Areas Of High Population Density Research Articles

The distribution and characterisation of microplastics in air, surface water and sediment within a major river system

Rivers are key pathways for the transfer of microplastics (MP) to marine environments. However, there are considerable uncertainties about the amount of microplastics transported by rivers to the ocean; this results in inaccuracies in our understanding of microplastic quantity and transport by freshwater systems. Additionally, it has been suggested that rivers may represent long-term sinks, with microplastics accumulating in sediment due to their high density or other biological, chemical, and physical factors. The atmosphere is also an important pathway by which airborne microplastics may enter aquatic habitats. Here, we compare for first time microplastics type and concentration in these key environmental mediums (air, water and sediment) along a major river (Ganges), from sea to source to understand 1) the abundance, 2) the spatial distribution, and 3) characteristics. Mean microplastic abundance settling from the atmosphere was 41.12 MP m2 day−1; while concentrations in sediment were 57.00 MP kg−1 and in water were 0.05 MP L−1. Across all sites and environmental mediums, rayon (synthetically altered cellulose) was the dominant polymer (54–82 %), followed by acrylic (6–23 %) and polyester (9–17 %). Fibres were the dominant shape (95–99 %) and blue was the most common colour (48–79 %). Across water and sediment environmental mediums, the number of microplastics per sample increased from the source of the Ganges to the sea. Additionally, higher population densities correlated with increased microplastic abundance for air and water samples. We suggest that clothing is likely to be the prominent source of microplastics to the river system, influenced by atmospheric deposition, wastewater and direct input (e.g. handwashing of clothes in the Ganges), especially in high density population areas. However, we suggest that subsequent microplastic release to the marine environment is strongly influenced by polymer type and shape, with a large proportion of denser microplastics settling in sediment prior to the river discharging to the ocean.

Electric grid resilience: The effects of conductor coverings, enhanced tree trimming, and line characteristics on tree-related power outages

Tree damage is a major cause of storm power outages in forested regions of the world which results in substantial economic losses each year. Utilities must understand the effectiveness of resilience programs to make the best use of limited resources. Our study evaluated the effectiveness of covered conductors and enhanced tree trimming (ETT) in reducing tree-related outages during storms for an electric overhead distribution system. Our study area was the Eversource Energy service area in Connecticut which has heavy forest cover coinciding with areas of high population density. We controlled for the effects of confounding factors including weather, power line phase, and tree canopy cover. Covered conductors and ETT were similarly effective in reducing power outages with median rate reductions of 0.19 - 0.29 outages/km/year. When used in combination, covered conductors with ETT had a significant additive effect with median reductions of 0.29 – 0.33 outages/km/year compared to bare conductors with no ETT. Multiphase power lines had median outage rates that were 0.17 – 0.37 outages/km/year lower than outage rates for single-phase power lines. Our findings will help utilities select and justify their choices of resilience strategies and more accurately predict outage locations in advance of approaching storms.

Domestic water quality and the discriminatory influence of socio-economic stratification on accessibility to safe water in a part of Osun State, Nigeria

The status of the water supplied to households in an urban local government area in southwest Nigeria was examined. Specific objectives were to characterize household water sources, assess the per capita usage of potable water sources and examine quality of the household water in the area. The purposively selected study area, Olorunda local government area in Osun State, Nigeria (being an urban local government area) was stratified into ‘urban core’ (central business district, CBD or high population density area), ‘transition’ (medium population density area but with less social infrastructure) and ‘sub-urban’ (typically government reserved area and low population density area) based on household density and associative socio-economic status. The methods were a mix of questionnaire administration to heads of 120 households (40 per stratum) and collection of the drinking water samples from the supply sources at four randomly selected households in each stratum. The water samples were analysed for the concentrations of nitrite (NO2-), nitrate (NO3-), fluoride (F-), lead (Pb) and arsenic (As) as well as E-coli bacteria contents based on their importance in determining water quality in urban areas. The results showed that domestic water sources are mainly hand dug well (55.8%), borehole (37.5%) and pipe borne (6.7%). Residents averagely consumed at most 4L of water per day. Furthermore, the investigated chemical parameters varied as NO2 (0.37-0.94 mg/l), NO3 (0.29-0.70 mg/l), and F- (0.003-0.97 mg/l). As and Pb occurred in trace quantities, and there were no pollution threats to consumers. The amount of E coli and total coliform contents were however outside the safe limits for residents, suggesting contamination of household water by the bacteria sources. The study concluded communities with low socio-economic status which do not have access to state-provided tap water source are more likely to consume polluted water than those with high socio-economic status or that are supplied with state-provided tap water. The study advocates improve urban water management for the urban fringe dwellers.

Home health care routing and scheduling in densely populated communities considering complex human behaviours

This study focuses on the home health care routing problem (HHCRP) in the scenario of high population density areas where many elders live closely together. This study considers two main objectives. The first is to reduce travel and wait times for nurses or elders. The second concerns socially related objectives in scheduling problems, such as ‘quality of life’ and empowerment, by considering assumptions related to the acquaintanceship and mutual preferences of nurses and elders. This study models the effects of mutual preferences and acquaintanceship on service time in HHCRP. We use the Markov decision process and chance-constrained programming (CCP) to model the system to conserve the sequential service provision parameters and better represent the influence of stochastic service times. Because traditional deterministic algorithms cannot solve such a model, we apply a model-free reinforcement learning algorithm, Q-learning (QL), as well as the ant colony optimisation (ACO) algorithm. Thus, we tackle this problem by developing a model and algorithm to solve complex, large-scale systems. This study’s theoretical and practical contributions are verified by feedback from researchers and practitioners.

Spatial Statistics and Severity of Highway Accidents in Nakhon Pathom, Thailand

The aim of this study was to use spatial statistics and geographic information systems to identify high-risk areas for highway accidents in Nakhon Pathom, Thailand. Secondary data from the Ministry of Transport on the locations of accidents in the road network between 2021-2022 was analyzed using Equivalent Property Damage Only (EPDO), Spatial Autocorrelation, Kernel Density Estimation, and hotspot analysis. The study focused on Nakhon Pathom, a province in Central Thailand, and found that high-risk areas were concentrated along major routes with heavy traffic and high population density, including both urban and community areas. The study also identified specific risk spots, with Kamphaeng Saen District and Highways NO. 321(Kamphaeng Saen-Thung Khok Road), NO. 3231(Den Makham-Bang Len Road), and NO. 3232(Nong Phong Nok - Pai Chedi Road) being particularly affected, as well as Sam Phran District and Highway NO. 375(Ban Bo-Phra Prathon Road). These findings provide important insights into the clustering of accidents and their risk spots, which can be used to improve traffic safety in Nakhon Pathom.

Anticipating Current and Coming Technologies that Affect U.S. Travel Choices

Understanding the preferences for new and future transportation technologies is important to ensure an efficient and equitable future transportation system. A survey was conducted of Americans’ preferences for several such technologies. Americans are concerned about vehicle range and charging station availability for electric vehicles (EVs) and hesitant about autonomous vehicle (AV) safety. Opinions about many transportation technologies, such as vertical takeoff and landing (i.e., air taxis), shared parking, and air-drone delivery are mixed. These less familiar technologies require continued tracking of preferences. A 55% increase is estimated in the probability of an individual choosing a battery electric vehicle (BEV) pickup truck if its fuel economy increases by about 9%. This result supports a market for BEV pickup trucks currently under development by many automakers. The preference for vehicle autonomation appears to depend on the use case. Driving task automation is preferred by residents of low-density, car-dependent areas where long commutes are common. In contrast, automated parking technologies are favored by those living in denser communities. Intermittent bus lanes are favored by those living in high population density areas, but not among those in areas with high shares of zero-vehicle households. These results provide indications of where to direct future research in the field.

Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data

Safety issues associated with transporting crude oil by rail have been a concern since the boom of the U.S. domestic shale oil production in 2012. During the last decade, over 300 crude-oil-by-rail incidents have occurred in the United States. Some of them have caused adverse consequences including fire and hazardous materials leakage. However, only limited information on crude-on-rail routes and their associated risks is available to the public. To this end, this study proposed an unconventional way to reconstruct crude-on-rail routes using geotagged photos harvested from the Flickr website. The proposed method linked the geotagged photos of crude oil trains posted online with national railway networks to identify potential railway segments that those crude oil trains were traveling on. A shortest path-based method was applied to infer the complete crude-on-rail routes, by utilizing the confirmed railway segments as well as their directional information. Validation of the inferred routes was performed using a public map and official crude oil incident data. The results suggested that the inferred routes based on geotagged photos had high coverage, with approximately 96% of the documented crude oil incidents aligned with the reconstructed crude-on-rail network. The inferred crude oil train routes were found to pass through several metropolitan areas of high population density, who were exposed to potential risk. These findings could improve situational awareness for policy makers and transportation planners. In addition, with the inferred routes, this study has established a good foundation for future crude oil train risk-analyses along the rail route.

Assessing spatial variation in water supply of a city using dasymetric mapping

Abstract Wastewater has the potential to act as a supplement when freshwater resources are limited. To utilize this, city administrators need to identify the type and quantity of wastewater generated and its various functional uses. In countries like India, where detailed data about wastewater is not available, any potential reuse proposal is difficult to design and execute. To cover this gap, this research proposes a technique using dasymetric mapping and Voronoi diagrams to estimate the quantity and spatial distribution of wastewater generated in a city, based on population data and water supply information, by mapping and identifying the variation in the supply. The developed research framework is tested in Bhopal city in India. The results suggest that there is higher water consumption in areas of high population density, whereas wastewater generation displays a greater variation based on land use. Among 217 Voronoi polygons created throughout the city, eight have wastewater generation at more than 10 litres/sq. m of area. The total wastewater generated while considering only municipal water supply was 148.32 MLD. On intersecting the Voronoi polygons with ward boundaries, it is found that six wards generate wastewater more than 50 litres/sq. m, whereas seven wards generate less than 1 litre/sq. m of area.

Comparing the Travel Behavior of Older Users Between Station-Based and Dockless Bike Sharing Systems

As the population worldwide continues to age, providing improved mobility services for older people becomes increasingly crucial. In recent years, the maturation of bike sharing has led older people to progressively incorporate it into their everyday lives. In this study, station-based bike sharing (SBBS) and dockless bike sharing (DBS) are investigated in relation to older population mobility. This research relies on the fusion of multiple data sources, including SBBS and DBS trip records, point of interest (POI), and meteorological conditions in Nanjing, China. A zero-inflated negative binomial regression model is used to compare the travel behaviors among various age groups with the exposure variable. SBBS outperforms DBS in relation to age equity, while diverse travel behavior patterns are exhibited between the age groups. Although younger users are the majority of users, older users travel more frequently than younger users in bike sharing services. Also, older users are more likely to use shared bikes near the religious and health POIs, as well as in higher population density areas. This study provides beneficial insights into the transport equity and service improvement of bike sharing systems.

Cryptosporidiosis threat under climate change in China: prediction and validation of habitat suitability and outbreak risk for human-derived Cryptosporidium based on ecological niche models

BackgroundCryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.MethodsThe applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011–2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.ResultsThe Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ2 = 76.641, P < 0.01; χ2 = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions.ConclusionsThe Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks.Graphical

Association of long-term exposure to air pollution with chronic sleep deprivation in South Korea: A community-level longitudinal study, 2008–2018

Background and objectiveAlthough there are many findings about the effects of fine particulate matter (PM2.5) and sleep deprivation on health respectively, the association between PM2.5 and chronic sleep deprivation has rarely been investigated. Thus, we aimed to investigate this association using a nationwide survey in South Korea. MethodWe examined the association between long-term exposure to PM2.5 and chronic sleep deprivation using a national cross-sectional health survey covering the entire 226 districts in inland South Korea from 2008 to 2018, with a machine learning-based national air pollution prediction model with 1 km2 spatial resolution. ResultsChronic sleep deprivation was positively associated with PM2.5 in the total population (odds ratio (OR): 1.09, 95% confidence interval (CI): 1.05–1.13) and sub-population (low, middle, high population density areas with OR: 1.127, 1.09, and 1.059, respectively). The association was consistently observed in both sexes (males with OR: 1.09, females with OR: 1.09)) and was more pronounced in the elderly population (OR: 1.12) than in the middle-aged (OR: 1.07) and young (OR: 1.09) populations. ConclusionsOur results are consistent with the hypothesis regarding the relationship between long-term PM2.5 exposure and chronic sleep deprivation, and the study provides quantitative evidence for public health interventions to improve air quality that can affect chronic sleep conditions.

Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example.

The COVID-19 pandemic highlighted the limitations of urban public health emergency response capabilities. Taking Wuhan as an example, this study used breakpoint regression, kernel density analysis, overlay analysis, and accessibility analysis from Stata and ArcGIS, and divided epidemic prevention facilities into the basic epidemic prevention facilities (hospitals), and the emergency epidemic prevention facilities (mobile cabin hospitals) for further analysis. The results showed that over 70% of the basic epidemic prevention facilities in Wuhan were located in high density population areas. On the contrary, most of the emergency epidemic prevention facilities were located in low density population areas. The local treatment effect of the implementation of the emergency epidemic prevention facility policy is about 1, indicating that there was a significant impact of emergency epidemic prevention facilities on outbreak control, which passed the bandwidth test. What's more, the analysis of the accessibility of residential points revealed that more than 67.3% of people from the residential points could arrive at the epidemic prevention facilities within 15 min, and only 0.1% of them took more than 20 min to arrive. Therefore, the epidemic prevention facilities can effectively curb the spread of the epidemic, and people from residential areas can quickly get there. This study summarized the spatial characteristics of epidemic prevention facilities in Wuhan and analyzed the importance of them, thus providing a new perspective for future research on upgrading the city's comprehensive disaster prevention system.

Perencanaan Sistem PengelolaanAir Limbah Domestik di Unit Pengembangan (UP) I Rungkut, Kota Surabaya

Development Unit (UP) I Rungkut is one of the areas in Surabaya that has a high risk of sanitation problems. The causes are environmental problems arising from the disposal of domestic waste which is directly discharged into drainage channels. Therefore, the Development Unit (UP) I Rungkut Surabaya City designed a Wastewater Distribution System and a Wastewater Treatment Plant (WWTP). In this study, a shallow sewer type wastewater distribution system was used because it is suitable for areas of high population density and gently sloping ground elevations. In the WWTP, several alternative technologies are used, such as the Bar Screen, Equalization Tank, Flotation Tank &amp; Oil Settlement Tank, Mixing Tank (Coagulation-Sedimentation Tank), Food Chain Reactor, Final Clarifier, and Sludge Drying Beds. The planning area is divided into 5 service blocks with a total population of 24,405 people. The results of the study of the technical aspects, are used WWTP with the main processing using the Food Chain Reactor unit. The planning results show that HDPE pipes with a diameter of 355-500 mm are used in the distribution system. The required investment budget is Rp. 87,832,528,386.00. The budget for operating and maintenance costs is Rp. 4,000.00/House Connection (SR) every month.

Water quality of The Gambia River: A prospective drinking water supply

Drinking water in The Gambia is mostly derived from boreholes that could potentially be contaminated. The Gambia River, a major river in West Africa that covers 12 % of the country's area, could be more exploited for drinking water supply. During the dry season, the total dissolved solids (TDS), ranging from 0.02 to 33 g/L in The Gambia River, decreases with the distance to the river mouth with no major inorganic contamination. The freshwater (<0.8 g/L TDS) starts from Jasobo at approximately 120 km from the river mouth and extends by about 350 km to the eastern border of The Gambia. With a dissolved organic carbon (DOC) ranging from 2 to 15 mgC/L, the natural organic matter (NOM) of The Gambia River was characterised by 40–60 % humic substances of paedogenic origin. With such characteristics, unknown disinfection by-products could be formed if chemical disinfection, such as chlorination, was implemented during treatment. Out of 103 types of micropollutants, 21 were detected (4 pesticides, 10 pharmaceuticals, 7 per- and polyfluoroalkyl substances (PFAS)) with concentrations ranging from 0.1 to 1500 ng/L. Pesticides, bisphenol A and PFAS concentrations were below the stricter EU guidelines set for drinking water. These were mainly confined to the urban area of high population density near the river mouth, while the quality of the freshwater region of low population density was surprisingly pristine. These results indicate that The Gambia River, especially in its upper regions, would be well suited as a drinking water supply when using decentralised ultrafiltration treatment for the removal of turbidity, as well as, depending on pore size, to a certain extent microorganisms and DOC.

Impact of Air Pollution on Population Density: A Regression Analysis

With the growth of population and migration, the population density is growing. In high population density area, it found that the air spread virus spread rapidly. Covid-19 cases are actively happening in Malaysia and government is implement movement control to avoid the human traffic and reduce the infected case. In metropolis, such as Petaling district with more strata development, it found that the infected cases are higher than other district. Therefore, to study the relationship between air spread virus and density, this paper employed the regression analysis by collected the infected case and death case of Covid-19 from 25/1/2020 to 31/5/2022 as sample for this paper. From the result, it found that there is significant relationship between air spread virus and density. Thus, it is crucial to re-access the current density ratio for future development to prevent the air spread virus.

An Accessibility Measurement Based on Commuter Behaviour and Living Conditions: An Empirical Analysis of the High-Speed Railway Network in the East of China

High-speed railways as a competitive intercity transport solution in areas of high population density have been constructed rapidly in the last decade. Accessibility measurements have been frequently tested and applied with various definitions, indicators, and processing methods for assessing traffic system utility. In this paper, an improved method of accessibility measurement based on travellers’ profitability is introduced. Three levels of accessibility indicators, Daily Commute Accessibility (DACC), Daily Work Commute Accessibility (DWACC), and Weekly Commute Accessibility (WACC) were designed based on different commuting frequencies and purposes. The average traveller’s income and local living cost were integrated to simulate the real commute scenario and assess the status of the transport system. In the case study, a series of statistics, containing 50 lines of travelling data and 10 years of economic data, was collected from the historical railway service record and local economy yearbook, in an area with 11 cities connected by conventional normal-speed and upgraded HSR networks in the east of China. An index sheet measuring the three levels of accessibility indicated the changes in the travel benefit ratio throughout the test period following popularisation of the high-speed service. To validate the practicability of the new methodology, regression analysis of four groups of panel data, including the accessibility index and local demographic data, was implemented to illustrate the population fluctuation impacted by the HSR services. The results proved that the HSR service is more beneficial in reducing population aggregation than the conventional railway service, which has the opposite effect, leading to the generation of cities with a high population density, and could help to rebalance the local uneven population distribution and promote the progress of urbanisation.

Factors affecting public access defibrillator placement decisions in the United Kingdom: A survey study

AimThis study aimed to understand current community PAD placement strategies and identify factors which influence PAD placement decision-making in the United Kingdom (UK). MethodsIndividuals, groups and organisations involved in PAD placement in the UK were invited to participate in an online survey collecting demographic information, facilitators and barriers to community PAD placement and information used to decide where a PAD is installed in their experiences. Survey responses were analysed through descriptive statistical analysis and thematic analysis. ResultsThere were 106 included responses. Distance from another PAD (66%) and availability of a power source (63%) were most frequently used when respondents are deciding where best to install a PAD and historical occurrence of cardiac arrest (29%) was used the least. Three main themes were identified influencing PAD placement: (i) the relationship between the community and PADs emphasising community engagement to create buy-in; (ii) practical barriers and facilitators to PAD placement including securing consent, powering the cabinet, accessibility, security, funding, and guardianship; and (iii) ‘risk assessment’ methods to estimate the need for PADs including areas of high footfall, population density and type, areas experiencing health inequalities, areas with delayed ambulance response and current PAD provision. ConclusionDecision-makers want to install PADs in locations that maximise impact and benefit to the community, but this can be constrained by numerous social and infrastructural factors. The best location to install a PAD depends on local context; work is required to determine how to overcome barriers to optimal community PAD placement.

The coming perfect storm: Diminishing sustainability of coastal human–natural systems in the Anthropocene

Abstract We review impacts of climate change, energy scarcity, and economic frameworks on sustainability of natural and human systems in coastal zones, areas of high biodiversity, productivity, population density, and economic activity. More than 50% of the global population lives within 200 km of a coast, mostly in tropical developing countries. These systems developed during stable Holocene conditions. Changes in global forcings are threatening sustainability of coastal ecosystems and populations. During the Holocene, the earth warmed and became wetter and more productive. Climate changes are impacting coastal systems via sea level rise, stronger tropical cyclones, changes in basin inputs, and extreme weather events. These impacts are passing tipping points as the fossil fuel-powered industrial-technological-agricultural revolution has overwhelmed the source–sink functions of the biosphere and degraded natural systems. The current status of industrialized society is primarily the result of fossil fuel (FF) use. FFs provided more than 80% of global primary energy and are projected to decline to 50% by mid-century. This has profound implications for societal energy requirements, including the transition to a renewable economy. The development of the industrial economy allowed coastal social systems to become spatially separated from their dominant energy and food sources. This will become more difficult to maintain with the fading of cheap energy. It seems inevitable that past growth in energy use, resource consumption, and economic growth cannot be sustained, and coastal areas are in the forefront of these challenges. Rapid planning and cooperation are necessary to minimize impacts of the changes associated with the coming transition. There is an urgent need for a new economic framework to guide society through the transition as mainstream neoclassical economics is not based on natural sciences and does not adequately consider either the importance of energy or the work of nature.

Examining the release of synthetic microfibres to the environment via two major pathways: Atmospheric deposition and treated wastewater effluent.

Research on the discharge of synthetic microfibres to aquatic environments has typically focused on laundering, where fibres can be discharged via wastewater effluent. However emerging research suggests that microfibres generated during the wear of textiles in normal use could present a major, additional, pathway for microfibre pollution to the environment. This study aimed to quantify and compare the quantities of microfibre entering the marine environment via both these pathways; wastewater discharge and atmospheric deposition. Areas of high and low population density were also evaluated. Samples were collected in and around two British cities (Bristol and Plymouth) both of which are located on tidal waters. Fibres originating from the atmosphere were deposited at an average rate of 81.6 fibres m2 d-1 across urban and rural areas. Treated wastewater effluent contained on an average 0.03 synthetic fibres L-1. Based on our results we predict ~20,000-500,000 microfibres could be discharged per day from the Wastewater Treatment Plants studied. When the two pathways were compared. Atmospheric deposition of synthetic microfibres appeared the dominant pathway, releasing fibres at a rate several orders of magnitude greater than via treated wastewater effluent. Potential options to reduce the release of microfibres to the environment are discussed and we conclude that intervention at the textile design stage presents the most effective approach. In order to guide policy intervention to inform the Plastics Treaty UNEA 5.2, future work should focus on understanding which permutations of textile design have the greatest influence fibre shedding, during both everyday use and laundering.

Identifying Factors for Supporting Early Warning Flood using Clustering Approach And Geo-Spatial Analysis

Floods in Jakarta are very frequent and caused by many factors, from very high rainfall to flash floods. This natural disaster has greatly impact the society, from economy to health problems. In this research, we used ArcGIS Pro with unsupervised clustering method HDBSCAN to create a prototype that would make it easier for people to find out the area that is prone to floods. We received a lot of positive input from many respondents who had seen our prototype design and how it can assist people as the early warning to floods. We analyzed the factors lead the flood early warning system, those factors are high density population distance from river to the high-density population area, drainage system, rainfall intensity, and flood history. We will group flood point with the unsupervised clustering method.