Geographic Information System Approach Research Articles

Mangrove untuk Ketahanan Iklim berdasarkan Indeks Kerentanan Pesisir, Penerapan di Mempawah, Kalimantan Barat

Coastal areas are particularly vulnerable to climate change. The primary objective of this study is to use the Geographic Information System (GIS) approach to assess the level of vulnerability in the coastal area of Mempawah Regency, West Kalimantan, Indonesia, by utilizing the Coastal Vulnerability Index (CVI) and analyzing the role of mangrove land cover in explaining the coastal vulnerability based on land cover characteristics. From 41 surveyed grids, a substantial 65.83% are classified under the category of very low vulnerability, while 34.14% fall within the range of low vulnerability, in Mempawah. The validation of the mangroves' role as a defense mechanism in mitigating climate phenomena within coastal areas was validated through various approaches such as Normalized Difference Vegetation Index (NDVI) and land cover

Identification of potential landfill site suitability for urban solid waste disposal of Balurghat Municipality of Dakshin Dinajpur District using GIS and multi-criteria decision-making approach

The production of urban solid waste is one of the most dangerous environmental health risks on the planet. By selecting suitable landfill sites, it is possible to resolve the issue of health risks and environmental pollution driven by the unscientific disposal of solid waste. The current research is centered on determining suitable landfill locations for solid waste disposal within the Balurghat municipality through the integration of Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) approach. Ten factors were taken into consideration according to their weightage including elevation (0.022), Lithology (0.027), Slope (0.032), Land use and land cover LULC (0.040), Depth of water (0.057), Population density (0.075), Distance from sensitive places (0.107), Distance from road (0.154), Distance from river (0.205) and Land value (0.282). After conducting thorough field visits, an analytical hierarchy process (AHP) under the MCDM approach using GIS reveals acceptable sites that were noted and referenced. Final results are validated through a receiver operating characteristic (ROC) curve using randomly selected 80 potential landfill-suitable site location points with higher accuracy, and a total of 93% of the area under the curve (AUC) has been found worthy to validate the spatial result. The present investigation revealed that only 0.65% of land is very highly suitable, 31.06% of land is highly suitable, 52.54% of land is moderately suitable and 14.74% of land is not suitable for landfilling in Balurghat Municipal area and surroundings respectively. The highly suitable site belongs to the Mamna, Katna, Kuaran, Amtali, Noksha, Bannapara, and Malancha villages of the study area which is a very negligible area. So, the planners should adopt alternative strategies like source minimization, composting, sanitary landfills and awareness programmes for sustainable solid waste management. Hence, the Balurghat Municipality administration, urban planners, and administrative authorities stand to gain valuable insights from the findings of this study as they endeavour to enhance the management of urban solid waste in the area.

Mapping of Groundwater Potential Zones of Khordha District using GIS and AHP Approaches

The most dependable source of fresh water is groundwater. Groundwater supplies are severely threatened by a number of factors, including urbanization, industrialization, and population growth. The amount, quality and variables affecting groundwater supplies are significantly impacted by climate variability. The fall in groundwater levels is often exacerbated by poor quality surface water resources and unreliable monsoons. Therefore, in order to supplement the groundwater supply, it is important to locate and define the groundwater potential zone (GPZ). The analysis is conducted for the Khordha district, where groundwater rather is a primary source for agricultural uses. In order to determine the possible groundwater zones, many factors, including geomorphology, geology, elevation, slope, precipitation, soil type, soil texture, drainage density (DD), lineament density (LD), Land use/Land cover (LULC), and lineament density (LD), are constructed as separate layers in the geographical information system (GIS) backdrop. The multi-criteria decision-making technique and the Analytic Hierarchy Process (AHP), which enable pairwise evaluation of criteria impacting the potential zone, were utilized to establish the weights for the different layers and after that, the weighted overlay analysis (WOA) tool in ArcGIS10.8 was used to produce the final groundwater potential map. The output map of specified region was delineated into five new classes-very good, good, moderate, poor, and very poor of which 12% (325.1745km2) falls under ‘very low’, 22% (603.9765km2) under ‘low’, 26% (700.7715km2) under ‘moderate’, 26% (694.2591km2) under ‘high’, 14% (376.7553km2) under ‘very high’. Approximately 1395km2 area concerning 52% of study region, falls under ‘high’ and ‘very high’ categories of GPZ. Validation of the generated GPWZ map was done with data acquired from Central groundwater board. The accuracy assessment was done by kappa coefficient error matrix, and based on overall accuracy, the obtained map was 81.538% accurate to field value. As dependable results were produced with the proposed methodology, future management plans incorporating natural and artificial recharge practices can be created in these locations with effectiveness.

Assessment of Groundwater Quality Using the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Multivariate Statistical Analysis (MSA), and GIS Approaches: A Case Study of the Mnasra Region, Gharb Plain, Morocco

Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca2+ dominance among cations and Cl− as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca2+-Cl− water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited “Insignificant pollution”. NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated “Good” for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as “Excellent” and 16.66% as “Good”. Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region.

3D Point Cloud and GIS Approach to Assess Street Physical Attributes

The present research explores an innovative approach to objectively assessing urban streets attributes using 3D point clouds and Geographic Information Systems (GIS). Urban streets are vital components of cities, playing a significant role in the lives of their residents. Usually, the evaluation of some of their physical attributes has been subjective, but this study leverages 3D point clouds and digital terrain models (DTM) to provide a more objective perspective. This article undertakes a micro-urban analysis of basic physical characteristics (slope, width, and human scale) of a representative street in the historic centre of Valencia (Spain), utilizing 3D laser-scanned point clouds and GIS tools. Applying the proposed methodology, thematic maps were generated, facilitating the objective identification of areas with physical attributes more conducive to suitable pedestrian dynamics. This approach provides a comprehensive understanding of urban street attributes, emphasizing the importance of addressing their assessment through advanced digital technologies. Moreover, this versatile methodology has diverse applications, contributing to social sustainability by enhancing the quality of urban streets and open spaces.

Spatial interactions between perceived biophilic values and neighborhood typologies in urban wetlands

Wetlands provide a wide range of ecosystem services; however, little is known about their perception value or use for improving urban planning and wetland management. This study explores the perception values towards the Los Batros Wetland in Chile, by inhabitants from different neighborhood typologies. A sample of 457 responses evaluated the wetland by applying the Kellert framework of 9 biophilic values using a Public Participation Geographic Information Systems (PPGIS) approach. A spatial autocorrelation analysis with hotspot revealed that the spatial distribution of biophilic values varies by neighborhood typology. Subsequent ANOVA and T-test suggest that such distribution is affected by perceived accessibility and visitation purposes, and is influenced by socio-demographic aspects that vary among neighborhood typology. Inhabitants of the garden city typology located next to the wetland area, whose residents have higher education and income levels and who have easy and moderate access to the wetland, agreed with a diverse type of biophilic values. In the garden city, the ecologistic-scientific value has the higher spatial concentration. In the condominium typology, with similar education and income levels and accessibility, but situated far from the wetland, there was less agreement with biophilic values, and these were more dispersed, i.e. biophilic values are less representative. In this case, the aesthetic value prevails over others. At the north area of the neighborhood unit, where residents had lower education and income levels along with moderate to difficult physical access to the wetland, but they developed horticultural activities alongside the wetland, inhabitants agree with various biophilic values, highlighting its symbolic value. Conversely, biophilic values of people in the favela were not in agreement nor disagreement, regardless they have similar physical access and distance to the wetland as residents in the condominium typology, but have the lowest income and education level. Findings suggest that effective wetlands management requires appreciation of the clusters of values assigned to wetland environments, which in this case relate to neighborhood typologies. These clusters should be considered when planning to restore, protect, and improve urban wetlands.

Seasonal variations in chlorophyll–a and sea surface temperature in the exclusive economic zone of Sri Lanka

Oceanic phytoplankton plays a crucial role in regulating the biogeochemical cycle in marine ecosystems. Light harvesting pigments such as chlorophyll–a (chl–a) can be used to understand marine primary productivity, especially phytoplankton abundance. Sea surface temperature is closely linked with phytoplankton abundance and climatic changes. The objective of the current study is to determine spatial and temporal variations of chl–a and sea surface temperature and their co-variation, over 12 years using statistical methodologies and Remote Sensing, Geographic Information System (GIS) and Cloud Computing Approach. In this study, the available sea surface temperature and chl–a data acquired from a Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor were proceeded through Google Earth Engine and Earth Science Data System. Data visualization was carried out using ArcMap™ software. Results show a weak negative linear relationship (–0.40, P < 0.05) between sea surface temperature and chl–a. Therefore, additional favorable environmental factors such as coastal upwelling, and nutrient discharge through river run-off can control the primary productivity of phytoplankton. We also illustrated spatial and temporal maps for chl–a and sea surface temperature distribution in the exclusive economic zone of Sri Lanka. Chlorophyll–a concentration is enhanced during the southwest monsoon, and the lowest concentration is observed during the first inter-monsoon period. Next, the highest sea surface temperature is recorded during the first inter-monsoon period, and the lowest sea surface temperature is observed during the northeast monsoon. Seasonal behavior of chl–a concentration and sea surface temperature are changed as chl–a (SWM) > chl–a (NEM) > chl–a (SIM) > chl–a (FIM) and SST (FIM) > SST (SIM) > SST (SWM) > SST (NEM), respectively. In addition, both trend lines for each variable show a positive gradient, which may be attributed to global warming. Finally, we observed the alteration of chl–a and sea surface temperature that linked to changes in ocean chemistry during the global COVID–19 pandemic.

Protecting breeding sites: a critical goal for the conservation of the golden eagle in Mexico under global change scenarios

AbstractImpacts of global climate and land‐use changes on distribution patterns and breeding sites remain today poorly studied for several vulnerable emblematic bird species, including the Golden Eagle (Aquila chrysaetos). Herein, we analyzed the potential effect of global climate changes and agricultural activities on the distribution patterns of this top predator across Mexico. We assessed the long-term role of protected areas (PAs) for safeguarding the species’ overall distribution and its breeding sites. We evaluated current and future (2040s, 2060s, and 2080s) threats from global change using ecological niche modeling and geographic information system approaches to determine the percentage of the species’ distribution area that overlaps with highly human-modified areas and PAs under each climate scenario. We also used niche overlap tests to assess whether the species’ breeding sites show equivalence or similarity of climatic conditions over time. Our findings revealed shifts in the Golden Eagle’s distributional area, with an overall size reduction (by ~ 57% in the 2040s and ~ 78% in the 2080s) due to future environmental changes, mainly attributable to increasingly dry and warm conditions. Mexican PAs cover ~ 12% of the Golden Eagle’s range across country, but this decreased by &gt; 33% on average under the species’ future distributions. Although the hypothesis of equivalent climatic conditions at breeding sites over time was rejected, those sites did have long-term climate similarity (niche overlap: 0.75–0.83; P &lt; 0.05). Considering the species’ nest site fidelity and that colonization of new areas within Mexico seems unlikely, protection of these breeding sites is a critical step for the long-term conservation of this emblematic species in Mexico.

GIS and Geospatial Approaches for Political Science Studies: Urban Development Analysis

A geographic information system (GIS) is a tool that collects, organizes, interprets, and maps different kinds of data. The geospatial method consists of the gathering, displaying, and manipulating of imagery, GPS, satellite photos, and historical data that are used with geographic models and either explicitly specified in terms of geographic coordinates. Political science studies regional, state, and national governments, political actors, political discourse in the media, and the connections between political figures and groups. In this study, Geographic Information System and Geospatial approaches for Political Science studies are used to develop Urban Development Analysis. Political scientists have been incorporating GIS technology into their statistical analyses in recent years. This study's understanding of GIS as a mix of technology, methodology, and situated social practices is the foundation of the GIS. With the development of a permanent and easily editable database in a particular area, where various types of data may be kept, merged, and graphically displayed, GIS technologies make it all this simpler. GIS allow researchers to deal with complex, multivariate, and multidimensional historical processes more successfully as well as uncover historical, political, or social issues that may not always be readily apparent when using more conventional research and analytical techniques.

Assessment of Off-Grid Power Plants in Nigeria: Location, Capacity, Performance and Current Status

The power sector in Nigeria still struggles with significant electricity challenges resulting from the unavailability of power supply and the unreliability of the conventional national grid. The total installed capacity of off-grid plants in Nigeria is approximately a meagre 52 MW, with a combination of 67 operational mini-grids and solar home systems across the country impacting only about one million households and around five million residents out of Nigeria’s population of over 200 million people.  It has been reported that both urban and rural areas suffer the impact of power shortages and frequent blackouts. The unreliability of power supply in Nigeria has been identified as a significant problem affecting educational institutions in terms of productive learning, student residency and institutional operations, and also the overall operation of healthcare facilities as it limits access to quality healthcare services. The study examines the presence and potential of off-grid power solutions in Nigeria which present a more reliable approach to supplying electricity to users, as a deliberate response to the multiple and complex challenges in the Nigerian power systems to identify the present location, installed capacity, operational performance, and current status of off-grid power plants in Nigeria. The Geographic Information System and statistical approaches were employed. It was discovered that off-grid solutions are beginning to spread across the country on different scales. However, most rural areas in Nigeria still do not have access to electricity supply. The study encourages decentralized power generation in the country and emphasizes the need for the federal government through the Rural Electrification Agency (REA) to consider investing in off-grid solutions, particularly in the rural areas for socio-economic benefits.

Abstract 434: Understanding metabolic heterogeneity of estrogen receptor positive metastatic breast tumors using spatial transcriptomics and geographic information systems approaches

Abstract The tumor microenvironment consists of numerous cell populations showing diverse metabolic preferences, causing metabolic heterogeneity and therapy resistance. Fulvestrant, a clinically approved selective estrogen receptor (ER) degrader, is the standard of care for ER-positive breast cancer, yet resistance has been reported among metastatic breast cancer patients. In our previous studies, we showed such resistance is attributable to metabolic heterogeneity in the tumor microenvironment. Despite metabolic heterogeneity posing a common challenge in cancer research, current methods, such as histology and Magnetic Resonance Imaging, cannot explore nutrient uptake at transcript-level resolution with spatial context, making it difficult to understand the heterogeneity that affects cellular growth and metabolism. Visium Spatial Transcriptomics, a method that shows regional gene expression, is emerging as a powerful spatial analysis tool, and we integrated this method with geographic information systems to investigate the tumor microenvironment heterogeneity and highlight the importance of cell-microenvironment interactions. We developed a computational pipeline to visualize hotspots of spatially relevant genes using breast cancer metastatic samples from xenograft models and human patients. This pipeline integrates Visium tools and geospatial methods for processing transcriptome profiling data. We analyzed the degree of local spatial association based on Local Moran’s I to estimate regions with significant co-localization of single and multiple gene expressions within a tumor. We then leveraged the co-localized areas in the process of biomarker identification and revealing biological pathways. We also used unsupervised clustering of the complete transcriptome profiles to test the resemblance between identified clusters and hotspots as well as any disruption in the spatial structure of clusters in response to therapy or metastasis. Gene set enrichment analysis of these clusters revealed several glucose or lipid metabolism pathways, and mapping of the genes corresponding to each pathway showed mutually exclusive gene expression patterns in the sample. We also observed minimal co-localization of two metabolic pathways but extensive co-localization between metabolic genes and ER target genes, suggesting distinct metabolic preferences and spatial distributions of endocrine therapy resistant cell populations. Altogether, our analysis pipeline established a computational framework for characterizing the link between tumor microenvironment, local metabolism, and changes in transcriptional response to external stimuli. Our findings support the development of strategies to target different endocrine resistant regions using a combination of ER and metabolic signaling inhibitors. Citation Format: Jin Young Yoo, Sabrina Akter, Nandana Varma, Atharva Jain, Aiman Soliman, Zeynep Madak Erdogan. Understanding metabolic heterogeneity of estrogen receptor positive metastatic breast tumors using spatial transcriptomics and geographic information systems approaches [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 434.

Your Favourite Park Is Not My Favourite Park: A Participatory Geographic Information System Approach to Improving Urban Green and Blue Spaces—A Case Study in Edinburgh, Scotland

Access to urban green and blue spaces (UGBSs) has been associated with positive effects on health and wellbeing; however, the past decades have seen a decline in quality and user satisfaction with UGBSs. This reflects the mounting challenges that many UK cities face in providing appropriate public facilities, alongside issues such as health inequalities, an ageing population, climate change, and loss of biodiversity. At present, little is known about the preferences of different population subgroups and, specifically, the UGBSs they visit and the spaces they avoid. Using a public participatory geographic information system (PPGIS), the overall aim of the research presented here was to investigate the preferences of different population subgroups in urban areas, and the UGBSs they visit, using Edinburgh, Scotland as a case study. We created a baseline visitor demographic profile for UGBS use, and highlighted how visitors perceive, physically access, use, and engage with UGBSs. The results revealed considerable variation in UGBS preference: one person’s favourite UGBS may be one that someone else dislikes and avoids. It is clear that adapting UGBSs to suit local communities should not be a ‘one-size-fits-all’ approach. The conflicting views and preferences of different groups of respondents point to the importance of developing policies and park management plans that can accommodate a variety of uses and experiential qualities within individual parks. PPGIS approaches, such as those utilised in this study, offer opportunities to address this issue and provide evidence to increase equitable UGBS usage.

Optimal site selection for geothermal heated greenhouses in cold climates: a fuzzy logic and geographic information system approach

Abstract This paper presents a comprehensive model for selecting optimal sites for geothermal heated greenhouses in the agricultural industry. The research involves two main componentsf: assessing the geothermal energy resource using geological, geochemical and geophysical indicators; and developing a siting model based on fuzzy logic that considers technical, environmental and socio-economic factors. The study focuses on East Azerbaijan province in Iran—a cold region. The results indicate that ~3.24% of the total area of the province is suitable for constructing geothermal greenhouses, resulting in potential savings of ~148 000 and 745 978 m3 of natural gas in areas with high and very high suitability, respectively.

Multivariate analysis and GIS approaches for modeling and mapping soil quality and land suitability in arid zones

Assessing soil quality marks the initial step in precision farming and agricultural management. Developing countries like Egypt face numerous hurdles in ensuring food security due to increasing populations and limited agricultural resources. A geographic information system (GIS) and multivariate analysis were utilized in the current work to evaluate and map a soil quality index (SQI). Moreover, the land suitability of the land for two plantations of the tree's oak (Quercus robur), and pine (Pinus silvestris), respectively was assessed using a parametric approach. A total of 82 soil profiles were selected to fulfill the objectives of the study. Based on the samples' PC scores, and agglomerative hierarchical clustering (AHC, the data was divided into two clusters: Cluster I and Cluster II, which collectively account for approximately 57% and 43% of the total data, respectively.. . The findings indicated that land suitability for planting Q. robur planted identified 2.14% of the research area as highly suitable (S1), 37.98% as moderately suitable (S2), and 59.89% as not suitable (N). Furthermore, the assessment of suitability for P. silvestris indicated that 50.88% of the investigated area was classified into: S1, 48.73% as S2, and 0.39% as N, which means it is not suitable for conservation activities. The research identified that soil depth beside excessive salinity and calcium carbonate as the primary soil constraints in the area in both clusters. The average soil depth, ECd and CaCO3 were 113.62 ± 12.41, 17.27 ± 10.23, 16.83 ± 6.57 in Cluster 1 and 45.43 ± 15.21, 22.42 ± 12.43, 21.55 ± 5.63 in Cluster II. The study demonstrates that integrating multivariate analysis with GIS enables a precise and streamlined assessment of the Soil Quality Index (SQI). Soil suitability modelling underscores the importance of implementing efficient management practices to attain agricultural sustainability in arid regions, particularly amidst intensive land utilization pressures

Daily life activities of young adults with obesity living in highly accessible and compact urban environments in Seoul, South Korea: a spatiotemporal qualitative study protocol

IntroductionAmid the growing global concern about obesity, young adults in South Korea are particularly affected, with 30.8% of people aged 19–34 classified as obese. Given the urban-centric lifestyle of Korean...

A geographic information system approach for estimating state‐wide water quality credit need: Application for planned transportation projects in Virginia

AbstractUncertainty in water quality trading (WQT) markets is frequently cited as a deterrent for participation, with few studies focusing on uncertainty in future water quality credit needs. To reduce this uncertainty, we present a geographic information system (GIS)‐based methodology for estimating an upper bound of water quality credit needs for a set of spatially referenced planned construction projects over a large geographic region. We demonstrate the methodology by applying it to estimate future credit needs for the Virginia Department of Transportation's (VDOT) 6‐year improvement program. The results show that 25% of the state's 6‐digit hydrologic unit code (HUC) basins lack sufficient current credit supply to meet the estimated future credit need from VDOT's planned projects alone. Furthermore, while 70% of the 8‐digit HUCs containing planned projects have a sufficient current credit supply to meet VDOT credit needs, this is true for only 20% of the 10‐digit HUCs. Finally, nearly 25% of the planned transportation projects, representing potentially $9 million in credit purchases at current market rates, will be constructed in catchments with impaired water bodies. State regulations will initially limit these projects to trade with credit banks collocated at the 12‐digit HUC level. This application demonstrates how the GIS‐based methodology can be applied to reduce uncertainty about future WQT credit needs and how needs are aligned with current credit supply.

Delineation of Potential Groundwater Zones and Assessment of Their Vulnerability to Pollution from Cemeteries Using GIS and AHP Approaches Based on the DRASTIC Index and Specific DRASTIC

The risk of aquifer contamination is determined by the interaction between the pollutant load and the vulnerability of an aquifer. Owing to the decomposition of bodies and degradation of artefacts, cemeteries may have a negative impact on groundwater quality and suitability for use due to the leaching of organic compounds (e.g., biodegradable organics, pharmaceuticals, and formaldehyde), inorganic compounds (e.g., nitrate and heavy metals), pathogenic bacteria, and viruses. Factors such as burial and soil type, rainfall amount, and groundwater depth may increase aquifer vulnerability to pollutants generated in cemeteries. The potential for groundwater contamination was investigated in two cemeteries of the Soure region in Portugal (Samuel–UC9 and Vinha da Rainha–UC10), using the classic DRASTIC model, followed by some adjustments, depending on the particularities of the locations, resulting in a Final Classification considered as Specific DRASTIC. By combining Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP), groundwater potential zones (GWPZs) were identified, and aquifer vulnerability was assessed, which included the elaboration of thematic maps using GIS operation tools. The maps allowed for the identification of areas with different susceptibilities to contamination: from “Low” to “Very high” for the DRASTIC index and from “Very Low” to “Very high” for the Specific DRASTIC index. Although the difference between the UC9 and UC10 cemeteries is negligible, UC10 is more vulnerable because of its proximity to the community and critically important mineral water resources (such as Bicanho Medical Spa). The Specific model seems better-suited for describing vulnerability to cemeteries. Although there is limited groundwater quality data for the area, the development of vulnerability maps can identify areas that can be sensitive spots for groundwater contamination and establish procedures for pollution prevention.

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.

Fine Scale Modeling for Potential Distribution of Dengue Fever in Tampan District, Indonesia

Larvisiding is one common way used to reduce mosquito density in breeding areas before metamorphosizing into adults. Despite numerous eradication efforts, the outcomes have not met expectations, leading to additional issues such as environmental pollution in urban areas. In the context of dengue hemorrhagic fever (DHF), addressing the challenge of mitigating the endemic outbreak entails formulating an effective strategy through a vector eradication approach. Therefore, this study explored the spatial pattern of DHF and estimated the potential spread of outbreaks. A geographic information system approach, with nearest neighbor analysis and kernel density estimation (KDE), was used to generate information regarding the pattern and potential for transmission of Aedes aegypti mosquitoes. The results showed that in 2019, a random pattern was observed, while in 2020, a clustered pattern of virus spread occurred. Furthermore, in terms of the potential transmission, an exposed zone of 9.73 km² was identified in 2019, and this increased to 15.72 km² in 2020. In this study, several important actions were implemented with a spatial approach, enabling the detection and polarization of events. However, the limitations included not being comprehensive in addressing the hygiene, sanitation, drainage, and population density aspects.

Using Data Bricolage and Mixed-Methods GIS to Uncover Mental Health Service Gaps in Rural Australia

This article develops an approach to data bricolage by mixed-methods geographic information systems (GIS) to challenge assumptions that quantitative service provision data and consumer surveys are the only sources of data that can inform gaps in service accessibility. Claims of repurposing health data have long animated health geography, but methodological advances have only recently begun to open opportunities for geographical analyses of reused secondary data. In this study, we developed novel mixed-method GIS approaches to sourcing and integrating (i.e., bricolage) geolocated health consumer information produced in online mental health forums. Although digital methods have been used for some time to gather and analyze social media and other online health data, we emphasize the process of partnering with mental health organizations to generate new knowledge about place-based lived experiences that can be used to improve service provision. Using rural Australia as a case study, we geospatially analyzed qualitative lived experience data produced in online mental health forums to better understand rural peoples’ service access challenges. In doing so, we found that it is feasible to bricolage secondary reused sources of qualitative lived experience data describing rural experiences in place.