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14 results for “refugee camps”
Supplementary material for the publication: J.D. Nixon, K. Bhargava and E. Gaura, Energy Performance Gap in Community-Based Solar Energy Interventions: Lessons from two Rwandan Refugee Camps, 2020
<p>The dataset deposited here was prepared under the EPSRC-funded <a href="http://heed-refugee.coventry.ac.uk/">Humanitarian Engineering and Energy for Displacement</a> research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities, create an evidence base on the usage of different energy interventions and provide recommendations for improved design of future energy interventions to better meet the needs of people. </p> <p>As part of the project, we deployed a Standalone Solar System for a Community Hall in Nyabiheke camp, Rwanda, and a PV-battery Microgrid in Kigeme camp, Rwanda. The microgrid supplies power to a playground and two nursery buildings. It powers a total of 20 CPE (each with 3 LEDs) and 10 sockets. The standalone system at Hall powers 7 CPE (with 3 LEDs each) and 4 sockets. The aim of the study was to (a) understand the energy consumption behaviour, light usage and other enabled uses within the set location in each camp (b) create an evidence base on the value of energy and its benefits in displaced contexts (c) identify best practice in the construction, control and operation of the respective systems as a shared energy resource.</p> <p>The system data used for the performance analysis for this study (July 2019 and March 2020) is deposited here along with the metadata. The results from analysis are presented in a paper titled '<strong>Energy Performance Gap in Community-Based Solar Energy Interventions: Lessons from two Rwandan Refugee Camps</strong>' (currently under submission). The scripts for analysis can be found at our Github account <a href="https://github.com/cogent-computing">Cogent Labs</a> under HEED-Microgrid and HEED-Hall repositories.</p>
Data to support the publication "Unknown risk: assessing refugee camp flood risk in Ethiopia"
<p>This dataset supports the publication "Unknown risk: assessing refugee camp flood risk in Ethiopia". This dataset contains the delineated boundaries for 24 refugee camps in Ethiopia. Also included are refugee camp building footprint data (where available). All datasets are in shapefile format.</p>
Data and code for Decoding dynamic landslide hazard processes for a massive refugee camp (KTP) in Bangladesh
<p>The codes have been implemented using R 4.4.0. Landslide priority zonation using Monte Carlo simulation is implemented in Google Colab.</p> <p>A Dynamic Landslide Hazard Assessment has been conducted using a Generalized Additive Model (GAM). The results of the GAM are also compared with standard machine learning algorithms (MLs): NNET, RF, LDA, xgBoost, and SVM.</p> <p>The code is jointly developed by Dewan Haque and Ritu Roy, with collaboration from many others. The GAM code is an update from the study published by Zhice, F. (2023), <a href="https://doi.org/10.5281/zenodo.10395153" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10395153</a>, adapted to apply it across settings. The ML code has been developed from scratch.</p> <p>The required data from intensive fieldwork and satellite image analysis is uploaded here to reproduce the results. Additionally, R Markdown files are provided.</p> <p>The ReadMe file here, as well as on GitHub, will be useful for further instructions.</p> <p>GitHub Link: https://github.com/Dewan-cpu/Decoding-Landslide-Hazard-Assessment</p>
Rohingya Refugee Camp Fuel Load Dataset (Camp 4Ex, 5, KRC)
<p>A comprehensive survey was conducted on July 2, 2022, to prepare the fuel inventory map featuring dwelling structure, fuel load density, placement of fuel etc. In the 5-day long survey, three camps having contrasting fuel inventory have been examined. They are- Camp 4 Extension (Ex), Camp 5 and Kutupalong Registered Camp (KRC). These camps were selected based on the following features :</p> <ul> <li>Being the youngest of all the camp in Kutupalong, Camp 4 Ex followed a standard design and an average separation distance of 7m.</li> <li>On the other hand, Camp 5 is densely populated, having no visible space between two dwellings. It was one of the largest camps with a population of almost 25 thousand. The Rohingya community there are as equally impoverished as those living in Camp 4 Ext. The shelters of both of these camps are made of cellulose based structure material like wood, bamboo, timber etc., but the dwellings of camp 5 don’t follow any standard design.</li> <li>With a sharp contrast, dwellings in KRC follow a shaded structure consisting of six dwellings under one roof but separated by brick wall or corrugated steel sheet. KRC began informally in 1991, making it the oldest of all camps and its dwellers somewhat self-sufficient. A lot more permanent structure e.g., wooden furnitures, bed, wardrobe, showcase has been found here, increasing its fuel load larger than that of Camp 4 Ex and 5.</li> </ul>
Business load profiles used in "Maximising the benefits of renewable energy infrastructure in displacement settings: Optimising the operation of a solar-hybrid mini-grid for institutional and business users in Mahama Refugee Camp, Rwanda"
<p>Version used in the submission of "Maximising the benefits of renewable energy infrastructure in displacement settings: Optimising the operation of a solar-hybrid mini-grid for institutional and business users in Mahama Refugee Camp, Rwanda" by Hamish Beath, Javier Baranda Alonso, Richard Mori, Ajay Gambhir, Jenny Nelson and Philip Sandwell.</p>
Refugee Camp Flood Risk - NASA ARSET Training Data
<p>This upload contains data and documentation to complete the practical exercise in <em>Part 1 - Assessing Flood Risk in Refugee Camp Settings</em> of the NASA ARSET <em>Earth Observations for Humanitarian Applications </em>training programme. Further details can be found at http://appliedsciences.nasa.gov/get-involved/training/english/arset-earth-observations-humanitarian-applications</p>
Exploring risk factors and antimicrobial susceptibility patterns associated with bacteriuria among Syrian refugees in makeshift camps
<p><span>Database and code necessary to replicate the analysis.</span></p>
Mother and Child Education Program in Palestinian Refugee Camps
ClinicalTrials.gov study NCT02402556. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: A refugee camp in the center of Europe: clinical characteristics of asylum seekers arriving in brussels
Open the record for dataset details and reuse information.
Shelter Level Fire Hazard Risk of the Rohingya Refugee Camps, Cox's Bazar, Bangladesh
Open the record for dataset details and reuse information.
Malaria Survey in the Tak Province Refugee Camps
ClinicalTrials.gov study NCT01902797. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Study of Chest Infections in Infants Living in a Refugee Camp on the Thai-Burmese Border
ClinicalTrials.gov study NCT00894764. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Sentinel-1 and Sentinel-2 database for refugee camps detection
<p>This database was generated by AGENIUM Space in the framework of the CORTEX project (https://esacortexproject.agenium-space.com/) funded by ESA.</p> <p>Database of pairs of Sentinel-1 and Sentinel-2 images (https://www.copernicus.eu/en, https://scihub.copernicus.eu/) which contain the same region where a refugee camp (from those identified by the UNHCR) is present. Original Copernicus images were acquired between 2017 and 2019.</p> <p>The Sentinel-1 images come from the IW mode and are GRD product from both ascending and descending orbits. The Sentinel-2 images are surface reflectance products (L2A). The initial targeted application is to perform style transfer to generate a Sentinel-2 lookalike from a Sentinel-1 image. The database focuses on refugees’ camps in the Middle East area. As said, the locations of 39 camps were retrieved from the UNHCR (United Nations refugee agency) website (https://www.unhcr.org/).</p> <p>More details are provided in attached document S1-S2-RefugeeCamps-DB-description.pdf</p> <p>This work is funded by a contract in the framework of the <strong>EO SCIENCE FOR SOCIETY</strong> PERMANENTLY OPEN CALL FOR PROPOSALS EOEP-5 BLOCK 4 issued by the European Space Agency.</p>
Dietary Habits of Saharawi Type II Diabetic Women Living in Algerian Refugee Camps: Relationship with Nutritional Status and Glycemic Profile
<p>Diabetes is one of the main health problems among Saharawi refugees living in Algerian camps, especially for women. As is known, diet plays an important role in the management of diabetes. However, the dietary habits of Saharawi diabetic women are unknown. Therefore, we investigated the dietary habits and established their relationship with the nutritional status and glycemic profile of such women. We recruited 65 Saharawi type II diabetic women taking orally glucose-lowering drugs only. Dietary habits were investigated using qualitative 24 h recall carried out over three non-consecutive days. Anthropometric measurements were taken and blood parameters were measured. About 80% of the women were overweight and about three out of four women had uncompensated diabetes and were insulin resistant. The Saharawi diet was found to mainly include cereals, oils, sugars, vegetables (especially onions, tomatoes, and carrots), tea, and meat. Principal component analysis identified two major dietary patterns, the first one "healthy" and the second one "unhealthy". Women in the higher tertile of adherence to the unhealthy dietary pattern had a higher homeostatic model assessment for insulin resistance (HOMA) index (b = 2.49; 95% CI: 0.41-4.57; <em>p</em> = 0.02) and circulating insulin (b = 4.52; 95% CI: 0.44-8.60; <em>p</em> = 0.03) than the women in the lowest tertile. Food policies should be oriented to improve the quality of diet of Saharawi diabetic women.</p>
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