Geographic Information System Methods Research Articles

Flood hazard analysis in Mumbai using geospatial and multi-criteria decision-making techniques

Abstract Flood risk assessment remains a crucial element, particularly within locations highly susceptible to repeated flood occurrences. This study seeks to conduct an elaborate flood risk analysis for Mumbai, India based on an integrated method of geographic information systems and analytic hierarchy process (AHP). In this study, land use/land cover, average annual rainfall, elevation, drainage density, normalized difference vegetation index, distance from rivers as well as distance from roads are identified and considered. For this reason, the expert survey utilizes the AHP weights so as to find out the significance of these factors towards flooding danger. Investigations show a flood risk index and a corresponding map for Mumbai, where all areas are divided into risk zones very low to very high. ‘High’ risk or ‘Very High’ risks are particularly situated along the rivers. Such details offer critical knowledge to policymakers who will undertake informed emergency preparedness measures designed to shield Mumbai's citizens and assets. Therefore, this research is considered as one of the modern techniques flood risk evaluation, which can be applied in other flood-affected areas worldwide.

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.

Developed analytic hierarchy process and multi criteria decision support system for wind farm site selection using GIS: A regional-scale application with environmental responsibility

As determined by empirical analysis, renewable energy sources account for less than 1.73 percent of the developing countries energy market. The western region of Iran, or province of Kermanshah, presents significant opportunities for power exports to neighboring country (Iraq). In this research, an appropriate location for wind farms in Western Iran is determined with the assistance of a combined method of Geographic Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) description. Electrical, techno-economic, environmental, and geo-infrastructure aspects, as well as their respective sub-criteria, were subjected to a comprehensive analysis and weighting in this study. The Analytical Hierarchy Process (AHP) was utilized to achieve this result. The aforementioned conclusions were reached through an extensive examination of insightful interviews conducted with esteemed experts in the domain of wind energy. Significant suitability for the potential installation of large-scale wind turbines or wind farms is evident in six critical areas, encompassing more than 20 % of the evaluated region, according to the findings of this paper. Conversely, it was deduced that precisely 80 % of the areas examined were deemed inappropriate for such endeavors. The assessment yielded four locations that were deemed suitable, denoted as A, B, C, and D. The southern, western, and central regions of the province contain these locations. The proposed total capacity is 216 MW, which is determined by the combined surface areas of these regions (19 km2, 55 km2, 64 km2, and 40 km2, respectively). An anticipated reduction of 1,262,471 tons in greenhouse gas emissions is anticipated as a result of the implementation and substitution of the proposed wind farms for the gas turbine power plants that presently predominate in Iran's thermal power plant sector. The method used in this article can be extended to all cases of other faculties to measure the potential of wind farm resources.

Spatial mapping of indoor air quality in a light metro system using the geographic information system method

Abstract It is known that one of the greatest problems of developed countries in the twenty-first century is traffic. For this reason, engineers have searched for alternative solutions to the problem of traffic. One such solution is the construction and utilization of rail systems instead of main roads. From an engineering perspective, rail systems can be divided into three groups: metro, light metro, and tram systems. Light metro systems, which are a form of public transportation, are not directly inside the traffic. Their most important advantages include the fact that they do not release combustion products such as CO, and metro and light metro systems may be considered environmentally friendly based solely on their electricity consumption. In this study, measurements of parameters affecting indoor air quality were made inside light metro cars and in and around light metro stations belonging to the light metro system of the Metropolitan Municipality of Antalya, known as the tourism capital of Turkey. In February and March 2021, when the COVID-19 pandemic was first registered in Turkey, particulate matter (PM), temperature, and relative humidity measurements were made for testing indoor and outside air quality. Moreover, as outside air parameters, outside temperature, outside relative humidity, CO, normalized difference vegetation index, and ultraviolet aerosol index data were obtained from the General Directorate of Meteorology of Turkey. The measurement results were analyzed using the inverse distance weighting method in the geographic information system. Based on the results of the analyses, spatial maps were created for indoor and outside air quality parameters in the light metro system. Using these maps, the effects of passenger density and environmental factors both inside the metro cars and at the metro stations on indoor air quality were identified. In addition, the spread of the SARS-CoV-2 virus in the COVID-19 period was analyzed using spatial maps of the PM0.3 and PM0.5 parameters. It is believed that the results of this study will set an example for further indoor air quality studies worldwide, and this study is unique in that it employed a method that is used particularly in survey and geomatics engineering for analyzing indoor air quality in light metro systems.

Spatial Modelling Analysis for Potential Expansion of Cipanas City Candidate Area as Autonomous City

The establishment of new autonomous city is considered a significant decision and the proposal has been under review in Cipanas for several years. Therefore, this research aimed to address the proposal by conducting spatial modelling analysis for potential expansion of Cipanas as autonomous city, using Geographic Information System (GIS) method. The physical and social factors were analysed, using spatial overlay analysis to determine potential development area. SWOT analysis was also performed for qualitative insights into strengths, weaknesses, opportunities, and threats of the prospective Cipanas area. The results showed that Cipanas had significant potential to become autonomous city, with a particular focus on agriculture and tourism due to the varied topography and predominant natural land use. Through overlay analysis, areas in Pacet, Cipanas, and a small part of Cugenang Sub-districts were identified as potential development zones for the capital city. In general, Cipanas area was found suitable for the development of a major city with an agropolitan concept. Certain areas were considered more appropriate with urban characteristics compared to other areas based on specific criteria. Based on the results, recommendations include infrastructure improvements, economic sector diversification, tourism promotion, and disaster risk reduction activities. GIS spatial analysis facilitated the accurate identification of potential areas, aiding in mapping and pinpointing optimal areas for the establishment of new autonomous city.

Efforts to Increase the Capacity of Sukorejo Village, Semarang City Community in Facing Landslide Disasters Through the Preparation of Evacuation Standard Operating Procedures (SOPs)

This study identified the problem of landslide disasters that often occur in Sukorejo Village, Gunungpati District, Semarang City. Sukorejo village belongs to the high ground movement zone which has a high degree of vulnerability to soil movement. The purpose of the study was to determine efforts to increase the capacity of the community in facing landslide disasters through the preparation of evacuation standard operating procedures (SOPs). The data collection of this study used interview, observation, documentation, and geographic information systems (GIS) methods. Data analysis is carried out with the approach of spatial analysis and qualitative descriptive analysis. The results showed that the preparation of evacuation SOPs is very important to increase the capacity of the community during landslide emergency response. The recommendations given are the need to add an Early Warning System (EWS) tool, install evacuation route signs, and gathering points in landslide-prone areas. In addition, the community also needs to increase awareness and preparedness in the face of possible landslides. This research contributes to improving understanding of landslide disaster mitigation efforts and can be followed up by assessing community capacity and evaluating future evacuation SOPs.

Hazard-mapping and health risk analysis of iron and arsenic contamination in the groundwater of Sylhet district.

This study investigates groundwater contamination by arsenic and iron and its health implications within the Sylhet district in Bangladesh. Utilizing geographic information system (GIS) and inverse distance weighting (IDW) methods, hazard maps have been developed to evaluate contamination risk across various upazilas. The findings show significant arsenic and iron pollution, particularly in the northwestern part of the district. In about 50% of the area, especially in Jaintiapur, Zakiganj, Companiganj, and Kanaighat where arsenic levels surpass 0.05 mg/L which is the standard limit of Bangladesh. Iron levels peak at 13.83 mg/L, severely impacting 45% of the region, especially in Gowainghat, northeastern Jaintiapur, Zakigonj, and Golabganj. The study employs USEPA health risk assessment methods to calculate the hazard quotient (HQ) and hazard index (HI) for both elements via oral and dermal exposure. Results indicate that children face greater noncarcinogenic and carcinogenic risks than adults, with oral HI showing significant risk in Balagonj and Bishwanath. Dermal adsorption pathways exhibit comparatively lower risks. Cancer risk assessments demonstrate high carcinogenic risks from oral arsenic intake in all areas. This comprehensive analysis highlights the urgent need for effective groundwater management and policy interventions in the Sylhet district to mitigate these health risks and ensure safe drinking water.

"Integrated Geospatial Solutions for Enhanced Kukadi River Basin Delineation using Remote Sensing and GIS Techniques"

This study offers an innovative approach to enhance the precision and accuracy of the delineation of the Kukadi River Basin by integrating cutting-edge geospatial technologies, particularly Remote Sensing (RS) and Geographic Information System (GIS) methods. Due to its varied topography and land cover, the Kukadi River Basin play a crucial hydrological entity in the area which presents difficulties for standard delineation techniques. High-resolution satellite imagery is used in the study to provide exact information on land cover in the Kukadi River Basin. The work aims to extract comprehensive land cover data by utilizing spectral analysis and image classification techniques, which are part of RS. In order to improve the delineation of the Basin borders, this data is seamlessly integrated with GIS spatial analytic tools, which also incorporate digital elevation models, slope, and other terrain metrics. The research findings demonstrate the possibility of combining RS and GIS technology to overcome the challenges associated with varying terrains, hence furthering the improvement of Basin delineation approaches. The results provide a useful and dependable paradigm for defining river Basin in a variety of geographical contexts, which is important for water resource management, Environmental Conservation, Land use planning, decision-makers, researchers, and practitioners working on hydrological studies.

Geographic information system-based multi-criteria decision-making analysis for investment assessment of wind-photovoltaic-shared energy storage power stations: a case study of Shanxi Province.

As the center of the development of power industry, wind-photovoltaic (PV)-shared energy storage project is the key tool for achieving energy transformation. This research seeks to construct a feasible model for investment appraisal of wind-PV-shared energy storage power stations by combining geographic information system (GIS) and multi-criteria decision-making (MCDM) method. Firstly, a comprehensive criteria system is established from the perspectives of orography, economy, resources, climate, and society, and the evaluation data is described using probabilistic linguistic term sets (PLTSs). Then, to avoid the weight deviation produced by the single weighting approach, a comprehensive weighting model including the best-worst method (BWM) and entropy weight method is provided to calculate the weights of criteria. Next, expert weights are calculated based on trust analysis. Finally, alternatives are ranked by the improved gained and lost dominance score (GLDS) method. To verify the validity of the model, an empirical investigation is carried out in Shanxi Province. The results show that the economy is the primary factor influencing the investment decision. Among all the projects approved by the government, alternative F4 located in Yanzhuang Town, Yuanping City is the best investment object. Furthermore, to illustrate the stability of the result, triple sensitivity analysis and comparative analysis are conducted in Shanxi Province. This study expands the application scope of GIS and MCDM method by first providing support for government and investors to identify optimal investment targets.

Morphometric Analysis of Dachigam Drainage Basin Using Geo-Spatial Technology (GST)

The examination of morphometric parameters through quantitative analysis proves highly valuable in assessing river basins, prioritizing watersheds for soil and water conservation, and natural resources management. In this study, an in-depth analysis of the Dachigam Catchment has been conducted, focusing on the quantification of various morphometric parameters. The research employs Geographic Information System (GIS) techniques to assess morphometric parameters in the micro-watersheds of the Dachigam Catchment. Linear and areal morphometric parameters were systematically derived and tabulated based on linear and shape characteristics of drainage channels, utilizing GIS and topographical maps (scale 1:50,000). The morphometric analysis conducted in the Dachigam catchment indicates that the basin has an elongated shape, suggesting that peak discharges would generally exhibit a flat profile and take time to rise. The drainage network within the basin is predominantly of the dendritic type, signifying a degree of homogeneity in texture. The slope analysis shows that the Dachigam watershed has a significant amount of steep terrain, ranging from 0 to 74.63%. The majority of the area falls within the 24 to 35% slope range. Examination of the aspect indicates that slopes oriented towards the south and southwest are the most prevalent in the basin. The watershed's mean bifurcation ratio is 1.71. This low ratio suggests that the watershed hasn't experienced significant distortion. In contrast, high bifurcation ratios exceeding 5 typically indicate distorted drainage patterns. The research illustrates how remote sensing and GIS methods can effectively analyze watershed morphometrics. These techniques offer valuable insights for planners and decision-makers involved in watershed-level planning and drainage basin management.

Towards a sustainable city: Deciphering the determinants of restorative park and spatial patterns

Urban parks have been found to provide mental health benefits. Some empirical studies have tested natural features and perceptual measures respectively, announcing their contribution to psychological restoration. However, inconsistent findings were occasionally reported, whereas few attempts have been made to combine both observed and perceptual factors for validation. Little is known about the variation of restorative drivers and their spatial patterns. To address these problems, this study combined public participation geographic information system (PPGIS) and deep learning method to capture visual qualities of landscape features along with several important perceptual measures. A typical urban park in Wuhan, China, was selected for a pilot study, and 1560 crowdsourced on-site images were collected, with thematic and geographic information being integrated. A series of statistical models, e.g., OLS, QRM, and MGWR, were employed successively for validation. The results showed that landscape preference, place attachment, greenery and water were validated as the global explanatory factors to estimate the conditional mean of psychological restoration. The variation of influential effects of these factors were detected at different restoration levels. There exist spatial heterogeneity for these influential factors on restorative effects. Findings provided new knowledge on a deeper understanding of the subtlety of restoration drivers and their spatial patterns. The findings offered useful insights and guidance for urban planners in creating high-quality green parks with restorative values.

Equity of travel to access surgery and radiation therapy for lung cancer in New Zealand

PurposeCentralisation of lung cancer treatment can improve outcomes, but may result in differential access to care for those who do not reside within treatment centres.MethodsWe used national-level cancer registration and health care access data and used Geographic Information Systems (GIS) methods to determine the distance and time to access first relevant surgery and first radiation therapy among all New Zealanders diagnosed with lung cancer (2007–2019; N = 27,869), and compared these outcomes between ethnic groups. We also explored the likelihood of being treated at a high-, medium-, or low-volume hospital. Analysis involved both descriptive and adjusted logistic regression modelling.ResultsWe found that Māori tend to need to travel further (with longer travel times) to access both surgery (median travel distance: Māori 57 km, European 34 km) and radiation therapy (Māori 75 km, European 35 km) than Europeans. Māori have greater odds of living more than 200 km away from both surgery (adjusted odds ratio [aOR] 1.83, 95% CI 1.49–2.25) and radiation therapy (aOR 1.41, 95% CI 1.25–1.60).ConclusionsCentralisation of care may often improve treatment outcomes, but it also makes accessing treatment even more difficult for populations who are more likely to live rurally and in deprivation, such as Māori.

Assessing the Correlation Between Basic Sanitation and Diarrhea Prevalence in Bulurejo Village, Gresilk: A Geographic Information System (GIS) Approach

In 2022, the number of diarrhea cases increased to 958 sufferers, with the highest incidence occurring in Bulurejo village. Physically, the sources of clean water still exhibit discoloration and unpleasant odor. The latrine construction lacks a roof, and the walls are made of cloth. The construction of waste bins lacks covers, and the wastewater disposal facilities (SPAL) are open. This research aims to determine the correlation between basic sanitation and the prevalence of diarrhea using the Geographic Information System (GIS) method. The study is descriptive-analytical through observations and a GIS approach in the form of a map. From the observations, bivariate and univariate analyses were conducted using the chi-square test. The results show that basic household sanitation is related to the prevalence of diarrhea in Bulurejo. Clean water facilities, with a p-value of 0.014, indicate a significant relationship. Toilet facilities, with a p-value of 0.347, show no significant relationship. SPAL facilities, with a p-value of 0.009, indicate a significant relationship. Waste disposal facilities, with a p-value of 0.029, indicate a significant relationship. After analysis, the results were represented in the form of a map. The Geographic Information System (GIS) approach was utilized to develop more effective mapping strategies for the improvement of sanitation and diarrhea control in the area. These findings indicate the necessity for enhancing basic sanitation facilities and implementing programs at community health centers to reduce diarrhea cases in Bulurejo.

Abstract TMP20: Mapping the Expansion of the Minnesota Stroke System of Care

Objectives: Stroke is the fifth leading cause of death in Minnesota (MN) and in the United States. The state of MN a has a unique geographical layout with many healthcare facilities located in rural areas. In 2013 legislation was passed authorizing the Minnesota Department of Health to designate hospitals as Acute Stroke Ready Hospitals, Primary Stroke Centers, and Comprehensive Stroke Centers. When a hospital joins the MN Stroke System they maintain vital infrastructure, expertise, and care processes to provide high quality stroke care in accordance with evidence-based guidelines. We used geographic information systems (GIS) methods to visualize the growth and expansion of the Minnesota Stroke System and quantify its reach to Minnesotans across the state over a 10-year period. Methods: Using the Network Analyst extension of ESRI ArcGIS Desktop 10.8.2, 30- and 60- minute drive time service areas were calculated around each designated hospital in 2013, 2017 and 2023. Census block groups were identified where the mean center of population fell within the 30-minute drive time areas and the populations of those block groups were summed. A percentage was calculated using the total Minnesota population as the denominator. Results: In 2013, only 66% of Minnesota’s population lived within 30 minutes of a designated stroke center and 80% lived within a 60-minute drive time. Stroke designated hospitals (19) were largely concentrated in metropolitan areas, leaving many rural Minnesotans without ready access to stroke centers. After the first cycle in 2017, or three-year period post statute, drive time status increased to 90% of the population living within 30 minutes of a designated stroke system hospital and 98% living within a 60- minute drive time. As of 2023, 94% of Minnesotans now live within a 30-minute drive of a designated Stroke System Hospital and 99% live within a 60-minute drive time. Conclusions: Stroke statute was the catalyst for improving stroke care access in MN. The voluntary system of care expanded rapidly from 19 initial hospitals to 119 over a 10-year period. This progress means more than 1.9 million additional Minnesotans now have better access to emergency stroke care.

Assessment of the Impact of Population Reduction on Grasslands with a New “Tool”: A Case Study on the “Mountainous Banat” Area of Romania

The landscapes and, implicitly, the surfaces of secondary grasslands in the mountain areas have been intensively modified and transformed by humans. In this context, this paper analyses the spatial and temporal changes of grassland surfaces following the impact of human population reduction. Thus, the study proposes the implementation of the Grassland Anthropic Impact Index (GAII) as a “measurement tool” to functionally link the two components, grassland surface and human population. The spatiotemporal analyses are based on Corine Land Cover data and demographic data, processed via Geographic Information Systems (GIS) methods and the Land Change Modeler (LCM) tool. The research shows that over a period of 28 years, the population, which was continuously decreasing, caused a series of transformations to the grasslands over an area of 33343 ha. The influence of the reduction in the number of inhabitants was also demonstrated by the direction of the changes produced in the grassland surfaces: in the better populated areas, the grasslands expanded over lands with other uses, and in the sparsely populated areas, they were abandoned. GAII values generally increase with the decrease of the population in the target area, meaning that for an inhabitant (potential user) a greater grassland surface is reported, resulting in a greater responsibility for the management of this resource on a space and time scale. Following the evaluation of the trend of the last 28 years, it was observed that the depopulation of mountain areas can be seen as a threat to grassland ecosystems, either through the transition to other categories of use, or through abandonment. The implications of these phenomena are much broader: they produce chain reactions and affect other components of the regional geosystem.

SPATIAL CRITERIA FOR INDUSTRIAL AREA: SUSTAINABLE DEVELOPMENT STRATEGY IN SANGIRAN CULTURAL HERITAGE ZONE, GONDANGREJO DISTRICT

<span>Gondangrejo District is a suburb (peri urban) of Surakarta City with significant industrial growth in Karanganyar Regency. The driving factor of the development of the Gondangrejo District is the relocation of urban activities in Surakarta City. Gondangrejo District is an area of deconcentration of industrial activities because of its location directly adjacent to Surakarta City. A comprehensive site selection analysis is essential for industrial siting that supports sustainable builders. We select the optimal site for the industrial area by considering various criteria and inhibiting factors using GIS-based MCDA. Most suitable for industrial sites with GIS and AHP to build industries in The Gondangrejo District. This study aims to determine the most optimal industrial area by considering various appropriate criteria using multi-criteria decision analysis (MCDA) and geographic information system (GIS) methods. Based on the criteria used, namely proximity to roads, distance from rivers, distance from settlements, physiology, and population density with the same weight of 20%, a suitable location for the industrial area with a linear pattern or extending from east to west in the Gondangrejo District. Based on the same criteria with different weights from the results of the AHP analysis, suitable locations for industrial sites are Dayu Village, Rejosari Village, and Wonosari Village, which form a centering pattern. The study results found that the optimal industrial areas in Gondangrejo District are Dayu Village, Rejosari, and Wonosari. The results of the suitability of this industrial area can be used by decision-makers in the development planning of the Gondangrejo District.</span>

Identifying spatiotemporal trends of SARS-CoV-2 RNA in wastewater: from the perspective of upstream and downstream wastewater-based epidemiology (WBE).

Recently, many efforts have been made to address the rapid spread of newly identified COVID-19 virus variants. Wastewater-based epidemiology (WBE) is considered a potential early warning tool for identifying the rapid spread of this virus. This study investigated the occurrence of SARS-CoV-2 in eight wastewater treatment plants (WWTPs) and their sewerage systems which serve most of the population in Taoyuan City, Taiwan. Across the entire study period, the wastewater viral concentrations were correlated with the number of COVID-19 cases in each WWTP (Spearman's r = 0.23-0.76). In addition, it is confirmed that several treatment technologies could effectively eliminate the virus RNA from WWTP influent (> 90%). On the other hand, further results revealed that an inverse distance weighted (IDW) interpolation and hotspot model combined with the geographic information system (GIS) method could be applied to analyze the spatiotemporal variations of SARS-CoV-2 in wastewater from the sewer system. In addition, socio-economic factors, namely, population density, land use, and income tax were successfully identified as the potential drivers which substantially affected the onset of the COVID-19 outbreak in Taiwan. Finally, the data obtained from this study can provide a powerful tool in public health decision-making not only in response to the current epidemic situation but also to other epidemic issues in the future.

Mapping the vulnerability of coastal areas of the Eastern region of Morocco (ERM) to oil spills risk

The objective of this study is to generate maps of coastal areas based on the Environmental Sensitivity Index (ESI) to assess oil spills risk. These maps have become a crucial tool for operational responders. ESI is a tool developed to evaluate the sensitivity of coastal environments and provides a method to assess the impact of oil spills systematically IPIECA. IMO. IOGP, (Juillet 2012). The establishment of the future Nador West Med oil transshipment port is expected to make maritime transport of hydrocarbons a significant source of pollution along the Eastern Region of Morocco (ERM), given the substantial traffic in these products. Through satellite imagery, it has been possible to observe and recognize the different geomorphological formations along the coast. In order to map these sites based on ESI index and describe their characteristics, it is essential to utilize Geographic Information System (GIS) and multi-criteria analysis methods to manage all relevant information. The produced maps provide valuable support to stakeholders in coastal management of oil spills response. Furthermore, ESI is used for coastal area management and preservation, particularly in identifying ecologically valuable regions. There are plans to implement a real-time alarm system to visualize coastal areas sensitivity in terms of the ESI index, guiding pollution control in the coastal areas.

Assessment of Morphometric and Hypsometric Analysis of the Ruste Basin Using Remote Sensing and Geographical Information System Techniques

A basin’s characteristics and features need to be comprehended completely by conducting morphometric analysis, such as evaluating the basin’s size, form, and surface features, to estimate floods and erosion rates properly. The main objective of this investigation is to evaluate morphometric measures and hypsometric analysis of Erbil’s Ruste Basin employing remote sensing and geographical information system methods. To investigate the significant tributaries of the selected area, the hydrology tool within the Spatial Analysis Tools of ArcGIS, version 10.7, was utilized to define the basin boundaries, map the drainage networks, and obtain topographic data. The findings of the linear morphometric parameters revealed that the logarithmic relationship between stream orders and stream numbers was negative. The difference in stream order and number seen in the watershed is due to topography and bedrock influence. The results also showed a negative correlation between stream length and stream order, and a coefficient of determination of 0.972, which indicates that the basin is made of low-permeability formation and subsoil materials. Considering the areal morphometric parameters, the circularity ratio, elongation ratio, and form factor are 0.594, 0.853 and 0.572, respectively, suggested a semi-circular shape. A drainage density value of 2.259 km-1 showed that the Ruste Basin is a basin with steeply to very steeply sloping hilly terrain with varying plant covering. Furthermore, the Ruste Basin has high relief and slope with a relief ratio of 0.151 and basin relief of 2.576 km, both of which imply that it has a steep slope with high erosive force, limited infiltration, and a high runoff rate. Ruste Basin’s ruggedness number was 5.819, indicating that it has badlands topography. The average hypsometric integral was 0.467, denoting a mature basin featuring S-shaped hypsometric curves. In conclusion, the results showed that analysis of morphometric parameters and hypsometric integral and curve provides us with a notion to basin characterization and guidance to making appropriate decisions to establish effective actions to sustainable water and soil conservation and natural resources management through applying water harvesting methods, check dams, and bench terraces.

Suitability analysis of PV solar power plant sites in Gandaki province: Application of GIS and Remote sensing

The escalating global demand for energy has triggered a shift towards cleaner alternatives due to mounting environmental concerns. Emerging as a viable substitute, solar power has gained prominence as fossil fuels' adverse impact becomes evident. Historically reliant on hydropower, Nepal is exploring alternative energy sources to mitigate seasonal output variations. Despite abundant renewable resources like biomass, wind, and solar energy, Nepal's energy sector faces funding and technical expertise challenges. Solar energy presents significant promise as a primary renewable source in Nepal, boasting ample sunlight due to its location. However, the current solar capacity remains limited at around 54.6 MW, comprising less than 2.5% of the total installed capacity. The critical factor is the identification of suitable sites for solar power plants. Geographical Information System (GIS) and Multi-Criteria Decision-Making (MCDM) methods have been employed for suitability analysis. This study employs the Analytic Hierarchy Process (AHP), a robust MCDM technique, to assess site suitability. The research is carried out in the Gandaki province, Nepal, encompassing the Himalayan, Hilly, and Terai regions. Criteria like solar radiation, slope, aspect, land use/land cover, proximity to roads, and substations are considered. These criteria are reclassified into suitability categories based on expert opinions and guidelines. The results indicate areas highly suitable for solar power generation, covering 12.40 km2 (5.64% of the study area), followed by regions least suitable, spanning 7681 km2 (34.93% of the province's area). This research contributes to the effective deployment of solar power by identifying optimal locations for solar power plant construction, thus advancing Nepal's renewable energy goals.