Igo Southeast Asia Maps Download
Sandrine Willert
The global human population is projected to increase from 7 billion to over 9 billion between 2011 and 2050, with much of this growth concentrated in low income countries [1]. The greatest concentration in growth is set to occur in urban areas, disproportionately impacting Asia where half of the population is expected to be living in urban areas by 2020 [1]. The effects of such rapid demographic growth are well documented, influencing the economies, environment and health of nations [2]. To measure the impact of this population growth there is a need for accurate, spatially-explicit, high resolution maps that correctly identify population distributions through time.
The absolute error of the different population maps for Cambodia is shown in Figure 4. The AsiaPop method, in general, produces more accurate results, with many more administrative units showing low error values compared to the GRUMP and GPW methodologies.
While it remains difficult to validate large-scale population distribution datasets, given that no independent sources exist at a global scale [19], the accuracy of population maps can be assessed if there exists a reference dataset at a finer spatial resolution than maps generated [10], [15], [44], [45]. Using different administrative levels, we have shown here that the AsiaPop method was the most accurate modelling method for the redistribution of population counts compared to existing replicable approaches. The lower RMSE (Table 2) of the AsiaPop method indicates a better overall fit of the model. The smaller difference between RMSE and MAE values for the AsiaPop method suggests this approach also has less variability in errors.
Given the speed with which population growth and urbanisation are occurring across much of Southeast Asia, and the impacts these are having on the economies, environments and the health of nations, this study outlines a timely and relevant approach for providing national level population distribution data. Additionally, the Southeast Asian region has a range in spatially-detailed census aggregations providing a good basis for further testing and validation of the dasymetric modelling approach that relies on relationships between land cover and population density to redistribute population distribution in a spatially-explicit manner. The approach was designed with an operational application in mind, using simple and semi-automated methods to produce easily updatable maps as new censuses and ancillary datasets become available. Population datasets for 2010 and 2015 are freely available as a product of the AsiaPop Project and can be downloaded from the project website: www.asiapop.org.
A full set of data sources and acknowledgments are provided on the AsiaPop website (www.asiapop.org). Beyond these, we wish to thank the reviewers for their time and comments which greatly improved the manuscript during the publication process.
Enterovirus A71 (EV-A71) is a non-enveloped virus possessing 4 capsid proteins: VP1-VP4. The outermost capsid protein, VP1, plays roles in both antigenicity and virulence of the virus. The concept of generating other EV-A71 genotypes of reverse genetics (rg) viruses by replacing VP1 can be made possible with synthetic biotechnology, allowing us to redesign organisms, creating unavailable ones. To determine suitable vaccine candidates against EV-A71 infections, we combined synthetic biotechnology, rg-virus production and high-fidelity determinants to produce genetically stable viruses. With the use of antigenic cartography, we are able to view the antigenic distance among various points. We analyzed and generated various EV-A71 VP1 sequences from Taiwan and Southeast Asian (SEA) countries, which were then used to produce recombinant rg-viruses and the viral proteins were purified for immunization of mice and rabbits. Antisera against various EV-A71 genotypes were used in neutralization assays against various Taiwan and SEA EV-A71 genotypes. Based on neutralization data from mice and rabbit antisera, we found that antisera produced from several genotypes were able to effectively neutralize the various Taiwan and SEA EV-A71 genotypes. Additionally, comparing the antigenic maps produced from mouse, rabbit and human antisera against different EV-A71 genotypes, a difference in clustering was seen and the spacing between points also differed. Based on antigenic mapping and neutralizing activities, B4 7008-HF and C4 M79 may be good potential vaccine candidates against EV-A71.
Amazon Location Service adds a new data source in Southeast Asia, GrabMaps, offering maps, search, and routing. Developers building applications in Southeast Asia can display their data on local up-to-date maps, use search boxes to locate end-user addresses and points of interest, and calculate routes using real-time traffic conditions.
Amazon Location Service is a location-based service that helps developers easily and securely add maps, points of interest, geocoding, routing, tracking, and geofencing to their applications without compromising on data quality, user privacy, or cost. With Amazon Location Service, you retain control of your location data, protecting your privacy and reducing enterprise security risks. Amazon Location Service provides a consistent API across a range of location-based service data providers (Esri, HERE, Open Data Maps, and GrabMaps), all managed through one AWS console.
LD variation and population-specific recombination rates at CDKAL1. The extent of LD variation between pairs of SGVP and HapMap populations at the CDKAL1 gene, with separate LD heatmaps and recombination rates estimated from genotype data at each population. Population-specific recombination rates are shown except for CHB and JPT, where the same HapMap estimated recombination rates for JPT+CHB are used.
Grab is the largest delivery organization in Southeast Asia, with millions of driver partners and customers. Their subsidiary, GrabMaps, creates up-to-date mapping data in those countries/regions for their own use, and others. Amazon Location Service uses GrabMaps' location services to help AWS customers use maps, geocode, and calculate routes effectively. GrabMaps' location services are built to provide high-quality, authoritative, and ready-to-use location data, specifically for southeast Asian countries.
The platform provides users with extensive options to view and research the 1,437 digitised maps. Maps can be easily selected by period and collection. The historical maps can be viewed as a projection on a contemporary map of the same area. The way the maps are displayed can be easily adjusted using the geo-reference tool. Users can also search and filter by language, country and region, land use and buildings in the area, such as forts, villages, towns, palaces, trade and industry in the form of factories, markets, shopping areas and agriculture including crops, mining, plantations, fishing, etc. In addition, the maps can be consulted for cultural and political regions, environmental and landscape features such as mountains, volcanoes, reefs, jungles, wildlife, climate and rainfall. The maps are also searchable for technical aspects such as scale, latitude and longitude, compass roses and annotations. Furthermore, the maps have been made searchable by map maker, publisher and place of publication.
Various aspects of maps can be consulted via special 'MapJourneys', including cartouches, illustrations, coats of arms and insert cards. In addition, sub-regional maps can be viewed and attention is paid to travel routes and networks, including postal routes, train, tram and telegraph connections and shipping routes.
The UBL made 593 digitised maps available for the online platform Historical Maps of Southeast Asia. These maps were selected from the cartographic collections of the Royal Tropical Institute (KIT) and the Royal Institute of Linguistics, Land and Ethnology (KITLV), which have been managed by the UBL since 2013 and 2014. Both collections mainly focus on maps of the former Dutch colonies: Indonesia, Suriname and the Antilles. In addition, some maps from the UBL Bodel Nijenhuis collection were made available. This collection forms the foundation for the UBL cartographic collection and was built by Johannes Tiberius Bodel Nijenhuis. Upon his death in 1872, Bodel Nijenhuis bequeathed his vast and varied collection of maps and atlases to the UBL, including hundreds of unique, hand-drawn maps. Over the course of a century and a half, the collection received numerous additions through donations and purchases. At the end of 2021, the donation of the extensive private collection of John Steegh and Harrie Teunissen was added. With a total of approximately 120,000 historical maps and atlases, the UBL manages one of the largest cartographic collections in the Netherlands with an international focus.
It's been some time since we last released a set of infographic maps! Since Asia is a huge continent, we're focusing this time on the Southeast zone. Create a presentation where you talk about demographics, geography, food, culture or religion and include our infographics to visually support the data. These countries attract lots of tourists, so you can use the infographics for business, not just for education!
Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented.
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