil erosion is a most severe environmental problem in hilly area. The study is carried out on Upper Bagmati River basin, North of Kathmandu valley having an area of 61 Sq.km. (approx). Universal Soil Loss Equation (USLE) model, with Geographic Information System (GIS) has been used to quantify the soil loss. Erosion modelling requires huge amount of information and data, usually coming from different sources and available in different formats and scales and for management of these data, GIS was used, which helped considerably in organizing the spatial data representing the effects of each factor affecting soil erosion. Five essential parameters of USLE Rainfall erosivity factor (R), Soil erodibility Factor (K), Slope length and steepness (LS) factor, Cropping management factor (C) and Support practice factor (P) have been used to estimate soil loss amount in the study area. All of these layers have been prepared in Arc GIS using various data sources and data preparation methods. DEM was prepared from the contour data with the interval of 20m which was used to generate LS factor. The monthly rainfall data (2010) of 17 rain gauge stations within the catchment area have been used to predict the R factor. K, C and P factors in basin area are adopted from the literature. The spatial distribution map of soil loss of the basin has been generated and classified into six categories depending on the calculated soil erosion amount. The annual predicted soil loss ranges between 0 and 292.878 t/ha/y. Low soil loss (mean 9.7 t/ha/y) have been recorded under forested areas. The high rate (mean 40.4 t/ha/y) of soil erosion was found in the cultivation area.

Soil Water Erosion Modeling in Tunisia Using RUSLE and GIS Integrated Approaches and Geospatial Data

Soil erosion is an important environmental problem that can have various negative consequences, such as land degradation, which affects sustainable development and agricultural production, especially in developing countries like Tunisia. Moreover, soil erosion is a major problem around the world because of its effects on soil fertility by nutriment loss and siltation in water bodies. Apart from this, soil erosion by water is the most serious type of land loss in several regions both locally and globally. This study evaluated regional soil erosion risk through the derivation of appropriate factors, using the Revised Universal Soil Loss Equation (RUSLE), which was applied to establish a soil erosion risk map of the whole Tunisian territory and to identify the vulnerable areas of the country. The RUSLE model considers all the factors playing a major role in erosion processes, namely the erodibility of soils, topography, land use, rainfall erosivity, and anti-erosion farming practices. The equation is, thus, implemented under the Geographic Information System (GIS) “Arc GIS Desktop”. The results indicated that Tunisia has a serious risk of soil water erosion, showing that 6.43% of the total area of the country is affected by a very high soil loss rate, estimated at more than 30 t/ha/year, and 4.20% is affected by high mean annual soil losses, ranging from 20 to 30 t/ha/year. The most eroded areas were identified in the southwestern, central, and western parts of the country. The spatial erosion map can be used as a decision support document to guide decision-makers towards better land management and provide the opportunity to develop management strategies for soil erosion prevention and control on the global scale of Tunisia.

Assessment of Soil Erosion Hazards in Kambiti Subcatchment, Murang’a County, Kenya

Erosion is a global problem that destroys soil and adversely affects ecosystem productivity. Soil erosion generally involves many processes but the major activities involve particles being transported and deposited to another location. With an increasing population, soil erosion, water availability, energy production, and biodiversity loss are some of the most pressing environmental problems around the world. Erosion is a hazard associated with agriculture in tropical and semi-arid areas. Kambiti sub catchment is part of the upper Tana catchment. The upper Tana catchment includes 25% of Kenya gazette forest. A large area of land has been degraded, resulting in a drastic reduction in surface water availability during the dry season and poor-quality water during the wet season caused by high silt levels. The main objective of the study is to assess erosion hazards using RUSLE model in Kambiti sub catchment area, Murang’a County. The specific objectives of the study were to determine the effect of rainfall erosivity and soil erodibility factor in Kambiti Sub catchment area in Murang’a County, to determine effect of slope factor to soil loss in Kambiti Sub-catchment area in Murang’a County, to determine the effect of crop protection and management factor in Kambiti Sub catchment area in Murang’a County to soil loss and to determine the strategies for management of soil and water in Kambiti Sub catchment area in Murang’a County. Data was collected from the catchment and analyzed using arc Geographical Information System to obtain the specific parameters in the revised universal soil loss equation model. Interpolation method was used to determine the mean annual precipitation. The k factor is a function of soil texture. Shape file for geological structure for Kenya was obtained from Kenya Agriculture and livestock Research Organisation and analyzed by use of arc GIS to obtain soil erodibility factor. The slope factor was analyzed using digital elevation model from arc view. Digital elevation model was gotten from STRM download. The C factor was derived from Landsat imagery from sentinel of 30metres by 30 metres. It was further analysed by unsupervised classification from Arc GIS. The sentinel clip of Kambiti sub-catchment was joined with ground trothing observations. The results were useful in estimation of soil loss therefore profiling the areas prone to soil loss. Study findings indicated rain drop impact and runoff were primarily responsible for causing erosion in Kambiti sub catchment. Anthropogenic factors played an important role in amplifying the severity of the damage, such as persistent vegetative degradation and destruction of soil structure due to organic matter depletion and routine shallow tillage. In recent years, erosion control has been hampered by the occurrence of gaps in knowledge regarding the integrated nature of erosion processes, leading to land damage caused by rill and inter-rill erosion going unaddressed. Poor people and those lacking capital to invest in reclaiming land are the main causes of abandoning degraded land. Through strategic awareness campaigns and education, soil erosion will be assessed and the knowledge gap will be closed. Participation of farmers in land use decisions is inevitable as it ensures that people who utilize land resources are recognized as equal partners in identifying problems and designing solutions. It was also recommended that Identification and operationalization of alternative off-farm income.

An analytical model for spatial developing of sports places and spaces

Purpose In terms of the use of sports places and spaces, per capita is a determining parameter for the status and perspective of the future. Although there are many uses for the per capita indicator in sports places, there are no consistent scientific and methodological methods for calculating it. Therefore, this study aims to provide an analytical model to determine the per capita index of sports places and spaces. Design/methodology/approach One of the matters that can be considered as the basic information required to develop and construct sports facilities is determination of per capita, which can be used as the most vital information to plan and develop this type of urban utilities. In the history of contemporary urbanization, the use of the per capita concept is one of Reinhard Laumeister’s innovations, a founder of modern urban engineering in Germany, hence, the use of per capita was triggered in 1876, almost 133 years ago. Findings The underlying information of the research in two spatial and descriptive sections was analyzed in the geographic information systems (GIS) software. After the division and network distribution of the boundary by the Thiessen Networks analytic function in the Arc GIS, per capita of each polygon was separately calculated using the presented formula and the population of the related blocks Originality/value Finally, with the qualitative per capita achieved in the previous stage, the study area was classified based on the need for the development of indoor pools to three, privileged, semi-privileged and deprived spectrums.

MONITORING DECADAL PRECIPITATION VARIABILITY IN UPPERINDUS BASIN, PAKISTAN

Upper Indus Basin (UIB) is critical for Pakistan’s economy as it is glacial incomposition and snow melt that provides 80% of the fresh water to Indus River. Decadal fluctuationsin the precipitation in UIB during 1980-2010, using interpolation technique in Arc Map were exploredin present study. The results provided a positive correlation between the winter precipitation andsummer runoff in middle elevation basins of UIB. The map of decadal difference of mean annualrainfall (1980-2010), prepared in Arc Geographic Information System 9.0, revealed that around Gilgit,Skardu, Astore, Chilas and Bunji, was found the least difference in mean annual rainfall, i.e. of -1.68 to-2.14mm, whereas area around Kakul experienced maximum rainfall decadal difference ranged from-13.63 to -17.45mm. The study suggested that south of lesser Himalayan areas experienced maximum rainfall variability during the period 1980-2010, whereas, lesser variability in north of Himalayan areas inferred safer addition in fresh water in Indus from its glacial reserve.

Deep Learning Framework for Landslide Severity Prediction and Susceptibility Mapping

Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and distance from road, lithology, and rainfall are considered. A landslide susceptibility map was generated using the Arc geographic information system (GIS) tool for all the triggering factors using frequency ratio method, Shannon entropy method, Relative effect method, and fuzzy logic method. A new Deep Neural Network (DNN) framework has been developed for the multiclass classification and prediction of landslide hazard zones as low, moderate, high, and very high. Existing works are only uses statistical methods, but the proposed work has used DNN to predict landslide severity at four different level even for semi data with over accurately. The training data for deep learning model are generated using the Sentinel Satellite images and field survey. The label for training the data are generated from the Landslide Susceptibility Index which are generated from statistical method. Among all the statistical method generated data the Shannon Entropy data is the most accurate of the four statistical methods achieves 99.16%, accuracy. The frequency ratio method based data achieves 97.08% accuracy, the relative effect method based data achieves 92.72% accuracy, and the Fuzzy logic method based data achieves 86.60% accuracy.

GIS Based Planning of Forest Road Alignment in Periyar Tiger Reserve, Kerala, India

In hilly places, constructing and building forest roads requires a variety of economic and environmental criteria. To develop a solution that minimize construction, maintenance, and adverse environmental effects, road management must take into account as many alternative alignment options as they can. The idea of this research was to plan the network of forest roads in the Periyar Tiger Reserve's mountainous region using Geographic Information Systems (GIS) based on Multi-Criteria Decision Analysis (MCDA). These techniques were applied using the study area's slope, aspect, Elevation, NDVI, drainage and susceptibility to landslides datasets. In addition, the road network created using the GIS-MCDA approach was contrasted with the existing road networks. The key elements that affect the road network in the research area were found, and the necessary maps were produced and categorized. The maps were graded using MCDA to determine the weight of both useful aspects as the next step in determining the significance and role of the aforementioned elements in the cost of road building. Second, using the Arc GIS 10.4 weighted overlay analysis tool, a forest potential map for road building was created by overlaying the weighted maps of the influencing elements. Thirdly, the competence of a map was divided into Six categories: very high, high, moderate, low, very low and Restricted roading Suitability. Finally, using a weighted overlay method to combine the road network and road planning potential map, the existing road network was analyzed. The findings of this study indicated that the majority of existing roads were located in high and moderate road Suitability. A small percentage was located in low road Suitability, which can be taken into account for alignment. These results suggested that the design of forest road planning in hilly areas can be more precisely accomplished using the multi-criteria evaluation method. Similar method as used in this study can be applied to other forested sites.

Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio method in Sikkim Himalaya

Sikkim Himalaya is located in the North-Eastern Himalaya and is prone to landslides caused by rainfall, anthropogenic factors, earthquakes, and other natural disasters. This study aims to identify landslide susceptibility map for the Sikkim Himalaya, India, utilizing an integrated methodology of Geographic Information System (GIS), Remote Sensing (RS), and the Frequency Ratio (FR) method. Identification of landslide susceptibility map in this region has used multiple datasets as rainfall, earthquake's magnitude, slope angle, altitude, distance to drainages, topographic roughness index, geomorphology, geology, soil, gravity anomaly, distance to faults, stream transportation index, topographic witness index, stream power index, distance to roads, LULC, and NDVI. All the above-mentioned factor/thematic layers were generated using remotely sensed as well as ground data with the help of Arc GIS software. Therefore, the weights of these all-thematic layers were calculated using the FR model for the occurrence of landslides prone in the area. After that, calculated weights of all factor/thematic layers were integrated with Arc GIS software to generate a landslide susceptibility map. The landslide susceptibility zone of the study area has been divided into 5 different classes, namely ‘Very High (11.88%)’, ‘High (15.75%)’, ‘Medium (25.88%)’, ‘Low (25.30%)’, and ‘Very Low (21.19%)’. The accuracy assessment of the study area was 87.8%, which was done by the Receiver Operating Characteristic (ROC) curve method. This research investigates the possibility of using broader approaches to determine landslide-prone areas.

Application of the Gavrilovic model to estimate the risks of soil erosion in Al-Salman district using remote sensing and GIS techniques

The study took the techniques of remote sensing (RS) and geographic information systems (GIS) as a basis for the cartographic representation of the risks of soil erosion within the Al-Salman district and then analyzed it geomorphologically. )31.20'.0''-29.20'.0'' (north, and (45.30'.0''-44.0'.0'') east longitudes with an area of (17463.84 km2). The study used six satellite views from the data of the American satellite (Landsat 8), and the Dem (Digital Elevation Model) files were relied on with an accuracy of (30 m), and it relied on the geographic information systems program (Arc GIS V.10.3) and the program (ERDAS 2014) in Drawing, improving, showing and diagnosing the spectral characteristics of the visuals to serve the study, and it was also clear that Al-Salman district was exposed to geomorphological risks represented by soil erosion that was estimated according to the Gavrilovic model. km2), which is equivalent to a percentage of (89.31%) of the total area of the study area. The light erosion category ranked second with an area of (1866.02 km2), representing a percentage of about (10.68%) of the total area of Al-Salman district, while it formed The medium erosion category is a very small percentage compared to the area of the study area, it reached (0.02 km2), which is equivalent to about (20000 m2).

Geospatial Distribution of Health Centers in Dass Local Government Area of Bauchi State, Using Geographic Information System (GIS) Tools

This paper examined the spatial distribution of health care facilities in Dass local government area of Bauchi state using GIS tools. Data were obtained from primary and secondary sources: a GPS was used to collect the coordinates of each health care facility. Data from the Ministry of Health (Bauchi State) about the location, name and types of health care facilities in the study area included one general hospital; one model primary health centre, fourteen primary health centers, one clinic, one dispensary and one health post. Population data was obtained from the National Population Commission (NPC, 2006). GIS analysis was used in analyzing the data. The analysis of nearest neighbour was done by using the extension of Arc GIS 10.5 in the spatial analyst tool and average nearest neighbour. The result shows that there is less than 1% (0.01 level of significance) likelihood that the spatial pattern of the distribution of health care facilities in Dass Local Government Area is dispersed and this could be as a result of random chance. This might be as the result of the fewer number of health facilities. The research recommends that government should locate health care services close to the people as possible as distance was found to influence utilization.

Distribution and population status of Adansonia digitata L. (baobab) and its contribution to livelihood in Makueni County, Kenya

Adansonia digitata L. commonly known as baobab is a globally known high valued multipurpose tree. The current study was designed to map the distribution and determine the effects of different land use systems (cropland, grazing land and settlement area) on the species population density, composition, health and productivity in Makueni County. Livelihood potential of baobab in the studied area was also assessed. Two sub counties; Kibwezi East and West in Makueni County where baobab populations occur were purposely selected for this study. A reconnaissance study was carried out followed by selection of three contrasting representative land use systems: Namely cropland, grazing land and settlement area/homesteads using Google Map through a desktop study. Plots of 0.5 km long and 0.25 km wide were used to assess the population and health status of baobab trees. Market centers and chiefs’ camps were randomly sampled for a household and market survey where a total of 423 informants were interviewed. Baobab growth characteristics across the three land use systems in the two sub counties as well as household and market data were analyzed using GraphPad Prism version 8.4.3. The waypoints were downloaded from the Garmin etrex 10 GPS handset into Arc Map 1.0 of Arc Geographic Information System (GIS) (ESRI, Redlands, CA) where the baobab distribution maps were generated. The findings revealed that the baobab populations occurred in clusters of high to low density. Density and fruit production of baobab trees were statistically different across the three land use systems in the two sub counties while height, DBH and crown diameter did not differ significantly. No saplings were found in the study area. The study revealed that there is a huge potential for baobab fruits in diet especially during food scarcity. Therefore, farmer training is advisable to augment local knowledge and skills for enhanced value addition of baobab products.

Different Clinical Features of Idiopathic Achalasia in Various Countries

Idiopathic achalasia is a motility disorder affecting the lower esophageal sphincter. Dysphagia is a hallmark symptom, but patients may exhibit other symptoms. The aim of this review is to compare achalasia symptoms globally. PubMed and Google Scholar were filtered from 1952–2021 with the search terms achalasia, epidemiology, diet, countries, and genetics. A total of 14 articles addressed demographics, symptom profiles, genetics, and diagnosis criteria amongst 2463 patients. Data on countries’ climate and diet were obtained through Arc Geographic Information System (GIS) and Our World in Data. Countries were grouped by similar climate zones and diets. Achalasia symptoms varied by region. In West Africa, patients exhibit parotid swelling, anemia, and dehydration; diminished appetite in East Asia; dysphagia and weight loss in West Asia and Europe; respiratory symptoms, reflux, and retrosternal pain in North America; and vomiting in Southern Asia. Weighted percentages of dietary oils/fats were (24.3%) in North America, Western Asia (17.8%); Europe (17.7%); East Asia (17.6%); West Africa (14.7%); Southern Asia (13.8%); North Africa (12.4%); Northeast Africa (10.1%). Conditions such as Down Syndrome and Triple A syndrome are associated with achalasia. There was no correlation for achalasia presentation and climate zones. Achalasia symptoms are likely multifactorial. Diet, genetics, and environmental factors may play significant roles.