GIS Techniques Research Articles

Spatial coal seam modeling and reserve estimation using geostatistical methodologies by GIS technique in a selected coalfield in Ermenek Basin, Turkey

The accurate and reliable calculation of tonnage and quality of coal is vital for the success of mining projects. The Ermenek coal basin is located in the Western Taurus Mountains in the southern part of Turkey, which covers an area of approximately 620 km2 and is a Neogene coal basin. This paper generates spatial modeling of Pamuklu-Tepebaşı coal seams in the Ermenek Basin and the prediction of coal reserve by using geostatistical methods with Ordinary Kriging (OK) based on the GIS technique. The data used in the study were obtained from 82 boreholes belonging to a private company that has actively produced coal in the Pamuklu-Tepebaşı coalfield. In this study, the OK method was applied to spatial coal seam modeling for comparison of the performance of 11 distinct models. Using the rational quadratic models better explained the spatial structure of the coal seam depth data. The nugget-sill ratio indicated high spatial dependency with 0.01 and 0.02 for coal seam upper-lower surfaces, respectively. The kriged coal depth maps for upper and lower coal seam surfaces have been created using ArcGIS 10.2 software. As a result of these analyses, it was calculated that there is a coal reserve of 3.734.017 m3 using the determined surfaces with OK in the study area. Furthermore, developed spatial distribution maps in the study area could be helpful to plan further exploration activities.

Ensembling machine learning models to identify forest fire-susceptible zones in Northeast India

Forest fires pose significant challenges by disrupting ecological balance, impacting socio-economic harmony, and raising global concerns. North-East India (NEI) experiences high incidences of forest fires, making it crucial to implement suitable management measures considering the driving forces influencing fire likelihood. This study aims to identify forest fire susceptibility zones in NEI by using five machine-learning modeling approaches, Boosted Regression Tree (BRT), Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Tree (CART), and Multivariate Adaptive Regression Splines (MARS), and an ensemble method. Forest fire data from the SNPP – VIIRS sensor (2018–2019) were rectified for spatial autocorrelation. Thirty-two responsive predictor variables related to topographic, climatic, biophysical, and anthropogenic factors were used as model inputs and multicollinearity analysis was performed to eliminate highly correlated predictors. Results indicate that the southern and southeastern regions of NEI, characterized by ample solar radiation, enhanced vegetation index, high human population density, and jhum cultivation, contribute significantly to higher susceptibility to forest fires. The Random Forest model performs best among the models employed, achieving an AUC value of 0.87. The ensemble susceptibility map, binarized based on AUC weighting, covers 29.54% of the total geographic area and 44.42% of the forested area of NEI. The vulnerability levels vary among states, with Mizoram showing the highest susceptibility at 89.27% and Sikkim exhibiting the lowest vulnerability at only 0.49% of their respective geographic areas. This map provides valuable insights for implementing effective forest fire management plans in the region. Moreover, the methodology utilized in this study, which incorporates satellite imagery, GIS techniques, and improved modeling techniques, can be replicated in any geographical region worldwide to facilitate effective forest fire management at a regional to large scale.

Delineation of Groundwater Potential Zones for Sustainable Development and Planning using AHP and GIS Techniques in the Coal Mining Province of Mahan River Catchment Area

The present research aims to address the drinking water crisis in the Mahan River catchment area resulting from the disruption of groundwater availability due to extensive coal mining. The study uses GIS-based Multi-Criteria Decision Analysis (MCDA) to map the groundwater potential of the area by analysing several factors that affect groundwater availability, including rainfall, water depth, geomorphology, geology, soil, land-cover/land-use, and topographic characteristics derived from DEM. The groundwater potential map created using the MCDA technique classified the area into low, moderate, and high groundwater potential zones. The map was validated and verified using water table depth and electrical conductivity values available in the region, indicating that it can be used to identify groundwater recharging sites. The study’s results show that about 30% of the area has high groundwater potential, and more than 45% of the area has moderate groundwater potential. The information derived from the study can be used for sustainable management and proper planning of groundwater resources in the Mahan River catchment area. Overall, the study presents a useful approach to address the groundwater depletion problem resulting from coal mining activities in the Mahan River catchment area.

A Study of Occupational Structure in Kerala State Using GIS Techniques

Occupational structure is the distribution or division of working population in different sectors based on occupations. It is one of the key elements in manifestation of population composition of a region. The economy is segregated based on its occupational structure namely, the agriculture sector, industrial or manufacturing sector and service sector. Occupational structure provides clear picture of working and non-working population in an area. The growth and prosperity of a region largely depends on the size of working population and proportion of productive workers engaged in various economic activities. The objective of this study is to find out the shift in occupation from primary sector to other sectors and the rate of change in last two decades from 2001 to 2011 in Kerala state with district as spatial unit. The study is based upon the secondary data collected from Census 2001 and 2011.By using GIS techniques thematic maps were prepared to show the variation in occupational structure in the study area. To find out the changes in occupational structure, percentage of workers engaged in four categories are to be calculated. There is a remarkable shift of workers from agriculture to non-agricultural sector in Kerala.

Advanced Ambiance Sensing Device using ESP32 and BME680

Occupational structure is the distribution or division of working population in different sectors based on occupations. It is one of the key elements in manifestation of population composition of a region. The economy is segregated based on its occupational structure namely, the agriculture sector, industrial or manufacturing sector and service sector. Occupational structure provides clear picture of working and non-working population in an area. The growth and prosperity of a region largely depends on the size of working population and proportion of productive workers engaged in various economic activities. The objective of this study is to find out the shift in occupation from primary sector to other sectors and the rate of change in last two decades from 2001 to 2011 in Kerala state with district as spatial unit. The study is based upon the secondary data collected from Census 2001 and 2011.By using GIS techniques thematic maps were prepared to show the variation in occupational structure in the study area. To find out the changes in occupational structure, percentage of workers engaged in four categories are to be calculated. There is a remarkable shift of workers from agriculture to non-agricultural sector in Kerala.

Fostering environmental and resources management in Sudan through geo-information systems: A prospective approach for sustainability

Environmental and land resource degradation is a serious problem that poses significant challenges in Sudan and worldwide generally. Despite the fact that the physical environment components are the underlying economic resources and production assets in developing countries like Sudan, and they directly affect the nation’s socioeconomic aspects of income, health, water availability, food security, and many others. The interventions and protective measures were insufficient to meet the magnitude and extent of the ongoing degradation and resource wastage. Based on the analysis of the indicators and trends of the environmental and natural resources management ‘status quo’, this paper is an attempt to overview and investigate the state of environmental and natural resources management and governance in Sudan. Further discussion delves into the utilization of geo-information systems in Sudan’s environmental and resource management by analyzing and reviewing “some previous case studies” where GIS approaches and techniques were deployed. The paper further strives to explore and highlight the opportunities and potential contributions of GIS in the context of Sudan’s environmental and resource management. Lessons learned from the previous experiences were considered, and the recommendations for the future use of a tailored geo-information system in Sudan context were highlighted and suggested to support better practices and sustainability insights for environmental governance and resources management.

Assessing landslide susceptibility in Lake Abya catchment, Rift Valley, Ethiopia: A GIS-based frequency ratio analysis

Ethiopia's varied landscape, significant rainfall, and diverse geological characteristics pose risks of landslides. The specific research area spans 40 km2 within the Lake Abaya catchment area in the Rift Valley of Ethiopia. This investigation aimed to map landslide susceptibility using remote sensing information, GIS technology, and frequency ratio analysis. It evaluated multiple factors influencing landslide susceptibility. The process involved meticulous mapping of thematic layers, utilizing GIS techniques and diverse data sources, including primary data, satellite imagery, and secondary sources. A combination of Google Earth image analysis and field surveys was used to map landslide susceptibility in inaccessible areas. It was determined that 138 landslide sites existed. Of these, 30% (41 points) were assigned to the test of the model and another 30% to the training of the model, for a total of 97 points. The landslide susceptibility was classified into five categories based on frequency ratio analysis of the landslide susceptibility index (LSI): very low, low, moderate, high, and very high. The northeastern sector of the study area demonstrated a comparatively diminished susceptibility to landslides, ranging from low to moderate, whereas the central and southern regions showcased markedly elevated vulnerability. An evaluation of the model's accuracy using the area under the curve (AUC) method based on test inventory landslide data produced encouraging results: 84.8% accuracy on the success rate curve and 78.8% accuracy on the prediction rate curve. Based on the frequency ratio model, a susceptibility map is derived to represent susceptibility levels accurately.

Land Use Planning by Using GIS Techniques for Land Resource Inventory (LRI)- Northern Dry Zone of Karnataka, India

A study was conducted to determine land capability and to develop suitability map based on soil characteristics and climatic factors of watershed area. Detailed soil survey was carried out for Donur-2 micro watershed which comes under Basavana Bagewadi taluka of Vijayapura district, Karnataka to acquire the comprehensive data related land resources. From the study area, it was observed that based on soil-site characteristics four soil series were identified such as Dadamatti, Karjol, Nidoni and Rampur series and mapped into eight mapping units using GIS techniques. Donur-2 watershed area has been grouped into three land capability classes (LCC) viz., II, III and IV with four subclasses IIes, IIIs, IIIse and IVe. Subclass ‘e’ is due to major limitation of soil property group ‘e’ i.e erosion and slope, subclass ‘s’ is due to major limitations group ‘s’ having parameters like texture, depth and gravelliness. Subclass ‘se’ and ‘es’ are due to limitations of both soil parameters group above mentioned, however se and es are different classes which are based major limitation one of the group and followed by other group. Land capability map was developed using GIS techniques which indicates that out of 324.3 ha study area, LCC class IIIs covering major area i.e. 179 ha (55.12%), followed by class IIs i.e. 109 ha (33.51%), class IVe i.e. 23 ha (7.15%) and minor area of 7 ha (2.15%) area is covered by class IIIse. Soil suitability assessment indicates that majority of land is moderately suitable for agriculture. Class III soils are designated as moderately fertile agricultural land with significant constraints. However, with special conservation practices soils under class III can be used for cultivation of different crops. Class IV soils are categorized as reasonably fertile for intermittent cultivation, characterized by significant restrictions that limit crop options but with careful management practices these can be used for cultivation of arable crops. Therefore, the utilization of a land use planning approach (LUP) is instrumental in formulating tailored land resource management strategies to enhance land productivity, mitigate land degradation and attain sustainability goals.

Analyzing the spatial relationship between land surface temperature and elevation in three gullies locations in southeastern Nigeria

Gully erosion is a dangerous phenomenon that threatened human existence, plants and animals communities. Families are being separated from their ancestral home and livelihood due to gully erosion. Also, available agricultural lands to combat food insecurity are contently depleted on yearly basis across the globe as a result of gullies menace. Southeastern Nigeria is highly vulnerable to gully erosions due to it geology and studies on spatial relationships between gully LST and elevation has not been carried out, particular by applying remote sensing and GIS technique to investigate it variations. Available studies where limited to mapping and causes of gully erosion in the region. The study applies LST and elevation data to investigate correlation on three gullies locations. LST was derived from Landsat data and was first converted to radiance image while the elevation data was obtained from Google Earth image. Elevation data was used to produce raster surface in that cell values equivalent to LST at every point can be extracted. Three sets of paired sample points of LST and elevation was extracted from the three gullies locations and used to compute correlation coefficient (r). The study observed at Nanka gully a strong negative correlation of -0.665. This implies an increase in LST correspond to decrease in elevation within the gully. At Ekwolobia and Aguluezechukwu gullies sites, positive correlation coefficient of 0.692 and 0.910 were obtained. The positive correlation coefficients implied that LST and elevation increase or decrease within the gullies. This might be due to unequal distribution of radiation within gully surface as a result of three canopies. For further study, it is recommended that improve elevation data source like LiDAR elevation data should be use to investigate spatial correlation between LST and elevation at gully location.

Regional gap and sustainable development of interpreting level in mainland China: A statistics and GIS-based study.

Against the backdrop of globalization, interpreting, a translation communicative activity in a verbal way, plays an increasingly important role in international communications and exchanges. In response to this world pattern, the Chinese government attaches great importance to the interpreting industry. However, due to the national condition of uneven regional development, the English interpreting level across China is also unbalanced. Confronting this circumstance, previous research only stagnates at the level of recognizing the problem, but very few studies have attempted to solve the problem. Thus, the current study aims to figure out the regional interpreting level in mainland China by establishing and utilizing an innovative indicator system based on statistics and geography technologies. Based on the literature review and empirical questionnaire survey from different stakeholders, the study proposes an indicator system containing 3 first-level factors and 7 second-level factors to measure regional English interpreting levels. The weight of each indicator and scoring method is laid down based on factor analysis and interval marking. In addition, putting the innovative indicator system into practice, a total of 38 groups of regional data are collected to rank the regional interpreting level across China. Integrating with GIS and statistical techniques, the result visually shows that the English interpreting level across China is uneven at present: higher in the southern and eastern parts of China compared to that of northern and western China, which is unfriendly to sustainable development in the future. Facing this reality, a following-up analysis has been made for offering explanations of the results and suggestions for regional interpreting sustainable development.

Groundwater potential zones delineation using GIS and AHP techniques in upper parts of Chemoga watershed, Ethiopia

Water is one of the most imperative needs and used for innumerable purpose. The needs of groundwater exploration have being increased due to the radical climatic changes, for continually increased population growth and a change of human lifestyle. GIS and AHP of multicriteria decision making are the most effective, applicable and logical approaches to delineate the groundwater potential zones in upper parts of Chemoga watershed. GIS and AHP are a 7 computer-based systems used to handle, store, manipulate, analyze and present geospatial data to resolve several complicated problems in the environment. Hence, the groundwater potential zone is delineated by overlaying the weights of ten influencing factors (lineament density, rainfall, geomorphology, Lithology, slope, drainage density, roughness, land use/land cover, depth to groundwater level and elevation) in ArcGIS platform under spatial analysis tool. All those influencing factors are selected on the bases of their contribution for the ground water recharge. Based on the findings of weighted overlay analysis, 11.1, 18.2, 47.1, 15.4 and 8.2% of the region depicted very good, good, moderately good, poor, very poor groundwater potential zones, respectively. The investigated groundwater potential sites have validated by seven existed borehole data and hence the study verified their close relationships. Out of seven boreholes, about 7–4 and 3–1 were found under very good to good and poor to very poor groundwater potential zones, respectively.

Eurasian aspen (Populus tremula L.): Central Europe's keystone species 'hiding in plain sight'.

Knowledge of Eurasian aspen's (Populus tremula L.) ecological and growth characteristics is of high importance to plant and wildlife community ecology, and noncommercial forest ecosystem services. This research assessed these characteristics, identified aspen's habitat optimum, and examined causality of its current scarce distribution in central Europe. We analyzed a robust database of field measurements (4,656,130 stands) for forest management planning over 78,000 km2 of the Czech territory. Our analysis we used GIS techniques, with basic and multivariate statistics such as general linear models, ordination, and classification. Results describe a species of broad ecological amplitude that has heretofore attracted little research attention. Spatial analysis showed significant differences between aspen and other forest non-forest cover types. Additionally, we found significant association between the proportion of aspen in a stand, the size of forest property, and the forest category. The results demonstrate historic reasons for aspen's widespread presence, though contemporary occurrence is limited. This study advances the concept of a quantitatively based aspen ecological optimum (niche), which we believe may be beneficial for numerous aspen associates in the context of anticipated warming. Irrespective of local ecology (i.e., the realized aspen niche), the study confirms that profit-driven policy in forestry is chiefly responsible for historic aspen denudation in central Europe. Even so, we demonstrate that ample habitat is present. Further solutions for improving aspen resilience are provided to support these keystone systems so vital to myriad dependent flora and fauna.

SPATIAL ESTIMATION OF SOIL EROSION USING GEOSPATIAL TECHNIQUE – A CASE STUDY OF JANJEVA RIVER CATCHMENT (KOSOVO)

The aim of the study is to analyse the spatial estimation of soil erosion in a small size river catchment of Janjeva (Kosovo). Soil erosion is becoming a serious threat and its spatial estimation is crucial for soil resource protection and management. The Revised Universal Soil Loss Equation (RUSLE) methodology integrated with GIS techniques was applied to estimate the annual erosion rate. Different datasets including open-source data were used to find main components of soil erosion. The results show different soil erosion classes depending on lithological settings, landforms, climate conditions, soil properties, land cover and soil conservation practices. By calculating RUSLE parameters for Janjeva River catchment (84 km²), we found out that mean annual erosion rate is 1 t·ha-¹·yr-¹. Erosion rate class <5 t·ha-¹·yr-¹ dominates the catchment’s area with 92.5%, while other classes have 7.5% of catchments total area. Highest rates of soil erosion are found in volcanic rocks, steep slopes and soils without conservation practices. Soils located in western part of the catchment with adequate conservation practice have minimum erosion rate.

Analyzing Role of FSI in City Sprawl- Case Study: Pune City

Pune is the second-largest city in the state of Maharashtra after Mumbai, and is an important city in terms of its economic and industrial growth. Over the years Pune Municipal Corporation area has grown in concentric rings. Future growth of PMC will be mainly governed by existing transport corridors, existing and future industrial developments in and around PMC and the expansion of central business district (CBD). The aim of the research is to analyze role of FSI in city sprawl supported with a case study of Pune City. The objectives of the research are- to assess existing and proposed policies/projects undertaken in Pune City for last two decades, to understand population growth trend and its distribution within and around the city, to analyze factors contributing to intensification and spatial distribution of population density, to examine the effects of increased population density on the existing infrastructure facilities in the urban settlements and lastly to propose strategies or proposals for the selected study area. The methodology adopted for the study initiates with assessing the data collected from secondary sources. The increase in population and built-up area attributed to various factors are studied using satellite images and GIS techniques. Population and built-up density can be linked up together to understand how the former growth affects the latter. The distribution and pattern of population density helps to provide useful information in provision of necessary service infrastructure. Finally, different approaches of accommodating the future population are studied and proposed in the study. Keywords Urban sprawl; Density; Spatial Distribution; Accessibility; Urban Growth

Integrated approach for groundwater potential exploration in Abbay River Basin, East Africa

This paper presents and examines groundwater potential zones with the help of remote sensing and GIS methods for controlling and investigating the geospatial data of each parameter. Groundwater is a very important source for water supply and others, considering its availability, quality, cost, and time-effectiveness to develop. It is virtually everywhere and yet variable in quantity. Because of several conditions, such as rapid population growth, urbanization, industrialization, and agricultural development, groundwater sources are under severe threat. Climate change plays an important role in the quality and quantity of groundwater potential. In addition, climate change severely affects parameters that influence groundwater recharge. Unreliable exploitation and poor quality of surface water resources tend to increase the decline in groundwater levels. Hence, it is necessary to identify groundwater potential zones that can be used to optimize and monitor groundwater resources. This study was conducted in the Abbay River Basin and identifies the location of groundwater potential for developing new supplies that could be used for a range of purposes in the study area, where groundwater serves as the main source for agricultural purposes rather than surface water. Seven selected parameters—lineament density, precipitation, geology, drainage density, land use, slope, and soil data—were collected, processed, resampled, projected, and reclassified for hydrological analysis. For the generation of groundwater zones, weightage was calculated using an analytical hierarchy method, reclassified, ranked, and overlaid with GIS. The obtained results of weightage were lineament density (37%), precipitation (30%), geology (14%), drainage density (7%), land use land cover (5%), slope (4%), and soil (3%). The consistency ratio estimated for this study was 0.089, which was acceptable for further analysis. Based on the integration of all thematic layers and the generated groundwater potential zones, the map was reclassified into five different classes, namely very good, good, moderate, poor, and very poor. The results of this study reveal that 1295.33 km2 of the study area can be considered very poor, 58,913.1 km2 is poor, 131,323 km2 is moderate, 18,557 km2 is good, and 311.5 km2 is very good. Any groundwater management project performed in the better regions would offer the greatest value. A similar study would be valuable before planning any water resource development activity, as this would save the expense of comprehensive field investigations. This study also demonstrates the importance of remote sensing and GIS techniques in mapping groundwater potential at the basin scale and suggests that similar methods could be applied across other river basins.

Assessing the impact of cyclonic storm Tauktae on shoreline change in Mangaluru coast using geospatial technology

Cyclones are natural events that occur with atmospheric pressure variations. Compared to the eastern coast of India, the western coast has less cyclonic activity. Even though some of the cyclonic events turn into severe cyclonic storms and cause a huge impact on ecological and anthropogenic activities. This research focuses on the impact of cyclone Tauktae on the Mangalore coast. Cyclone Tauktae, one of the most powerful to pass through coastal Karnataka, caused significant damages, affecting 121 villages and resulting in four casualties. Utilizing geospatial techniques, this study employs Sentinel-2 satellite images to analyze shoreline changes during pre and post-cyclone Tauktae. A GIS technique involves the extraction of shorelines using 10-meter resolution images, with manual digitization excluding natural and man-made structures. Transect lines are generated with the help of DSAS to measure shoreline movement, distinguishing accretion and erosion. Rainfall conditions during the cyclone period are mapped using gridded rainfall data. The study area, encompassing ten coastal villages from Someshwara to Sasihithlu, is characterized by its vulnerability to cyclones. Results reveal substantial shoreline changes, with notable erosion in central and northern Mangaluru, Tannirbavi, and Hosabettu. Accretion is observed in south Someshwara and north Sashihitlu. Rainfall patterns are analyzed using Persian CCS gridded data, depicting the dynamic nature of precipitation during the cyclonic event. This research contributes valuable insights into the short-term effects of cyclonic storms on shorelines, emphasizing the importance of geospatial techniques for coastal management. The findings serve as a foundation for mitigating cyclonic impacts and enhancing resilience in the Mangalore coast, aiding future coastal management strategies

An Overview of Geomorphological Mapping: A Case Study of Rimbi Chhu River Basin, Sikkim, India

Geomorphology is the primary science which demonstrates the basic understanding and mapping of terrain features. A geomorphological map consists of scientific data and dynamic source of information on characteristics of landforms, their origin and evolution, which can be recorded in a map form. Basin hydrology also gets impacted by the terrain features of a basin as overland flow, stream flow and through flow is largely determined by the underneath surface. The configuration of the basin topography reflects the nature of the interaction between process and form. Profound understanding and in depth analysis of geomorphological features of a river basin can provide beneficial information for predicting, preventing and mitigating natural hazards; managing natural resources sustainably for future generation. Implementation of remote sensing and GIS techniques have fostered incredible improvements in landform recognition and accelerated the growth of geomorphological research. The river Rimbi Chhu has been selected as the study area in order to determine terrain configuration in relation with geomorphological features of the basin area. Visual representation of terrain (such as aspect, slope, channel networks, different river profiles, shaded relief and flow direction) and geomorphological (saddle, ridge line, convex-concave slope, rounded hills, fault for instance) derivatives is therefore illustrated, as well as a description of the challenges and crisis that can occur in this context.

Correlations between Urban Morphological Indicators and PM2.5 Pollution at Street-Level: Implications on Urban Spatial Optimization

During rapid urbanization, microclimate environment deterioration through events such as haze pollution and heat waves has continuously occurred in cities, which greatly affects the living environment, production activities, and health of urban residents. Therefore, it is particularly necessary to explore methods for controlling and optimizing the urban microclimate environment. In this paper, based on the mechanism of the effect of urban spatial structure at street-level on the distribution of atmospheric particulate matter, an indicator system that can be employed to comprehensively describe and quantify urban morphological structure at street-level was constructed from eight aspects: the spatial morphology of street-valleys, intensity of land use and development, geometric structure of buildings, inhomogeneity of buildings, roughness of the underlying surface, distribution of ecological landscapes, 3D architectural landscape morphology, and ventilation potential. Furthermore, using satellite remote sensing images and vector thematic maps of Shanghai, indicator factors were quantified by applying GIS technique. The intrinsic mechanism of the influence of the urban morphology on the diffusion and transport of atmospheric particulate matter was comprehensively analyzed by combining statistical methods and data mining algorithm, and eight key dominant factors were identified that can be considered to improve the urban ventilation conditions and help control urban air pollution, namely, the land use intensity, urban canopy resistance, vegetation cover, spatial congestion rate, comprehensive porosity, height-to-gross floor area ratio, building density, and average building volume ratio. As such, according to the quantitative analysis results for various combinations of the dominant factors, a spatial optimization strategy at street-level that can help improve the urban air quality was proposed in terms of identifying the pathways through which urban spatial elements affect the distribution of particulate matter, i.e., controlling the source–flow diversion–flow convergence process.

Remote Sensing & GIS Integration Bases Evaluation of Ground Water Quality in Telangana State, India

About 85% of drinking water needs in rural and 40% drinking water needs in urban areas are met from groundwater resources in Telangana state. There is a huge demand of ground water for different uses like agriculture, drinking and industrial purposes as the command area is very low in the state and it is evidenced by the fact that around 70% irrigation is dependent on ground water sources as compared to other surface sources like Tanks/Canals/Reservoirs etc. Climate change has affected the hydrological cycle with uncertain and increased variability in rainfall followed by with high rainfall in a short span of time resulting more surface runoff which ultimately decreases there charge to groundwater. Decreased recharge to the groundwater and excess withdrawal of groundwater has accelerated the depletion of groundwater resources there by resulting in stress on groundwater regime in terms of quality as well as quantity. The groundwater quality evaluation of Telangana state is carried out by using legacy quality data (2012-14) collected from Rural Water Supply & Sanitation Department, Government of Telangana. Contamination spread of groundwater is one of the most important concerns that have received attention at regional, local and global levels because of their importance on public health and its further impact in ecosystems. The spatial distribution of chemical parameters like pH, Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Fluoride (F), Chloride (Cl), Iron (Fe), Nitrate (NO3) and Sulfate (SO4) are examined with respect to its contamination level. The spatial distribution and concentration of chemical elements is carried out by using spatial interpolation technique namely Inverse Distance Weightage (IDW) method from the point source data. The distribution maps reveal important information to understand the hot spot areas of the groundwater systems and for identification of potential areas for providing safe drinking water supply. Site specific water conservation and artificial recharge measures are needed to be taken up with scientific lines by using Remote Sensing & GIS techniques, for enhancing the groundwater storage and also improving its quality.

THE ASSESSMENT OF SCENIC ATTRACTIVENESS ON COASTAL WAYS: A CASE STUDY OF PERSEMBE-BOLAMAN (ORDU-TURKEY)

The biophysical characteristics of the areas that can be seen while travelling on motorways have an impact on the perception of the landscape. Highways provide diverse landscape experiences to travellers according to their natural and cultural qualities. Especially coastal ways that combine with nature and the sea have a high potential for scenic attractiveness. This study aims to analyse the scenic attractiveness of coastal ways using GIS and RS techniques. Persembe-Bolaman coastal way in the Black Sea Region of Turkey was selected as a case study. Three road features and seven viewshed features that are assumed to affect landscape attractiveness on the Persembe-Bolaman coastal road were selected. The data set of these features was categorised into three clusters by k-means clustering, one of the unsupervised learning algorithms. The most attractive cluster in terms of scenic attractiveness was selected by determining the characteristics of the clusters. In conclusion, it was found that the scenic attractiveness was the highest in Cluster-1, which corresponds to 46.3% of the selected route.