Geographic Information System Techniques Research Articles

Geospatial Analysis of Wind Energy Siting Suitability in the East African Community

Site investigation is essential for developing and constructing a dependable and effective wind engineering project. Also, the kinetic energy of moving air, used to drive a wind turbine, produces electricity. Having seen the shortage of previous studies on wind energy sites’ suitability across Africa and having read about the abundance of untapped wind energy resources in the East African region, this paper used Geographical Information System (GIS), multi-criteria, and Analytic Hierarchy techniques to provide a geospatial analysis of wind energy technology siting suitability in Eastern African Community Countries. Different data were acquired and processed from numerous open-access databases (Global Wind atlas, Regional Center for Mapping of Resources for Development (RCMRD), African Geoportal, East African community website, and Energy data Info.org). The results reveal Kenya has large parts of its land areas highly appropriate for wind energy siting (15.26%) and 1.55% of its land classified as unsuitable for wind energy generation. The rates of suitability and unsuitability were respectively 26.57% and 4.87% for Burundi, 20.6% and 10.21% for Rwanda, 20.39% and 10.44% for Tanzania, and 4.65% and 27.15% for South Sudan. The findings also show that East Africa exhibits moderate levels of wind energy siting suitability, with an estimated average of around 37.27% of its land area moderately suitable for wind energy technology installation, covering thousands of square kilometers. The study is advantageous to academia and industry-related personnel engaged in renewable energy-related activities in other African countries with similar topographies.

Monitoring air quality of Sharkia Governorate using remote sensing

Due to Sharkia population’s rapid growth, the crises of atmospheric pollutants are causing significant concern. These circumstances have positive and negative impacts on both environment and climate. This research aims to investigate and evaluate changes in land and air characteristics of the governorate using remotely sensed data from several satellites (Landsat, Aqua, Terra, and Sentinel-5P) in conjunction with geographic information system (GIS) techniques. Three multitemporal Landsat images were acquired in July 2002, 2012, and 2022, to monitor land use/land cover (LULC) changes during the past 20 years. In addition, aerosol optical depth (AOD) data were obtained daily over 2022, and Particulate Matter (PM2.5) was calculated and then averaged seasonally. Sentinel-5P was utilized for CO, NO2, and SO2 retrievals. Results showed that the governorate was continuously subjected to spatiotemporal changes in LULC during the whole study period. It was mainly occupied by vegetation with a total area of 3711.64, 3851.05, and 3794.59 km2 in 2002, 2012, and 2022, respectively. Seasonal means of PM2.5 followed this order: spring (77.59 µg/m3) > summer (50.76 µg/m3) > winter (49.29 µg/m3) > autumn (42.71 µg/m3). However, the winter season recorded the highest mean values for all gases, CO (946.58 µg/m3), NO2 (9.70 µg/m3), and SO2 (13.07 µg/m3). It was concluded that the southern region of the governorate is more vulnerable to environmental stresses, which can reduce biodiversity and ultimately affect the study area’s climate. In order to manage fragile ecosystems sustainably, this study recommends the creation of efficient land and air management information systems and regulations.

Land Cover Change using GIS and RS Techniques of the Padma River Floodplain in the Three Adjacent Districts in Bangladesh

Bangladesh is a nation characterized by its reliance on river systems for various aspects of its socio-economic and geographical features. The region experiences a significant number of natural disasters every year as a result of the existence of the river. The region undergoes regular riverbank erosion as a result of the continuous changing of river channels. This study aimed to assess the changing of the Padma River and its impact on land use and land cover in the three adjacent districts of Munshiganj, Madaripur, and Shariatpur. Geographic Information System (GIS) along with remote sensing (RS) techniques were employed to analyze data collected between 1988 and 2023. Best results in detecting land-use/land-cover type and identifying erosional impact were achieved using K-means cluster unsupervised image classification. The accuracy of image preprocessing and classification was separately evaluated using the kappa coefficient. For the years 1988, 1993, 1998, 2003, 2008, 2013, 2017, and 2023, the findings indicated an overall accuracy of 86.36%, 83.32%, 87.1%, 85.43%, 87.3%, 87.92%, 88.42%, 90.06% and a kappa coefficient of 83.02%, 83.32%, 86.66%,85.37%, 87.78%, 87.29%, 87.91%, 86.59% respectively. Arable land accounted for 56.40 percent of the overall accreted land area (26340.06 ha), whereas cropland accounted for just 5.99 percent (2798.10 ha) based on long-term river channel migration results. In 35 years, arable land (23661.21 ha) suffered the most erosion (55.42%), followed by inland water (3351.53 ha), which suffered the least (7.15%). The implementation of an embankment inside the research area is proposed as a potentially efficacious strategy for mitigating riverbank erosion in this particular region. The government may implement long-term rehabilitation projects to support individuals who have been displaced by bank erosion and are now landless. Jagannath University Journal of Science, Volume 10, Number I, Jun. 2023, pp. 43-54

An Assessment of Flood Risk in the Gambia: A Data-Driven Approach to Flood Risk Management and Prevention

Coastal African countries, including Gambia, are increasingly vulnerable to a range of natural disasters, notably flooding, which poses significant challenges to sustainable development and safety. This study set out to comprehensively assess the flood risk in Gambia using a data-driven approach, aiming to enhance flood risk management and prevention strategies. Utilizing geospatial data and Geographic Information System (GIS) techniques, the research involved mapping and categorizing flood risk zones across various regions. The analysis focused on the identification and categorization of flood risk zones, assessment of the vulnerability of key infrastructures, health facilities, road networks, and settlements to flooding. The findings reveal that a total of 2,721 square kilometers of land is at flood risk categorized as either high or very high. This constitutes 26.89 percent of the country’s of terrestrial area. A total of 25 critical health infrastructure were in areas of this high flood risk categorization – ranging from general hospitals to clinics. Up to 24.5% of the nation's road network was found to be in this flood risk zone. Of the country’s five administrative regions, the West Coast Region which is home to most of its urban centers was most at risk of flooding. Here, of the 353 settlements in this region, 172 of them fell under the high to very high-risk flood zone categorization, constituting 48.7% of the settlements at a significant level of flood vulnerability. This study enhances the understanding of flood hazards in Gambia, providing essential perspectives for decision makers, city planners, and emergency response teams. This research highlights the need for using data-driven methods in identifying and managing environmental risks. It also advocates for the adoption of long-term strategic planning, infrastructure enhancements, and community-based activities to reduce the effects of floods.

Flood Risk Vulnerability Detection based on the Developing Topographic Wetness Index Tool in Geographic Information System

Finding vulnerability to flooding locations is a crucial part of sensible urban development and effective natural disaster management. Globally, there has been a noticeable rise in the frequency of floods in recent years, which affects human habitation and several economic sectors. This calls for the employment of various prevention measures, wherein the assessment of vulnerability to flooding is crucial. The main objective of the present study is to introduce the best procedure for the identification of flood risk vulnerability detection using geographical information systems techniques and decision-making, based on a comparative evaluation of various scenarios. In this context, The current study will develop a Topographic Wetness Index (TWI) tool for the detection of these risks which can deal with the stream orders, calculate the length of the valley, and then show the outputs by thematic maps. The procedure with the developed adaptive tool has been applied to identify Flood Risk Vulnerability in Erbil city and some surrounding areas. The results of this paper indicated the existence of different levels of the TWI, which were classified into five classes. The procedure of this study has an advantage over other traditional methods since it takes into account mainly statistics data that are linked to the TWI which can be easily customized in detecting risk Vulnerability.

Integrated Analytical Hierarchy Process (AHP) and GIS techniques based Soil Erosion Susceptibility Mapping in Chite Watershed, Mizoram, India

Soil erosion is a significant form of land degradation that profoundly affects agricultural and ecosystem sustainability. The present study aimed at addressing this issue by developing precise and feasible erosion susceptibility map in Chite watershed, India, using integrated approach combining the Analytical Hierarchy Process (AHP) with Geographic Information System (GIS). To evaluate erosion susceptibility conditions, multiple causative factors including elevation, slope, drainage density, distance from streams, land use / land cover, rainfall intensity, normalized difference vegetation index, lithology, soil texture and lineament density were selected. These factors and their sub-classes were prioritized by AHP method based on their relative influence on soil erosion. Subsequently, the calculated AHP weights were utilized for generating a spatial dataset of soil erosion susceptibility through GIS technology. Accuracy assessment by the area under the ROC curve (AUC) reveals considerably acceptable results for the predicted map when compared to erosion inventory, producing an accuracy level of 0.812 (81%) and 0.922 (92%) for erosion and non-erosion points respectively. Thus, the present study manifests the efficiency of integrating the AHP and GIS techniques for erosion susceptibility mapping in the Chite watershed and this may serve as a valuable tool for sustainable land management and erosion control.

Soil fertility mapping of a cultivated area in Resunga Municipality, Gulmi, Nepal.

Soil fertility maps are crucial for sustainable soil and land use management system for predicting soil health status. However, many regions of Nepal lack updated or reliable soil fertility maps. This study aimed to develop the soil fertility map of agricultural areas in Resunga Municipality, Gulmi district of Nepal using the geographical information system (GIS) technique. A total of 57 composite geo-referenced soil samples from the depth (0-20 cm) were taken from the agricultural land of an area of 52 km2. Soil samples were analyzed for their texture, pH, organic matter, total nitrogen, available phosphorous, available potassium, available boron, and available zinc. These parameters were modelled to develop a soil quality index (SQI). Using the kriging tool, obtained parameters were interpolated and digital maps were produced along with soil quality and nutrient indices. The result showed that the study area lies within the fair (0.4 to 0.6) and good (0.6 to 0.8) range of SQI representing 96% and 3% respectively. Soil organic matter and nitrogen showed moderate variability exhibiting a low status in 95% and 86% of the total study area. Phosphorous and potassium showed medium status in 88% and 75% of the study area, respectively. Zinc was low and boron status was medium in most of the area. To maintain soil fertility is by improving the rate of exogenous application of fertilizers and manures. The application of micronutrients like boron and zinc is highly recommended in the study area along with organic manures. The soil fertility map can be used as a baseline for soil and land use management in Resunga Municipality. We recommend further studies to validate the map and assess the factors affecting soil fertility in this region. Soil fertility maps provide researchers, farmers, students, and land use planners with easier decision-making tools for sustainable crop production systems and land use management systems.

Water transportation planning in connection with extreme weather conditions; case study – Port of Novi Sad, Serbia

Abstract The Danube has a length of 588 km in the Republic of Serbia. The water transport on this river is underused. The hazardous events have a great impact on the traffic on this river, and the understanding of these events is of great importance. This study focuses on hazardous events on the Danube with the main focus on the port of Novi. The hazardous events used in this study are extreme air temperatures, devastating winds, drought, and heavy precipitation. The hazardous events were represented using geographic information systems (GIS), geostatistics, and numerical methods. The potential of the river transport network and the port capacity were analyzed and compared with the hazardous events of the last 30 years. The results showed that three areas of the port are of great importance for port security, and two areas are extremely affected by hazardous events. The distance of the port of Novi Sad from heavy precipitation events is 6.8 km in the southwestern direction. The periods of extremely low precipitation (climatic drought) were in 1994, 2008, 2012, 2015, 2019, and 2021. Extreme average maximum temperatures were in 1995, 2008, 2010, 2013, 2015, and 2019. On the other hand, minimum average temperatures were in 1994, 1996, 1998, 1999, 2017, and 2018, and the strongest winds were in 1995, 1998, 2003, 2009, 2012, and 2014. The methods and techniques of GIS, used in this research, have confirmed new potential geographical positions of the port that can be better adapted to future climate changes. Another main objective of this research is to recommend better spatial planning and construction of new green corridors.

Quantitative analysis of hydropower potential in the upper Beas basin using geographical information system and MIKE 11 Nedbor Afrstromnings Model (NAM)

AbstractThe present study aims to identify potential locations for small‐scale hydroelectric power (HEP) stations in hilly regions for the purpose of generating renewable energy. A rainfall‐runoff (R‐R) model of the Beas River catchment was established using the MIKE 11 NAM to estimate the available discharge. The model was calibrated and validated over the period of June‐2015–May‐2018 and June‐2018–May‐2020, respectively, using daily observed discharge data at the Pandoh Dam site. The model exhibited good performance with a coefficient of determination (R2) of 0.82 during calibration and 0.70 during validation and a water balance of −0.01% and −18%, respectively. However, Lmax, CK1, CK2 and CQOF are found most sensitive parameters during the calibration. Further, thirteen major streams of order five or higher were selected for the assessment of hydropower potential, resulting in the identification of 131 potential run‐of‐river (ROR) hydropower sites. The hydropower potential at two proposed sites, Bhang SHEP (9 MW) and Raison SHEP (18 MW), was estimated to be 11 and 15 MW, respectively, using 90% dependable flow. The results demonstrate the effectiveness of using Digital Elevation Model (DEM) and Geographic Information System (GIS) techniques for determining hydropower potential in ungauged basins in the Himalayas.

Analysis of land‐based parameters and development of multi‐criteria decision support system for demarcation of potential aquaculture sites in Nagapattinam, Tamil Nadu, India

AbstractThe aim of the present study was to develop a multi‐criteria decision support system to find out possible aquaculture sites available in Nagapattinam district of Tamil Nadu, India. This study focuses on identifying possible aquaculture sites available in Nagapattinam district using remote sensing and GIS approaches. A geographical model has been developed to choose the probable aquaculture sites. The remote sensing and geographic information system techniques were applied to study the decisive parameters that play a vital role in the site suitability for aquaculture purposes. The chosen decisive parameters viz., normalized difference vegetation index, digital elevation model, soil type, normalized difference water index, land use land cover area and land surface temperature were subjected to the development of decision support system. Moreover, four different multi‐criteria decision support techniques viz., weighted overlay, analytical hierarchy process, fuzzy classified analytical hierarchy process and fuzzy classified weighted overlay were applied in the present study. The results obtained from the study rendered that the weighted overlay and the analytical hierarchy process outperforms the fuzzy classified models. The suitability ratio of analytical hierarchy process and weighted overlay methods were found to be 12.7 and 12.4 respectively. A total of 25 locations were selected and mapped in the Nagapattinam region and their accuracy was checked. The analytical hierarchy process results were obtained with an accuracy of 84%. Hence, the analytical hierarchy process provided better results than the weighted overlay technique. The study rendered that the area of 7.22% is highly suitable for aquaculture. These findings are essential for the development of sustainable aquaculture, assisting stakeholders in selecting suitable aquaculture sites that maximize productivity while minimizing environmental degradation.

An integrated approach based on HFE-D, GIS techniques, GQISWI, and statistical analysis for the assessment of potential seawater intrusion: coastal multilayered aquifer of Ghaemshahr-Juybar (Mazandaran, Iran).

The overexploitation of coastal aquifers is one of the important reasons for the salinity of groundwater due to seawater intrusion (SWI). This study assesses the hydrochemical changes of the Ghaemshahr-Juybar (GH.-J.) plain. For this purpose, specific statistical methods, modified Piper diagram groundwater quality indicators ([Formula: see text] and [Formula: see text]), groundwater quality index specific to seawater intrusion ([Formula: see text]), and hydrochemical facies evolution diagram (HFE-D) along with GIS (Geographic Information System) techniques were applied to identify the spatiotemporal changes of salinity in coastal multilayer alluvial aquifer. The results show that the chemical composition in the GH.-J. aquifer is basically controlled by three main factors: (1) Caspian SWI and fossil saltwater penetration from an underlying layer, (2) reverse cation exchange process, and (3) feeding by domestic sewage, agricultural activities, and use of nitrate chemical fertilizers. The investigation of the hydrogeochemical facies evolution process shows that due to the reduction of extraction from wells, saltwater infiltration has significantly decreased. Therefore, according to the geological and lithological conditions of the aquifer and exposure to seawater, it is possible to prevent the entry of saltwater from the confined aquifer into the unconfined aquifer and the saltwater intrusion by developing well optimal operation policies in order to control withdrawal from semi-deep wells and the elimination of deep wells. This practical approach to managing the salinity of coastal aquifers is suitable for the allocating groundwater resources and for use in the development of aquifer simulation models.

Modeling climate change adaptation for sustainable coastal zones using GIS and AHP

The world is currently confronting one of its biggest environmental challenges: combating climate change. Coastal zones are one of the areas thought to be most sensitive to current and future climate change threats. The paper integrates Remote Sensing (RS), Geographic Information System (GIS) techniques, and Multi-Criteria Decision Analysis (MCDA) to detect vulnerable areas from climate change impacts in coastal zones in order to recommend adaptation systems in new coastal zones that can withstand various climatic changes. The proposed decision-making framework was developed in three phases: 1) climate data collection and processing; 2) Coastal Climate Impact Assessment (CCIA) model development; and 3) implementation and adaptation system selection. The climate data collection and processing phase involves determining the most significant climate change parameters and their indicators that affect coastal zone stability, extracting climatic data indicators from different climate database sources, and prioritizing the selected indicators. The indicators’ weights were estimated using the Analytical Hierarchy Process (AHP) through a questionnaire survey shared with experts in climate change impacts. A CCIA model development phase involves the formulation of the proposed model using GIS technique to discover the vulnerable areas according to the most dominant impact. The implementation and adaptation system selection phase involves the application of the framework to Al-Alamein New City in Egypt. A sensitivity analysis was conducted to measure the behavior of several climate change parameters to identify the most critical parameter for climate change in Al-Alamein New City. The results showed that the geology of the region is the most crucial component influenced by climate change. It is capable of producing a very sensitive area in the coastal zone while also taking other factors into account. When creating new urban neighborhoods, the erosion of the shoreline is the least important factor to consider. This is because coastal deterioration is caused by both the influence of metrological data on the region and the impact of human activity. Shoreline deterioration will be reduced if climate conditions are maintained while limiting the impact of human activities. To adapt to the long-term effects of climate change on coastal zones, a combination of soft and hard protection systems should be considered.

Identifying land use land cover dynamics using machine learning method and GIS approach in Karaivetti, Tamil Nadu

<p>An important analytical tool for tracking, mapping, and quantifying changes in land use and land cover (LULC) across time serves as the use of machine learning techniques. The environment and human activities both have the potential to change how land is used and covered. Classifying LULC types at different spatial scales has been effectively achieved by models like classification and regression trees (CART), support vector machines (SVM), extreme gradient boosting (XGBoost), and random forests (RF). To prepare images from Landsat before sending and analysis for an aspect of our research, we employed the Google Earth Engine. High-resolution imagery from Google Earth images were used to assess each kind of method and field data collection. Utilizing Geographic Information System (GIS) techniques, LULC fluctuations between 2015 and 2020 were assessed. According to our results, XGBoost, SVM, and CART models proved superior by the RF model regarding categorization precision. Considering the data, we collected between 2015 and 2020, from 11.57 hectares (1.74%) in 2015 to 184.19 hectares (27.65%) in 2020, the barren land experienced the greatest variation, that made an immense effect. Utilizing the support of satellite imagery from the Karaivetti Wetland, our work combines novel GIS techniques and machine learning strategies to LULC monitoring. The created land cover maps provide a vital benchmark that will be useful to authorities in formulating policies, managing for sustainability, and keeping track of degradation.</p>

Spatio-temporal Landuse/Landcover Dynamics in the Coastal Areas of Limbe and Douala IV Municipalities and Implications on Wetland Regulating Ecosystem Services

Globally, wetlands are ecological hot spots and as a result they supply a plethora provisioning, regulating, supporting and cultural services. Despite their functions, wetlands continue to degrade arising from urban developments (population growth and housing developments, road infrastructural developments, urban agricultures and usage of wetlands as dumpsites). These activities operate via land use/land cover changes at different scales in different areas depending on technology and needs of the population. This paper describes the implications of spatio-temporal land use/ land cover (LULC) dynamics in the Limbe I and III Municipality (L1&3Ms) and Douala IV Municipality (D4M) coastal areas from 1986 to 2022 on wetland ecosystem services. This research made use of Geographic Information System (GIS) technique in describing the land use/cover changes in the study areas. Primary data was obtained through field observations, questionnaires and ground truthing aim at confirming the observations on downloaded satellite imageries. Four Satellite images of different years (1986, 1999, 2013 and 2022) were downloaded from the United State Geologic Survey (USGS) Earth Explorer. Images were imported into Erdas Imagine, 2014 where preprocessing was done and Supervised Classification was adopted for the processing of the image to generate a raster format depicting the designed land cover/land uses; especially the wetlands which constituted one of the themes. Maps were generated to show changes in land use/cover which were transposed into tables and figures to show the trends in magnitude of changes, percentage of change and the rate of change. Within 36 years (1986-2022) built-up increased by 0.75km2 (0.36%) and 1.63km2 (0.45%) while wetlands retreated by -0.2km2 (-.96%) and -0.48km2 (-0.14%) in L1&3M and D4M respectively. Annually, wetlands decreased by - 97.04km2 and -191.54km2 while settlements/infrastructures increased by 294.33km2 and 644.46km2 over the same 36 year periods in L1&3Ms and D4M respectively. Base on wetland regulating services, changes in LULC has exposes neighbourhoods in L1&3Ms to flood vulnerability comprising the vulnerable, less vulnerable, least vulnerable and most vulnerable areas as opposed to two categories of neighbourhoods in D4M (most vulnerable neighbourhood’s and the less vulnerable neighbourhoods). Information on changes in land use-land cover is crucial in delineating impacted areas, understand the type of changes, their spatial patterns and the need for formulating proper urban planning and environmental preservation policies as well as updating these policies with time. GIS analysis of 1986, 1999, 2013, and 2022, indicated that, there have been significant modifications in observed LULC classes (forest cover, farmland and built-up land uses) over L1&3Ms and D4M.

Determination of Groundwater Potential Areas Using Remote Sensing (RS) and GIS Techniques in Mubi North Local Government Area, Adamawa State, North Eastern Nigeria.

This study utilizes Remote Sensing (RS) and Geographic Information Systems (GIS) techniques to determine groundwater potential areas in Mubi North Local Government Area, Adamawa State, Nigeria. The research aim to provide insights for water resource management and sustainable development. Data collected includes Landsat imagery, Digital Elevation Model (DEM), soil data, and vector layers. Preprocessing involved data format conversion, spatial reference alignment, and resolution standardization for compatibility and consistency. Spatial analysis extracted topographic parameters from the DEM and supervised classified Landsat imagery for Land Use/Land Cover (LULC) maps. Six factors, Drainage density, Slope, Soil, Elevation, LULC, and Aspect, were reclassified into low, average, and high groundwater potential indexes. ArcGIS overlay analysis integrated the factors, prioritizing Drainage density, Slope, Soil, and Elevation, to create a composite groundwater potential index. The index was calibrated and classified into five categories: Very Low, Low, Average, Marginally High, and High potential areas. Results reveal diverse groundwater potentials. Very Low areas cover 17,168.23 hectares, Average areas cover 18,534.86 hectares, Marginally High areas cover 19,362.08 hectares, Low areas cover 13,838.41 hectares, and High areas cover 12,757.44 hectares. Spatial distribution shows High potential in settlements like Sabon Gari and Bukkaji, while Very Low potential is found in Wuro Alhaji and Venda. This study contributes to water resource management and sustainable development. Findings aid targeted strategies, benefiting socio-economic development. The research enhances knowledge and informs decision-making for water resource management, fostering development and improving livelihoods in Mubi North LGA.

Exploring mental health literacy among prospective university students using GIS techniques in Bangladesh: an exploratory study.

Prospective university students experience substantial academic stressors and psychological vulnerabilities, yet their mental health literacy (MHL) remains inadequately explored. This study investigates four dimensions of MHL - help-seeking behaviors, stigma, knowledge about mental health and understanding of mental illnesses. Besides, Geographic Information System (GIS) techniques are employed to analyze spatial disparities in MHL, which is the first in the context of MHL research. A total of 1,485 students were assessed for sociodemographic characteristics, admission-related variables, health behaviors and family histories of mental health issues. Data were analyzed using SPSS and ArcGIS software. Multivariable linear regression analyses unveiled predictors of the MHL dimensions, with gender, family income, admission test performance, smoking, alcohol and drug use, physical and mental health history, current depression or anxiety and family history of mental health and suicide incidents emerging as common predictors. GIS analysis unraveled notable regional disparities in MHL, particularly in knowledge of mental health and mental illness, with northern and some southern districts displaying higher literacy levels. In conclusion, these findings accentuate significant gender and sociodemographic inequalities in MHL among prospective university students, highlighting the imperative for targeted interventions to enhance MHL and foster mental well-being in this cohort.

Geographic information system-aided evaluation of epidemiological trends of dengue serotypes in West Bengal, India.

West Bengal is a dengue-endemic State in India, with all four dengue serotypes in co-circulation. The present study was conceived to determine the changing trends of circulating dengue virus (DENV) serotypes in five consecutive years (2015-2019) using a geographic information system (GIS) during the dengue season in West Bengal, India. Molecular serotyping of dengue NS1 sero-reactive serum samples from individuals with ≤5 days of fever was performed using conventional nested reverse transcriptase-PCR. GIS techniques such as Getis-Ord Gi* hotspot analysis and heatmap were used to elucidate dengue transmission based on the received NS1-positive cases and vector data analysis was used to point out risk-prone areas. A total of 3915 dengue NS1 sero-positive samples were processed from most parts of West Bengal and among these, 3249 showed RNA positivity. The major circulating serotypes were DENV 3 (63.54%) in 2015, DENV 1 (52.79%) in 2016 and DENV 2 (73.47, 76.04 and 47.15%) in 2017, 2018 and 2019, respectively. Based on the NS1 positivity, dengue infections were higher in males than females and young adults of 21-30 yr were mostly infected. Getis-Ord Gi* hotspot cluster analysis and heatmap indicate that Kolkata has become a hotspot for dengue outbreaks and serotype plotting on maps confirms a changing trend of predominant serotypes during 2015-2019 in West Bengal. Co-circulation of all the four dengue serotypes was observed in this study, but only one serotype became prevalent during an outbreak. Representation of NS1-positive cases and serotype distribution in GIS mapping clearly showed serotypic shift in co-circulation. The findings of this study suggest the need for stringent surveillance in dengue-endemic areas to limit the impact of dengue and implement better vector-control strategies.

Assessment of land use cover changes, carbon sequestration and carbon stock in dry temperate forests of Chilas watershed, Gilgit-Baltistan

Abstract Land use and land cover change are affecting the global environment and ecosystems of the different biospheres. Monitoring, reporting and verification (MRV) of these changes is of utmost importance as they often results in several global environmental consequences such as land degradation, mass erosion, habitat deterioration as well as micro and macro climate of the regions. The advance technologies like remote sensing (RS) and geographical information system (GIS) are helpful in determining/ identifying these changes. In the current study area, changes in carbon stocks, notably in forest areas, are resulting in considerable dynamics of carbon stocks as a result of climate change and carbon sequestration. This study was carried out in the Diamer district of the Gilgit Baltistan (GB) Pakistan to investigate the change in cover change/land use change (particularly Forest Land use) as well as carbon sequestration potential of the forests in the district during almost last 25years. The land cover, temporal Landsat data (level 1, LIT) were downloaded from the USGS EROS (2016), for 1979-1989, 1990-2000 and 2001-2012. Change in land uses, particularly forest cover was investigated using GIS techniques. Forest inventory was carried out using random sampling techniques. A standard plot of size 0.1 ha (n=80) was laid out to determine the tree density, volume, biomass and C stocks. Simulation of C stocks was accomplished by application of the CO2FIX model with the data input from inventory. Results showed a decrease in both forest and snow cover in the region from 1979-2012. Similarly decrease was seen in tree volume, tree Biomass, dynamics of C Stocks and decrease was in occur tree density respectively. It is recommended we need further more like project such as BTAP (Billion Tree Afforestation Project) and green Pakistan project to increase the forest cover, to control on land use change, protect forest ecosystem and to protect snow cover.

ENVIRONMENTAL IMPACT OF URBANIZATION ON LAND USE COMPATIBILITY AND ENVIRONMENTAL QUALITY IN PORT HARCOURT, RIVERS STATE

This study examined the environmental impact of urbanization on land use compatibility and environmental quality in Port Harcourt Metropolis. The study adopted the multi-method research, integrating both qualitative and quantitative approaches through the convergent mixed method technique, where 399 household heads were selected from 189,317 household heads using the Taro Yamane formula. Questionnaires and checklists were administered to the household heads and ten (10) key informants respectively. Descriptive statistics, critical informant content analysis, and Geographical Information System (GIS) techniques were employed for data presentation and analysis for the study. Multiple Regression Analysis (MRA) was employed to test stated hypothesis for the study. The findings revealed numerous environmental changes resulting from land use/land cover change activities in the area to include deforestation, which accounted for 20.5%, degradation, which represented 19.7%, forest degradation corresponding to 19.7%, generation of waste causing pollution, accounting for 20% and decrease in environmental quality corresponding to 20.1% of the total sampled population of the study. Additionally, the impact of urbanization on environmental quality were revealed as flooding, which accounted for 11% of the sampled respondents as well as air pollution, representing 10.8%. Others ecological disaster (8.7%), waste disposal damping (8.9%), land use incompatibility (7.4%), slum developments and urban heat island (9.6%), land use conflict (8.1%), reduced wetland (8.4%), environmental degradation (7.4%), land use conversion (6.8%), overcrowding of buildings (7.1%) and habitat contamination (7.9%). The study concludes that rapid urbanization has significantly impacted land use compatibility and environmental sustainability in Port Harcourt metropolis. It is therefore recommended amongst others that the government should implement stringent urban development control measures to regulate land use and ensure sustainable urban growth as well as establish policies that limit haphazard expansion and promote planned development.

Geographic Information Systems Applications in Business Decision-Making

The recent advancements in Geographic Information Systems (GIS) techniques and their applications across various business domains provide an overview of cutting-edge GIS methodologies, including spatial analytics, machine learning integration, and advanced visualization tools. The study sheds light on how these techniques enhance decision-making processes in industries such as retail, service, and manufacturing. Challenges encompass the complexity of integrating diverse datasets, issues of data usage, and ensuring the interpretability and efficient use of machine learning algorithms within GIS frameworks. In response to these challenges, the primary objective of this study is to address the limitations of current GIS methodologies by understanding their capabilities while ensuring the effective use of advanced technologies, and optimizing business decision making processes.