Shelter Location Research Articles

Use of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand

The 2004 Indian Ocean tsunami led to improvements in Thailand’s early warning systems and evacuation procedures. However, there was no consideration of better aid delivery, which critically depends on estimates of the affected population. With the widespread use of geographical information systems (GIS), there has been renewed interest in spatial population estimation. This study has developed an application to determine the number of disaster-impacted people in a given district, by integrating GIS and population estimation algorithms, to facilitate humanitarian relief logistics. A multi-stage spatial interpolation is used for estimating the affected populations using ArcGIS software. We present a dasymetric mapping approach using a population-weighted technique coupled with remote sensing data. The results in each target area show the coordinates of each shelter location for evacuees, with the minimum and maximum numbers of people affected by the tsunami inundation. This innovative tool produces not only numerical solutions for decision makers, but also a variety of maps that improve visualisation of disaster severity across neighbourhoods. A case study in Patong, a town of Phuket, illustrates the application of this GIS-based approach. The outcomes can be used as key decision-making factors in planning and managing humanitarian relief logistics in the preparedness and response phases to improve performance with future tsunami occurrences, or with other types of flood disaster.

Optimal Location Identification for Emergency Evacuation Shelters using the Voronoi Diagram

Recently, the frequency of earthquakes in Korea has increased; thus it is very important to select the location of an emergency shelter. Therefore, this study proposed a method for selecting an emergency shelter location using the Voronoi diagram, which is usefully used to identify the shortest route or divide jurisdictions. First, Yangsan-si, where the earthquake zone is located, was selected as the target site for the study area, and the evacuation facility area was analyzed using the Voronoi polygon considering an evacuation to nearby emergency shelters regardless of administrative districts. Next, examining the vulnerable portions of the study area based on the existing earthquake outdoor evacuation facility data and floating population data, it was confirmed that there was a large regional variation. Finally, the location of a new shelter in Yangsan-si was selected by quantifying the location data of the building where supply was insufficient and the distance between emergency evacuation facilities as weights. The analysis result showed that installing a total of 7 shelters was the most efficient. The results of this study are expected to contribute to selecting the location of a new evacuation facility and establishing an efficient evacuation plan in the future.

Analisis Spasial Untuk Klasifikasi Pengembangan Tempat Penampungan Sementara Menggunakan Metode Jaringan Syaraf Tiruan

Garbage is a problem that needs an in-depth study in urban areas because the development of an area has consequences on increasing population density, facilities and infrastructure, public services, and other aspects that impact increasing the volume of waste. The distribution of temporary waste shelters (TPS) in each area is still insufficient to accommodate the volume of waste, and its availability is inadequate. The purpose of this study is to model spatial data through spatial analysis using artificial intelligence methods in classifying the development of integrated temporary shelter locations (TPST) and regional integrated temporary shelters (TPST Regions) by utilizing Web-based technology (Geographical Information System (Web-GIS). The Artificial Neural Network method with the Backpropagation algorithm is used for the spatial analysis process based on the parameters of the population, the amount of organic and inorganic waste, the amount of industrial waste, and the volume of the TPST and Regional TPST capacity. The spatial analysis results using the Artificial Neural Network method obtained an accuracy value of 7171.02%. The results of this study can be the basis for Department of Environment and Cleanliness policies for the development of TPST and TPST areas with information coverage at the village level.

Dispersal and Deposition of Detritus From Kelp Cultivation

A high resolution coastal and ocean hydrodynamic model system was used to investigate the transport and deposition patterns of Particulate Organic Matter (POM) from kelp farmed at three locations of different properties: a sheltered location, an exposed location, and an offshore location. Published values on the sinking speeds of organic particles from kelp were used, spanning several orders of magnitude. Recent work on quantifying the release of particulate organic matter from farmed kelp was used to link the release of carbon to possible cultivation volumes and scenarios, and finally to link this to the potential for carbon loading on the ocean floor. The results are presented in terms of loading and distribution per unit harvested kelp, and the loading estimates are compared with estimates of natural (background) primary production. According to the simulation results, organic matter may be transported anything from a few (hundred) meters up to a hundred km away from the release site, depending on the sinking rates, time of release, and the location. The depth at which the matter settles on the sea floor likewise depends on the properties of the matter and the sites. The time until settlement varied from minutes to several hundred hours. The results underscore the importance of constraining the dispersal and deposition of detritus from kelp cultivation in order to better understand and quantify associated environmental risks posed by organic loading, and the potential for seafloor carbon sequestration by kelp farming as a nature based climate solution.

An interdisciplinary agent-based multimodal wildfire evacuation model: Critical decisions and life safety

This article applies an interdisciplinary agent-based model (ABM) of wildfire evacuation to the devastating 2018 wildfire in Mati, Greece, where the second-deadliest wildfire of the 21st century took place. This model integrates the natural hazard system (wildfire propagation) with the sociotechnical response system comprising social (population response) and engineered (transportation network and shelter location) components. The research objective is to investigate the effects on wildfire casualties of the risk area population’s decisions about (1) whether to leave and how long to wait (i.e., departure time); (2) what transportation mode to use (e.g., walking or driving); and (3) how fast to travel. Analysis of several evacuation scenarios shows that the absence of children, multi-modal travel, staged evacuation, and increased shelter capacity lead to a more successful wildfire evacuation. These analyses can help emergency managers improve the effectiveness of their communities’ wildfire evacuation plans.

Analysis of landforms, early warning system, locations and evacuation paths for reducing flood disaster risk in Sragen, Central Java, Indonesia

One of the areas in Central Java Province that is prone to flooding is Sragen Regency. The distribution of flood disasters occurs in commensurate rivers and river confluences in lowlands which are dominated by settlements and agricultural land. The purpose of this study was to analyze the distribution of landforms along riverbanks in residential areas and rice fields, refugee shelter locations and evacuation routes for handling disaster risk reduction. The research method is grounded research by recording the population census and public facilities at the affected residential locations. Determination of evacuation locations and routes by using evacuation criteria parameters and safe distance parameters to determine the classification of refugee evacuation locations. The results of the study found that there was a lack of understanding of the landforms of river borders for agricultural and residential land, the utilization and loss of embankments on comparable rivers, especially in areas of interconnection between rivers in the lowlands. To minimize the risk of flooding, it is necessary to add EWS, river border land that is already owned by the community, the use of right of use must be gradually returned as a river border and the selection of the right location and route evacuation.

Notes on the fecundity of the caridean shrimp Cuapetes americanus (Kingsley, 1878) in two preserved areas in São Paulo State: Laje de Santos and Vitória Island

In the Atlantic Ocean, the shrimp Cuapetes americanus (Kingsley, 1878) is well distributed. This species has been studied regarding its taxonomic status, distribution records, and some biological and reproductive traits. However, its fecundity and reproductive aspects have never been evaluated in Brazilian waters before. SCUBA (Self Contained Underwater Breathing Apparatus) diving and Artificial Refuge Substrate were used to sample C. americanus specimens quarterly in a sheltered location in the Marine State Parks of Laje de Santos and Vitória Island for a year (2015-2016). A total of 45 animals (carapace length 1.35-4.54 mm) were sampled: 6 females; 18 ovigerous females; 3 juveniles; and 17 males. The major axis references were employed to analyze the relationship between the second pleura (SPL) and the carapace length (CL). The fecundity was 87.05 ± 80.50 eggs and it was similar to other populations connected to it, and it was exclusively associated favorably with CL. Despite being a small and inconspicuous species, C. americanus is a caridean shrimp species that has evolved to thrive and breed on continental islands. The importance of the creation and revision of management plans for no-take marine areas on the Brazilian coast is supported when many kinds of information about the ecology and biology of the species are available, such as caridean shrimps, which can be present as a link between trophic levels of the aquatic food web.

Scenario-based stochastic shelter location-allocation problem with vulnerabilities for disaster relief network design

We formulate the shelter location-allocation problem considering the vulnerability of the demand locations and their network connectivities with the shelter locations for disaster management's preparedness and response phase. We propose a scenario-based stochastic model that assigns the set of candidate locations evaluating operational, budgetary limitations, and service level expectations. The solution presents an evacuee-allocation plan considering the best collection of less vulnerable network connectivities between the demand areas and the shelter locations. We present a linear relaxation heuristic and compare the heuristic performance with the scenario-based formulation solved using CPLEX 12.8 optimisation solver for various problem sizes. We finally apply and solve the problem using real-life case data obtained during the major flooding event in and around the Chennai Metropolitan Development Area during 2015 to present our model's applicability and emergency response requirements. [Submitted: 12 November 2020; Accepted: 19 April 2021]

Siri' na pacce: The Local Wisdom of Coastal Community Settlement Patterns and Its Existence amid COVID-19 Pandemic

The handling of some issues due to the spread of the COVID-19 virus has been carried out in various cities, including the coastal city of Makassar. Efforts to break the chain of spread of the virus have been carried out starting from the recommendation to comply with health protocols to the establishment of regulations that limit people's daily movement. On the other hand, some local wisdom rooted in the lives of coastal residents also experienced a shift in meaning during this pandemic. This study aims to examine the meaning of local wisdom siri' na pacce in people's lives in coastal settlements, its manifestation in life during the COVID-19 pandemic and efforts that can be made as disaster mitigations. Methods of data collection were done by observation, interviews and questionnaires. The data collected was then analyzed by spatial analysis and description. This study found that the siri' value was influenced by bad stigma towards people with COVID-19 so that the meaning shifted in a negative direction. The value of pacce still has a positive form. It can be seen from community cooperation to help patients who are in self-isolation. At the end of the study, recommendations for pandemic disaster mitigation were formulated in coastal settlements, such as determining the location of temporary shelters and evacuation points.

Location and Layout of Long-Term Shelters for the Elderly from the Perspective of Refuge Needs: Case of Hefei

Location and Layout of Long-Term Shelters for the Elderly from the Perspective of Refuge Needs: Case of Hefei

Simulation of tourists’ wayfinding during evacuation based on experiments in Kyoto

Tourists are often more vulnerable than residents in sudden disaster situations due to lack of knowledge regarding evacuation routes and safe areas. To establish protocols and the schemes for tourist evacuation to safe areas, it is necessary to gather their likely behavior during an evacuation. Since there are few actual data available we conducted a VR (Virtual Reality) experiment assuming a sudden disaster situation and estimated tourists’ route choice based on the experiment. In the experiment pictures of intersection in the touristic Higashiyama area of Kyoto, Japan, where shown to participants and they could choose the direction they want to proceed until reaching an open space or designated shelter. As a result, we could quantify the impact of road width and, to some degree, network structure. The results reveal the tendency to select wide roads and to proceed straight. If the participants were put under time pressure these tendencies are intensified. Utilizing these results we constructed an evacuation simulation. We estimated the distribution and amount of tourists using data obtained from a mobile phone service provider. We conducted the simulation using VisWalk with various guidance situations and compared those results. The results illustrate potential capacity bottlenecks of designated shelter locations and the importance to provide route guidance and certain points in the network.

Assessment of water quality based on biological indices of macrobenthos: a river under pressure from tourism activities

Cijulang River is one of the leading ecotourism objects in Pangandaran, West Java Province, Indonesia. However, the river has a variety of activities that can increase the water pollution in the river such as Green Canyon cliffs tourism, ecotourism of mangrove conservation, housing, and industrial siting. Macrobenthos is one of the bio-indicators that can assess the rate of water pollution in rivers, especially their organic pollutants. Therefore, this research aims to determine water pollution status in Cijulang River Tourism by comparing various biotic indices. The study was conducted at four site sampling locations from upstream to downstream in the rainy season period and dry season period using different methods namely, line transect model, water quality assessment by biological indexing (diversity, species dominant, and family biotic), species deficit, and organic measurement. The research showed 5873 macrobenthos and divided into 27 species with an average abundance of 167 ind.m-2 and are mainly dominated by gastropod species Faunus ater (40%). They are extreme species that can live in high organic pollution and water salinity. This divided the research of quality water assessment of Cijulang River into three categories as follows: slightly polluted (score 36-46) at Green Canyon site, moderately polluted (score 50-60) at Boat Shelter and Muara Cijulang location, and highly polluted (score 66) at Nusawiru site.Keywords:RiverBio-indicatorOrganicAquatic pollution

Decoupling natural and man-made impacts on the morphologic and sedimentologic changes in the tidal flats, Saemangeum area, west coast of Korea: Implications for benthic ecosystem stability

The morphodynamics of tidal flats responds mainly to the nonlinear interaction between tides and seasonal wave activity. Man-made activities such as reclamation further complicate the morphodynamics by disturbing physical processes acting on the tidal flats. Decoupling the anthropogenic influence from the natural forcing on the tidal-flat morphodynamics is crucial in assessing the adverse effects of man-made activities. Still, it remains a challenge due to inherent difficulties in characterizing spatiotemporal variability of the tidal-flat morphology. A three-year-long field survey using unmanned aviation vehicle (UAV)-assisted photogrammetry, sedimentological and benthic fauna data was conducted on the Shinsi tidal flats near the Saemangeum dike, west coast of Korea, to evaluate the relative significance between natural and anthropogenic influence on the morphologic changes of the tidal flats and benthic community structures. The Shinsi tidal flats exhibited non-seasonal sedimentation patterns and experienced overall erosion despite their sheltered location from the offshore waves. The Saemangeum dike contributed to the sustained erosion by reflecting offshore waves toward the tidal flats during winter to spring. Heavy rainfalls also promoted erosion of the tidal flats in summer. The small-scale embankments complicated the spatial sedimentation trend by protecting tidal flats from offshore waves or promoting erosion with shoaling waves. Notable mud deposition occurred during winter, incompatible with the general hydrodynamic condition, resulting from intensive dredging activity inside and outside the Saemanguem dike. The proliferation of the opportunistic species followed the mud deposition for several months until the enhanced wave activity removed the muddy sediments from the flats. Overall erosion dominance and the temporary occurrence of opportunistic species imply that the Shinsi tidal flats are subject to non-seasonal changes in sedimentology and morphology due to artificial structures and man-made activity, leading to the instability of the benthic communities in the tidal flats.

Spatial distribution of sea turtles on South Atlantic subtropical reefs

Environmental conditions have a strong influence on sea turtle population dynamics. Sea turtles spend most of their lives in foraging areas; however, there is a lack of information on how oceanographic and biological parameters determine habitat use and density. Here, we estimated density of green turtles Chelonia mydas and hawksbill turtles Eretmochelys imbricata in a South Atlantic foraging area (Arraial do Cabo, Brazil). We also investigated the influence of environmental variables (wind fetch, temperature, depth, and visibility) and benthic composition on the distribution of turtles. Surveyed sites were split between a colder, more wave-exposed location (western), and a warmer, more sheltered location (eastern). To ensure that these mobile and sparsely distributed species were adequately surveyed, underwater visual censuses (timed transects) were conducted. Sea turtle densities were significantly different between warm/sheltered and cold/wave-exposed locations. C. mydas were almost 10 times more frequently sighted than E. imbricata. The local distribution of E. imbricata mirrored large-scale latitudinal patterns, where this tropical species is dominant on warmer reefs (similar to habitat conditions found at the eastern location). It was not possible to assess the environmental influence on E. imbricata sightings due to their low density. C. mydas were frequently sighted in the cold/exposed sites and negatively correlated with depth. Overall, the density of E. imbricata and C. mydas suggests that Arraial do Cabo is an important feeding ground in the western Atlantic Ocean. This study highlights that visual census can produce reliable density estimates of sea turtles in foraging areas.

Multi-criteria decision making for city-scale infrastructure of post-earthquake assembly areas: Case study of Istanbul

Assembly areas are first gathering places after earthquakes, and provide temporary sheltering. However if these areas have greater risks after earthquakes, they become more deadly. Current studies commonly look for evacuation shelter and temporary housing location models but most of them are not suited to assembly areas. This study aims to determine safe post-earthquake assembly areas by using the multi-criteria decision-making approach through an analytical hierarchy process using a geographical information system. 15 criteria were defined to evaluate the suitability in terms of spatial, natural structure and accessibility of each potential open space for emergency gathering. Following these criteria, possible areas were mapped, evaluated and scored with thematic hazard maps by using geographic information system in a case study to demonstrate the model. Finally, suitability layers were superimposed to estimate the safe assembly areas index and produce the city-scale infrastructure map. As a result, 107 assembly areas were designated for seven neighborhoods in Istanbul. Study results show that not every open area is safe to be a post-earthquake assembly area. The proposed method can provide useful information that could assist in earthquake disaster mitigation, and help government decisionmakers support further location allocation optimization of safe assembly areas.

A Flood Damage and Shelter Need Assessment: A Case Study of Mueang Sing Buri, Thailand

Flooding is one of the main disasters in Thailand and Mueang Sing Buri is among those areas hit. Located on the Chao Phraya River Basin, in the central region of Thailand, the area receives a large amount of runoff during monsoon seasons which causes frequent flood disasters. The aims of this research are to create a flood hazard map and to estimate the number of people that may need shelter after the occurrence of a flood, and to evaluate whether the shelter capacity is adequate in Mueang Sing Buri. To explore the potential locations of emergency shelters, the relevant information related to flooding was initially recorded, such as building detail, flood depth, elevation map, and flood risk map. The available space of each building varies by the characteristics of building types. The calculation of shelter capacity thus depends on characteristics of the buildings, accessibility, and percent of vacant area. The emergency shelter assessment benefits many sectors in the design of preparation plans for hazard management.

Penentuan Penampungan Korban Banjir Di Kecamatan Laweyan Kota Surakarta Berbasis Sistem Informasi Geografis

One of the anticipation actions that can be done before the flood disaster comes is to determine the evacuation route and evacuation location or shelter for flood relief and spread to the public in order to accelerate the process of evacuation of disaster victims so as to minimize losses from the flood itself. This research was conducted by approaching Geographic Information System (SIG) The purpose of this research is (1) Knowing the flood-prone agihan in Laweyan Subdistrict based on SIG. (2) Analyze the Availability of Shelter Locations (Educational Buildings and Buildings of Worship) of flood victims in Laweyan Subdistrict. It is expected that in the research to know the potential of the best temporary evacuation shelter / protection and evacuation design so that it can be considered and help the relevant agencies, especially local BPBD in order to improve flood mitigation in Sumber Village, Banjarsari District, Surakarta City. To reduce or overcome the impact caused by flood disasters on the comfort and safety of the community in Laweyan Subdistrict, researchers need to raise the title, " Determination of Flood Victim Shelter in Lawean District of Surakarta City Based on Geographic Information System".

The impact of surface currents on the wave climate in narrow fjords

This study investigates the effect of surface currents on wind-generated waves in a complex coastal system with narrow fjords. The simulations are based on a phase-averaged wave model forced with surface currents from a high-resolution coastal ocean and fjord circulation model, and high-resolution winds from a nested atmospheric model. Wave simulations with and without ocean forcing are evaluated by comparing integrated wave parameters and modelled spectra with observations from five wave buoys. The comparison covers three winter seasons (2017–2020) and a case study. The wind sea part of the spectrum is better simulated at all locations when using the current forcing. At the most sheltered location, where wind sea dominated the wave climate, the wave height estimates improved by 12 percentage points when including current forcing. Spectral moments and the shape of the average spectra are also improved at most of the locations when current forcing is applied. The effect of wave–current interactions was found to be more pronounced at inner locations where the relative difference of spectral bandwidth is up 5%, the difference in directional spreading is greater than 5 degrees during strong surface currents, and the relative difference in peak frequency is exceeding 10%. Our results are consequential for narrow, deep and sheltered water bodies, but are not expected to carry over to shallow water areas.

Shelter-Based Integrated Model Is Effective in Scaling Up Hepatitis C Testing and Treatment in Persons Experiencing Homelessness.

Hepatitis C virus (HCV) prevalence is high among people experiencing homelessness, but barriers to scaling up HCV testing and treatment persist. We aimed to implement onsite HCV testing and education and evaluate the effectiveness of low‐barrier linkage to HCV therapy among individuals accessing homeless shelters. HCV rapid testing was performed at four large shelters in San Francisco (SF) and Minneapolis (MN). Sociodemographic status, HCV risk, barriers to testing, and interest in therapy were captured. Participants received information about HCV. Those testing positive underwent formal HCV education and onsite therapy. Multivariable modeling assessed predictors of receipt of HCV therapy and sustained virologic response (SVR). A total of 766 clients were tested. Median age was 53.7 years, 68.2% were male participants, 46.3% were Black, 27.5% were White, 13.2% were Hispanic, and 57.7% had high school education or less; 162 (21.1%) were HCV antibody positive, 107 (66.0%) had detectable HCV RNA (82.1% with active drug use, 53.8% history of psychiatric illness), 66 (61.7%) received HCV therapy, and 81.8% achieved SVR. On multivariate analysis, shelter location (MN vs. SF, odds ratio [OR], 0.3; P = 0.01) and having a health care provider (OR, 4.1; P = 0.02) were associated with receipt of therapy. On intention to treat analysis, the only predictor of SVR when adjusted for age, sex, and race was HCV medication adherence (OR, 14.5; P = 0.01). Conclusion: Leveraging existing homeless shelter infrastructure was successful in enhancing HCV testing and treatment uptake. Despite high rates of active substance use, psychiatric illness, and suboptimal adherence, over 80% achieved HCV cure. This highlights the critical importance of integrated models in HCV elimination efforts in people experiencing homelessness that can be applied to other shelter settings.

Deep Neural Network-based Optimization Framework for Safety Evacuation Route during Toxic Gas Leak Incidents

Evacuation planning is important for reducing casualties in toxic gas leak incidents. However, most evacuation plans are too qualitative to be applied to unexpected practical situations. Here, we suggest an evacuation route proposal system based on a quantitative risk evaluation that provides the safest route for individual evacuees by predicting dynamic gas dispersion with a high accuracy and short calculation time. Detailed evacuation scenarios, including weather conditions, leak intensity, and evacuee information, were considered. The proposed system evaluates the quantitative risk in the affected area using a deep neural network surrogate model to determine optimal evacuation routes by integer programming. The surrogate model was trained using data from computational fluid dynamics simulations. A variational autoencoder was applied to extract the geometric features of the affected area. The predicted risk was combined with linearized integer programming to determine the optimal path in a predefined road network. A leak scenario of an ammonia gas pipeline in a petrochemical complex was used for the case study. The results show that the developed model offers the safest route within a few seconds with minimum risk. The developed model was applied to a sensitivity analysis to determine variable influences and safe shelter locations.