Download USA free DEM 10 meters Digital Elevation Model


1.7 million buildings mapped to fight malaria in Southern Africa, Central America, and Southeast Asia

Pentru cei interesati, desigur! Atentie, implica voluntariat:

Over the past few months, nearly 3,000 contributors have traced almost 1.7 million buildings, in a coordinated effort to map 500,000 km² of the malaria-affected world.

Volunteers use satellite imagery to trace buildings and add them to OpenStreetMap, creating a dataset which can be used by health programs in Southern Africa, Central America, and Southeast Asia to inform prediction models, target surveillance, and deploy resources within communities.

Explore 1.7 million buildings contributed by over 3000 mappers

On World Malaria Day, we recognize all of the remarkable work that’s been done so far, and gear up for the final push as our community seeks to complete this mapping initiative in full.

The mapping began last year with Visualize No Malaria, a partnership between Zambia’s Ministry of Health, PATH, the Tableau Foundation, and a coalition of tech partners. Digital Globe, the Clinton Health Access Initiative and the Humanitarian OpenStreetMap Team expanded the fight to a half million square kilometers. Groups like Missing Maps, YouthMappers, and the Peace Corps have also made significant contributions to the mapping lift. Here at Mapbox, we have been proud to support the effort with technical guidance and mapping.


Explore Livingstone, Zambia

Lukas developed this visualization to highlight the progress over the last several months. Dig into the code to see how he pulled together the data using GL JS and tippecanoe.

Learn how you can help us finish mapping all 500,000 km²!

GIS/Map Providers Compared: Integration?

Pentru cei interesati:

Question: There is a growing demand for maps and GIS to integrate with popular business platforms (BI, CRM, EAM) and data. Does your offering play well with other non-GIS/mapping systems?

Pitney Bowes

We approach this kind of integration in two ways. With the growing investment by BI companies to provide more mapping functionality with their solutions we will augment those applications with better visualization functionality. Many BI software providers won’t invest in advanced spatial analysis as that’s not their core competency. For those users of BI products that need advanced visualization beyond simple thematic mapping we offer contouring, point cluster mapping, and advanced spatial querying. Second, as mentioned above, Pitney Bowes is a data company. As such, we want to supply users with the data products that facilitate their location analytics. For example, IBM is a client for our data and software. IBM represents how Pitney Bowes is supporting their users with embedded geospatial technology.


Yes, we are fully interoperable with BI and other products. Our platform (CARTO Engine) was built from the ground up to let developers (end customers or 3rd party integrator’s) expose CARTO to end users through our API and SDK. We have a Spatial REST API, a Mobile SDK and a GEO UI Framework (CARTO.JS).


Actually, one of the main reasons we don’t see more users utilizing mapping in their daily decision-making process is that companies didn’t have enough resources, knowledge and time to adopt and integrate their solution BI, CRM and EAM with GIS systems. With GIS Cloud a lot of companies can finally afford to introduce that spatial aspect to your existing data, that is necessary for better understanding of your assets and processes.

Our main product is our platform that allows you to integrate with any non-GIS/mapping systems in the market where you focus on the tools you need and we do the heavy lifting for you by making sure everything else runs smoothly.


Yes! The Boundless offering does support integration with third party non-geospatial applications. The beauty of our technology being based on open source, the interoperability that is provided with OGC and open standards allows powerful and easy integration’s with other business systems.

For example, Tableau integrates with open standard web services (WMS) and provides a step-by-step tutorial of how to integrate with the Boundless open source GIS technologies. We see this with many more BI, CRM, and EAM solutions, and are only going to see the trend of integration using open standards continue to gain popularity.


Yes, ArcGIS integrates well with these and other enterprise systems. Geolocation (e.g., placing your assets and people onto facilities maps and indoor maps) is rapidly being used to extend systems like Business Intelligence, CRM and EAM. At Esri, we believe that these applications require a geospatial framework to help organize and exploit these valuable information assets and to protect customers as well as employees, especially as these systems grow in sophistication and increase their adoption of IoT and data feeds.

For example, Esri teams with companies such as Microsoft, IBM, Salesforce, SAS, and SAP to integrate ArcGIS technology and information inside, along with strong support for extending ArcGIS integration more deeply. CRM and EAM systems integrate ArcGIS and asset maps as key components – location plays a critical role in these systems.


Mapbox has a commercial focus. Modularity is an important design paradigm. This lends itself well to integration with other non-GIS platforms. BI and analysis are important. We are used as a visualization layer by many platforms including Tableau, Cognos, Qlik and MapD.


Yes Mango plays extremely well with business platforms and we offer several paths of integration that can be configured without the need to be a tech wizard.

It’s easy to create links from feature popups back to business systems. Our interface allows you to insert an attribute value into a URL when a feature is selected. E.g.

Mango will take the ID from the attribute data of the selected feature and insert it into the URL so users can navigate from the selected feature to the business system.

These links work both ways, users can create links from their business system to the relevant feature in Mango. E.g.

In the business system we just insert the layer name, attribute field (column) and attribute value and Mango will automatically open the map at that location with the feature highlighted and centered on the map and the attribute popup visible.

Also using our Dropbox integration feature it’s possible to automatically sync the data from the business system with your map. You can simply have your business system export a spreadsheet (CSV format) of the most up to date data at a set interval into a Dropbox folder on your computer or server that has been linked to Mango. Mango will then automatically pull in the updated data and update your maps.

Google Maps vs OpenStreetMap: Which is the Best Web Mapping Service?

Un mic ghid pentru a va ajuta in alegerea celui mai bun serviciu de webmapping: Google Maps vs OSM. Si eu ma intreb mereu care e mai bun? Pe care sa il aleg?

As a cartographer, you actually have an option as far as maps are concerned, but the solution isn’t so clear like was in the past. Google’s maps remain the king; however, OpenStreetMap is becoming a force to reckon with, getting more popular among different applications as well as services.
While one can find a comparison between the both community mapping programs, which one is really the preferred alternative to commit one’s scarce resources and precious time into if one desires to see his crazy mapping skills get projected on the internet?


1. Coverage

In terms of coverage, Google map has a higher coverage in many countries. As a matter of fact, it is the leading map in many countries which include the United States, Germany, and Japan and over 220 countries. OpenStreetMap, on the other hand, has a very poor coverage in most countries, there are instances where many important places such as hospitals, government buildings, parks etc. will be missing from the map and the individual will have to edit to include the missing places. Google Map is very detailed in its coverage, down to the smallest streets and shops. In website categories, Google map is also ahead of Open Street Map in many categories including arts, shopping travel, business and more than 200 other categories.

2. Ownership

While Google Map is copyrighted and owned by different organizations, OpenStreetMap is fully owned by you; the user, both the data and software are the property of the contributors. The organization is known as Open StreetMap Foundation only exists in order to develop, promote, support and protect the project.

3. Imagery satellite updating frequency:

It’s over and over again asked how often Google updates the imagery in Google Maps and Google Earth. The answer depends on where you live and can be anywhere from once a week to never. For much of the world, there are certain hotspots that get fairly regular updates and other places that have no high-resolution imagery whatsoever.
When it comes to OpenStreetMap, they don’t update satellite imagery, ever (for lack of satellites). They use imagery from third-party providers that have granted permission to them; Yandex and Google are not among them. In most parts of the world, the best imagery available to them is either Bing or the MapBox satellite imagery, and OpenStreetMap has no influence on when they update.

4. Cost of use

Though Google map is free, there are certain charges incurred when one makes use of Google mapping services. There is the cost of privacy in addition to not being able to control whatever is displayed on the map. OpenStreetMap, on the other hand, is totally free with no hidden cost and charges.

5. Closed System versus Open System

The most notable distinction between Google Map and OpenStreetMap is in the manner it handles the information you input into it, which can have an influence on your choice about which one to work with. OpenStreetMap styles itself as an open data source, which means that anyone or organization can use the map information present in OpenStreetMap.
On the other hand, Google Map is a close system. Every bit of information you put in ends up being a property of Google and you are reminded of this fact on the constantly enthralling Terms and conditions page.

6. Swiftness of updates

google maps maker
For somebody only just starting out mapping, you’ll wish to find the improvements you make without delay, right? Google Map allows you to immediately see your edits, however, it cautions that your change will have to be analyzed before it’s formally included. Strangely enough, even though it’s your first alteration to a map, you are able to evaluate other people’s edit. As a matter of fact, reviewing others’ edits is a way to get your alteration evaluated faster. But then, you have no idea of how long this evaluation.

7. Localized location of names

Google map tends to be very intelligent by showing the local names of places when available. For instance, A French name written in English makes little or no sense. This functionality in Google Maps helps to make the map very easy to read. In OpenStreetMap, this functionality is poorly implemented.

8. Design/Color scheme

In terms of design /color scheme, Google map has a more attractive interface; this is not unconnected to the fact that Google has the resources to hire good mappers/ designers for the job. With Google Map, you can easily distinguish the different parts of the map immediately. The reason for this attractive interface is because Google makes use of different colors to denote different objects. OpenStreetMap, on the other hand, uses very few colors to denote different features; hence so many things are not quite easily distinguishable.

9. API for accessing data

Both Google Maps and OpenStreetMap have an API allowing using maps and their data on web pages or applications.
The Google Maps API permits the embedding of Google Maps onto web pages of outside developers, using a simple JavaScript interface. It is designed to work on both mobile devices as well as traditional desktop browser applications. The API includes language localization for over 50 languages, region localization and geocoding, and has mechanisms for enterprise developers who want to utilize the Google Maps API within an intranet.
In October 2011, Google decided to start charging fees for access to the Google Maps API once daily usage limits are surpassed. Every time an Internet user visits a site that uses a Google map, a request is sent to the Google Maps API, and the number of requests made by a given site thus equals its number of visits. The more popular a site or application, the more its risks having to pay in order to continue to display a Google map.

In the other side, to get access to OpenStreetMap data freely from your application, you can use the Overpass API (formerly known as OSM Server Side Scripting); it is a read-only API that serves up custom selected parts of the OSM map data. It acts as a database over the web: the client sends a query to the API and gets back the data set that corresponds to the query.
Unlike the main API, which is optimized for editing, Overpass API is optimized for data consumers that need a few elements within a glimpse or up to roughly 10 million elements in some minutes, both selected by search criteria like e.g. location, type of objects, tag properties, proximity, or combinations of them.

10. Use of their maps by organizations

This website uses open data on the city of Montpellier to geolocate green spaces on an OSM map
This website uses open data in the city of Montpellier to geolocate green spaces on an OSM map

In fact, more and more major organizations are choosing OSM for their maps. In February 2012, Foursquare switched to the OpenStreetMap powered Mapbox platform. In March 2013, Wikipedia started using OSM as well. Craigslist uses it for apartment searches and even Apple has used OSM data in its maps… Other popular platforms using OSM powered maps are Github, Pinterest, Roadtrippers and Strava, to name a few.
There are two main reasons for that. First of all, the flexibility. OSM is ready for any styling you need to apply for your project. The second reason is that OpenStreetMap is and always will be available for free to users, developers and companies.

In conclusion, settling on the appropriate map to use will be finally determined by your specific needs. Google Map is known to be incredibly fast which is essential for mobile performance, tile loading etc. and has significantly better coverage in many areas while OpenStreet Map is known to have better performance in urban centers. Google Map is not that flexible and is only used for online purposes. But with Open StreetMap, the user can download all or some of the map for offline use, either in GIS format. This means that you can safely use OpenStreetMap information to find your way around and not have to reveal your location to anybody.


Using GIS to Understand Species Evolution

Looking at how species may have evolved over time is not usually considered an area where GIS might be applied. However, studies have used spatial modeling and GIS approaches to understanding species evolution.

In one study, the authors studied the evolution of two rodent species by changing the environmental conditions in a given region and studying how that would affect the distribution of rodents based on varied scenarios. The application of spatial models with different initial conditions that produce outcomes are then matched with empirical evidence from the biological record to determine which model conditions best match the distribution for the rodents.[1]

Another study looking at pelobatoid frogs analyzed GIS-based climatic data, with published life-history data of the frogs. The approach utilized a time-calibrated phylogeny. However, the results did not show climate as a major factor in the evolution of the frogs, rather small genome sizes and phylogeny affected by spatial factors were more of a contributing factor to noticeable evolution.[2]

Plant species richness for the Australian continent.  From: Evolutionary speed limited by water in arid Australia, Goldie et al., 2010.

Other studies are utilizing similar methods, such as in studying amphibians, that take advantage of the presence of GIS-based climate data for understanding evolutionary change where climate and phylogenic trait within geographic locations are potentially important factors.[3] Another similar approach was applied on Malagasy primates, where generalized linear models looking at climate and resource-related variables that also accounted for phylogenetic history and spatial autocorrelation determined that a strong phylogenetic effect, once again, had the most influence in evolutionary change, where the effects of space and location were relevant for the specie’s genetic development.[4] These examples demonstrate that spatial modeling and GIS can be used to explain how species evolution has occurred, helping to explain distribution of species in ways that have provided new insights to evolutionary biologists.


[1] For more on the application of modeling to understand rodent species’ distribution, see:  Anderson, R. P., & Raza, A. (2010). The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela: Effect of study region on models of distributions. Journal of Biogeography, 37(7), 1378–1393.

[2] For more on the evolution of pelobaoid frogs and their evolution using GIS, see:  Zeng, C., Gomez-Mestre, I., & Wiens, J. J. (2014). Evolution of Rapid Development in Spadefoot Toads Is Unrelated to Arid Environments. PLoS ONE, 9(5), e96637.

[3] For more on the study looking at amphibians, see:  Bonetti, M. F., & Wiens, J. J. (2014). Evolution of climatic niche specialization: a phylogenetic analysis in amphibians. Proceedings of the Royal Society B: Biological Sciences, 281(1795), 20133229–20133229.

[4] For more on Malagasy primates and studying their evolution using spatial methods, see:  Kamilar, J. M., Muldoon, K. M., Lehman, S. M., & Herrera, J. P. (2012). Testing Bergmann’s rule and the resource seasonality hypothesis in Malagasy primates using GIS-based climate data. American Journal of Physical Anthropology, 147(3), 401–408.