25 April 2018
| Dataset date: April 25, 2018-April 25, 2018
This report explores food insecurity in Nigeria in the context of urbanization and demographic change. A comparison of changing acute food security measures (IPC) from January and February 2010-2018 accompanies the report. The authors, Jordan Burnett, Leah Nadel, Victoria Santiago, and Arline Tarazona, completed their research in partial fulfillment of Public Health coursework in Medical Geography, for Spring 2018, at Drew University. Dr. Lisa Jordan edited the report and supplemented their work with additional spatial data.
17 April 2018
| Dataset date: October 15, 2017-October 15, 2017
Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.
This assessment covers all locations hosting Rohingya population in Cox’s Bazar District in Bangladesh and present needs overview and population information as of 15 October 2017.
All information and findings are included in the attached products including the raw dataset for further reference and analysis. Full report available on humanitarianresponse.info
6 April 2018
| Dataset date: April 04, 2018-April 04, 2018
Ce jeu de données renseigne sur les activités mises en oeuvre par la FAO dans le cadre de sa stratégie de réponse à la crise du bassin lac TCHAD sur la période 2017-2019. Il renseigne sur les activités réalisées , le montant des financements et le nombre personnes vulnérables assistées.
16 March 2018
| Dataset date: March 16, 2018-March 16, 2018
This set of tables is useful baseline information for any organization doing work in Puerto Rico and contains the 79 municipalities (equivalent to counties in the continental U.S.) as well as the corresponding 902 barrios.
14 March 2018
| Dataset date: January 01, 2016-December 31, 2016
Cameroon is currently faced with three simultaneous crises, whose combined effect has severely impacted the most vulnerable communities, threatening their livelihoods and eroding their ability to adapt. According to the latest census issued in October 2016, the number of internally displaced people (IDPs) has increased by more than 115 percent, reaching a total of 199 000 as compared to early 20154. This adds to approximately 259 145 Central Africans and 74,000 Nigerian refugees hosted in Adamaoua, EST, Nord and Far North regions. The food security situation has consequently deteriorated from 19 percent in 2015 to 24 percent in 2016, now affecting nearly 2.5 million people - almost 80 percent of whom reside in the North and Far North regions. Additionally, there are concerns of disease outbreaks, including cholera and measles. These strains on an already vulnerable population have pushed the country into a humanitarian crisis; with some agencies like WFP declaring a Level Three emergency in Cameroon from May to August, and the country remains on alert.
As determined by a recent joint CALP/OCHA mission on 7-11 November 2016, a number of agencies are turning to cash transfers as a modality of delivering aid in hard to reach areas. Cash Based Transfers (CBT) programs have already been implemented in the East and Far North regions in Cameroon by various agencies including: World Food Programme, Catholic Relief Services, International Rescue Committee (IRC), French Red Cross, Premiere Urgence International (PUI), PAJED (MINJEC/GIZ) and Plan International, in the sectors of Food Security and Nutrition, Economic Recovery and Livelihoods and WASH.
23 February 2018
| Dataset date: March 01, 2017-July 31, 2017
This is the minimal underlying dataset for a forthcoming manuscript presenting results from a cross-sectional survey aimed at measuring deaths, injuries, and kidnapping in Mosul households during the 29 months of ISIS control and the 8 months of Iraqi military action during the liberation.
6 February 2018
| Dataset date: May 02, 2016-May 02, 2016
Permite medir la evolución del estado de la educación en Guatemala de manera Municipalizada, está integrado por dos variables educativas: a) la cobertura; que es estimada en cada uno de los niveles desde su valor neto; es decir, el total de niños y niñas que asisten a la escuela con la edad correspondiente, entre el total de los del municipio que tienen esa edad; y b) la terminación: que es relativa al total de niños aprobados en el último año del nivel respecto al total de niños que, en esa edad residen en el municipio.
31 January 2018
| Dataset date: December 29, 2017-December 29, 2017
The Office of the Geographer’s Global Large Scale International Boundary Detailed Polygons file combines two datasets, the Office of the Geographer’s Large Scale International Boundary Lines and NGA shoreline data. The LSIB is believed to be the most accurate worldwide (non- W. Europe) international boundary vector line file available. The lines reflect U.S. government (USG) policy and thus not necessarily de facto control. The 1:250,000 scale World Vector Shoreline (WVS) coastline data was used in places and is generally shifted by several hundred meters to over a km. There are no restrictions on use of this public domain data. The Tesla Government PiX team performed topology checks and other GIS processing while merging data sets, created more accurate island shoreline in numerous cases, and worked closely with the US Dept. of State Office of the Geographer on quality control checks.
Tesla Government’s Protected Internet Exchange (PiX) GIS team converted the LSIB linework and the island data provided by the State Department to polygons. The LSIB Admin 0 world polygons (Admin 0 polygons) were created by conflating the following datasets: Eurasia_Oceania_LSIB7a_gen_polygons, Africa_Americas_LSIB7a_gen_polygons, Africa_Americas_LSIB7a, Eurasia_LSIB7a, additional updates from LSIB8, WVS shoreline data, and other shoreline data from United States Government (USG) sources.
The two simplified polygon shapefiles were merged, dissolved, and converted to lines to create a single global coastline dataset. The two detailed line shapefiles (Eurasia_LSIB7a and Africa_Americas_LSIB7a) were merged with each other and the coastlines to create an international boundary shapefile with coastlines. The dataset was reviewed for the following topological errors: must not self overlap, must not overlap, and must not have dangles. Once all topological errors were fixed, the lines were converted to polygons. Attribution was assigned by exploding the simplified polygons into multipart features, converting to centroids, and spatially joining with the newly created dataset. The polygons were then dissolved by country name.
Another round of QC was performed on the dataset through the data reviewer tool to ensure that the conversion worked correctly. Additional errors identified during this process consisted of islands shifted from their true locations and not representing their true shape; these were adjusted using high resolution imagery whereupon a second round of QC was applied with SRTM digital elevation model data downloaded from USGS. The same procedure was performed for every individual island contained in the islands from other USG sources.
After the island dataset went through another round of QC, it was then merged with the Admin 0 polygon shapefile to form a comprehensive world dataset. The entire dataset was then evaluated, including for proper attribution for all of the islands, by the Office of the Geographer.
30 January 2018
| Dataset date: May 02, 2016-May 02, 2016
Engloba aspectos tangibles e intangibles relacionados a la incapacidad de las personas de tener una vida digna. Los indicadores de pobreza rural evidencian insuficiencia de servicios básicos, falta de empleo, salud y educación.
26 January 2018
| Dataset date: April 01, 2016-June 01, 2016
This is the underlying data for a manuscript published in PLOS: Currents Disasters. The manuscript reports results from a survey of accessible areas, which were largely urban and government controlled, undertaken from April - June 2016 to identify unmet needs and assistance priorities in Syria.