Lets map using ‘StreetComplete’ App

Over time the number of OpenStreamMappers is increasing, almost every day the community is getting new Mappers. Indeed it’s a great news but, a matter of tension as well in terms of data quality because of the no or minimal knowledge of tagging, proper drawing, and the fate or end use of data.Its a great news for us that recently a java based android application has been developed what is suitable for new mappers for collecting data in the field offline. It uses Mapzen vector tiles for display. Thanks to Tobias ZwickStreet_Comp.png

Let me introduce you the application named streetcomplete.

  1. Download it from Google Play Store
  2. When you have an internet connection, find the place where you want to map, then you can stop the internet. you can find the area using your current location using mobile data.
  3. You will find the map tile with different features icon. Tap the icon and fill the answers generating against each feature like road, playground, building, path etc.Street_Comp_2.png
  4. After collecting data, upload your answers using the internet.
  5. Dont forget to authorize your OSM account from settings menu of the app.

Enjoy mapping. ~ AHASAN

N.B: The app is aimed at users who do not know anything about OSM tagging schemes but still want to contribute to OpenStreetMap by surveying their neighbourhood (or other places). Because of the target group, the app only presents issues which are answerable very clearly by asking one simple question, and which involve very few false positives.

Original Post 

iD Editor 2.4.0 : Check out the changes of this new release !!!

iD on browser edit panel

The iD editor is the de facto, browser-based OpenStreetMap editor. It was first launched in May 2013 to ease the editing for the osm contributors. iD is fast and easy to use and allows mapping from various data sources such as satellite and aerial imageries, GPS, Field Papers or Mapillary.

The iD editor is a great way to edit for small and easy changes that don’t require the advanced features of JOSM (a more advanced mapping editor). A detailed tutorial on iD editor is given on LearnOSM iD editor Chapter.

iD editor version 2.4.0 has been released on 25 August 2017 having some remarkable features and bug fixes, such as :
? Release Highlights

? A new global imagery layer: Esri World Imagery.  Esri just made their imagery available for OSM use! (Big thaks to ESRI). Check out the new imagery by opening the Background pane (shortcut B)

? New Features

  • Updates to save workflow :
    • Add review_requested changeset tag and checkbox
    • Add source changeset tag and multiselect field
    • Add hashtags changeset tag, API parameter, and auto fill hashtags from comment
    • Write changeset tags for new mappers to indicate walkthrough progress – These tags all start with ideditor:
    • Write changeset tag for changesets_count – it will contain "0" for someone making their first edit
    • Refactor uiCommit into several smaller modules
  • Add addr:unit input to address field for many countries
  • Make rotation and reflection operations available for more geometry types
  • Change raw tag editor readOnlyTags function to accept array of regular expressions
  • name field is no longer automatically added to every preset
  • Field refactor
    • Add options for fields, allow unwrapped fields (no label, buttons, etc)
    • uiField can now be used anywhere, not just inside the preset editor
    • Rename uiPreset -> uiPresetEditor (consistent with raw tag editor, raw member editor, etc)

✨ Usability

  • In save mode, esc should cancel and return to browse mode
  • Recognize more kinds of concrete surface as “paved”
  • When drawing, ignore accidental clicks on mode buttons
  • Change to 80px arrow key panning (this matches Leaflet default)
  • Smoother border around the round vertex preset icon circles
  • Render railway platform slightly different from sidewalk
  • Treat a few special tags as areas even in the absence of a proper area=yes tag.

? Bugfixes

  • Include imagery offset when calculating tiles for background layer
  • Return to browse mode when zooming out beyond edit limit
  • Make sure bool url params actually contain value ‘true’

? Localization

  • Update Chinese address format
  • Swap placement of increment/decrement spin buttons when RTL
  • Fix RTL styling for info panel close buttons
  • Fix RTL styling for spin control and form buttons

⌛️ Performance

  • Use requestIdleCallback in supported browsers for deferred data fetching
    • Avoid reparsing duplicate entities that appear across adjacent OSM tiles
    • Schedule parsing as a low priority task
    • Schedule redraws during idle browser times

? Presets

  • Add signpost term to guidepost preset
  • Remove maxspeed field from living street
  • Make office=physician non-searchable
  • Add preset for amenity=shower
  • Add preset for emergency=life_ring
  • Allow traffic mirror preset on vertex
  • Add presets for many theme park attractions
  • Improve search terms for wetland preset
  • Add jetty search term to amenity=pier preset
  • Remove bin=yes from excrement bag vending machine
  • Improve search terms for group home and social facility presets
  • Allow aerialway station to be drawn as an area
  • Improve search terms for T-bar lift
  • Add hedge preset to barrier category
  • Add railway presets for Derailer, Milestone, Signal, Switch, Train Wash and icons
  • Add railway preset for Buffer Stop, and icon
  • Replace generic “Reference” field with more specific named fields
  • Add preset for Telecom Manhole

The iD map editor is an open source project. You can submit bug reports, help out, or learn more by visiting their project page on GitHub: :octocat: https://github.com/openstreetmap/iD
Finally big thanks to the @TeamID for all their contribution and continuous effors for making more and more usefriendly iD versions.

Source: http://ideditor.com/ and iD Changelog

OpenStreetMap: The Joy of Open Cartography

A nice blog is written under EDUCATIONREMOTE SENSING & GIS section of scientiaplusconsrientia.wordpress.com, can’t wait to share it here.


I first heard about OpenStreetMap several years ago but did not have enough time or motivation to explore it in depth. That changed last year when I found that I could fit OpenStreetMap data as background maps to a Garmin handheld GPS for use in hiking and bicycle tours (using data downloaded from http://garmin.openstreetmap.nl/). This worked perfectly, and irreversibly awoke my curiosity for this project.

OpenStreetMap is a community-based mapping project on a global scale with the goal of producing and maintaining a complete and updated map that is free from legal and technical restrictions for use. OpenStreetMap implements a Open Data Commons Open Database License (ODbL). That means that one is able to use, modify and reshare the map and data, under the condition of giving credit to OpenStreetMap contributors, sharing under the same terms and keeping the data open. As the database grows in size and quality, the fact that the data are licensed in this manner makes the project an increasingly valuable resource.

OpenStreetMap homepage showing the layers dialogue.
                                                 OpenStreetMap homepage showing the layers dialogue.

In OpenStreetMap, any cartographer (amateur or otherwise) can contribute by mapping new features or editing existing ones. The resulting data can be used directly through its web interface, but it can also be advantageously integrated in websites, GIS platforms, and mobile applications. The potential uses are manifold. OpenStreetMap works for maps in the same way as Wikipedia does for facts. If you like cartography and open data, OpenStreetMap might be a perfect match for you.

Southern suburbs of Buenos Aires, Argentina. Streets and motorways as vectors from OpenStreetMap, superimposed on a Sentinel-2 image. Rendered in QGIS.
Southern suburbs of Buenos Aires, Argentina. Streets and motorways as vectors from OpenStreetMap, superimposed on a Sentinel-2 image. Rendered in QGIS.

There are many things that can be told about how to use OpenStreetMap (OSM) data. We can just begin by the most basic of them, namely how can we start contributing to the map. Before we start, it is worth to mention that the basic idea behind OSM is that the world can be described using features, which are composed of tags attached to basic elements (nodes, ways and relations). It took a little while for me to familiarize myself with this model but it is easily understood after some reading and practice. Also remember that OSM is a community based project. As in any project of this kind, there is an important code of conduct agreed upon by the participants. Please respect it for everyone’s enjoyment and benefit.

After creating a login, we may just start editing using the iD interface integrated in the web page. This is the recommended option for beginners (in contrast to the more advanced standalone application JOSM):

OpenStreetMap home page.
                                                                                    OpenStreetMap home page.

Once logged in, we can then click in the “edit” button, marked in the picture above (the menu appears in Swedish in my case, sorry I could not change it). Once into the editing mode, there is a simplified editing menu, reminiscent of those in GIS tools, with options for adding points, lines or polygons. It also allows to edit the nodes. The background images are from Bing maps:

OpenStreetMap in editing mode (iD).
                                                            OpenStreetMap in editing mode (iD).

Clicking in an object, in this case the coastline of the Island of Capri, Italy, shows a menu to the left with the tags with which the mappers have marked this object. Also note the node editing dialogue next to the selected node. One can then proceed to add, move and delete nodes or features, as well as adding or modifying tags.

OpenStreetMap in editing mode (iD).
                                                                        OpenStreetMap in editing mode (iD).

After saving the edits the newly created features or the edits to existing features are committed to the database. After a while, the servers will show the updated view service in the main map.

This simple recipe is the basis for a lot of the mapping work that goes into making OSM a great tool. Now think of all the unmapped features that may be present in your neighborhood or other areas you know well: hiking paths, bus stops, street names, forests, parks and a long list of etceteras. There are surely many potential improvements that you can easily introduce to the map. Go on and enjoy your mapping!

Chikungunya Map: Areas at Higher Risk in Dhaka

Chikungunya is a mosquito-borne viral disease first described during an outbreak in southern Tanzania in 1952. It is an RNA virus that belongs to the alphavirus genus of the family Togaviridae. The name “chikungunya” derives from a word in the Kimakonde language, meaning “to become contorted”, and describes the stooped appearance of sufferers with joint pain (arthralgia). Recently it has been much evident in Dhaka city like other areas of Bangladesh.

Institute of Epidemiology, Disease Control and Research or IEDCR gave a list of the locations while presenting a research paper at the Secretariat on Thursday.  The areas are Dhanmondi 32,  Sector 4 and Sector 9 of Uttara, Maddhya Badda, Gulshan 1, Lalmatia, Pallabi, Moghbazar, Malibagh Chowdhury Para, Rampura, Tejgaon, Banani, Noyatola, Kuril, Pirerbag, Rayerbazar, Shyamoli, Monipuripara, Mohammadpur, Mohakhali, Mirpur-1 and Korail slum.


  • Most people infected with chikungunya virus will develop some symptoms.
  • Symptoms usually begin 3–7 days after being bitten by an infected mosquito.
  • The most common symptoms are fever and joint pain.
  • Other symptoms may include headache, muscle pain, joint swelling, or rash.
  • Chikungunya disease does not often result in death, but the symptoms can be severe and disabling.
  • Most patients feel better within a week. In some people, the joint pain may persist for months.
  • People at risk for more severe disease include newborns infected around the time of birth, older adults (≥65 years), and people with medical conditions such as high blood pressure, diabetes, or heart disease.
  • Once a person has been infected, he or she is likely to be protected from future infections.


  • The symptoms of chikungunya are similar to those of dengue and Zika, diseases spread by the same mosquitoes that transmit chikungunya.
  • See your healthcare provider if you develop the symptoms described above and have visited an area where chikungunya is found.
  • If you have recently traveled, tell your healthcare provider when and where you traveled.
  • Your healthcare provider may order blood tests to look for chikungunya or other similar viruses like dengue and Zika.


  • There is no vaccine to prevent or medicine to treat chikungunya virus.
  • Treat the symptoms:
    • Get plenty of rest.
    • Drink fluids to prevent dehydration.
    • Take medicine such as acetaminophen (Tylenol®) or paracetamol to reduce fever and pain.
    • Do not take aspirin and other non-steroidal anti-inflammatory drugs (NSAIDS until dengue can be ruled out to reduce the risk of bleeding).
    • If you are taking medicine for another medical condition, talk to your healthcare provider before taking additional medication.
  • If you have chikungunya, prevent mosquito bites for the first week of your illness.
    • During the first week of infection, chikungunya virus can be found in the blood and passed from an infected person to a mosquito through mosquito bites.
    • An infected mosquito can then spread the virus to other people.

Source: WHO; CDC

Urban Damage Assessment from High Resolution Images using OSM MASK and Neural Network

A complete methodology has been given by Dariia Gordiiuk of Earth Observatory Systems(EOS) Data Analytics for detecting urban damages Applying Neural Network and Local Laplace Filter and OSM masking Methods to Very High Resolution Satellite Imagery. Hope it will help a lot the geospatial analysts.

Since the beginning of the human species, we have been at the whim of Mother Nature. Her awesome power can destroy vast areas and cause chaos for the inhabitants. The use of satellite data to monitor the Earths surface is becoming more and more essential. Of particular importance are the disasters and hurricane monitoring systems that can help people to identify damage in remote areas, measure the consequences of the events, and estimate the overall damage to a given area. From a computing perspective, such an important task needs to be implemented to assist in various situations.

To analyze and estimate the effects of a disaster, we use high-resolution, satellite imagery from an area of interest. This can be obtained from Google Earth. We can also get free OSM vector data that has a detailed ground truth mask of houses. This is the latest vector zip from New York (Figure 1).

Figure 1. NY Buildings Vector Layer

Next, we rasterize (convert from vector to raster) the image using a tool from gdal, called gdal_rasterize. As a result we have acquired a training and testing dataset from Long Island (Figure 2).

Figure 2. Training Data Fragment of CNN

We apply a deep learning framework Caffe for training purposes and the learning model of Convolutional Neural Networks (CNN):

Figure 3. CNN Parameters

The derived neural net enables us to identify the predicted houses from the target area after the event (Figure 4). We can also use data from another similar area which hasn’t been damaged for CNN learning (if we can’t access the data for the desired territory).

Figure 4. Predictive Results of CNN Learning

We work with predicates of buildings using vectorization (extracting a contour and then converting lines to polygons) (Figure 5).

Figure 5. Predictive Results of Buildings (Based on CNN)

Also, we need to compute the intersection of the obtained predicate vector and the original OSM vector (Figure 6). This task can be accomplished by creating a new filter, dividing the square of the predicate buildings by the original OSM vector. Then, we filter the predictive houses by applying a threshold of 10%. This means that if the area of houses in green (Figure 6) is 10% less than the area in red, the real buildings have been destroyed.

Figure 6. Calculating CNN-Obtained Building Number (Green) Among Buildings Before Disaster (Red)

Using the 10%-area threshold we can remove the houses that have been destroyed and get a new map that displays existing buildings (Figure 7). By computing the difference between the pre- and post- disaster masks, we obtain a map of the destroyed buildings (Figure 8).

Figure 7. Buildings: Before and After Disaster With CNN Method
Figure 8. Destroyed Buildings With CNN

We have to remember that the roofs of the houses are represented as flat structures in 2D-images. This is an important feature that can also be used to filter input images. A local Laplace filter is a great tool for classifying flat and rough surfaces (Figure 9). The first image has to be a 4-channel image with the fourth Alpha-channel that describes no-data-value pixels in the input image. The second image (img1) is the same, a 3-channel RGB image.

Figure 9. Local Laplace Window Filter

Applying this tool lets you get the map of the flat surface. Let’s look at the new mask of the buildings which have flat and rough textures (Figure 10) after combining this filter and extracting the vector map.

Figure 10. Flat Surface Mask With Laplace Window Filter Followed By Extracted House Mask

A robust library of the OpenCV computer vision has a denoising filter that helps remove noise from the flat buildings masks (Figure 11, 12).

Figure 11. Denoising Filter
Figure 12. Resulting Mask. Pre- and Post- Disaster Images After Applying Denoising Filter

Next, we apply filters to extract the contours and convert the lines into the polygons. This enables us to get new building recognition results (Figure 13).

Figure 13. Predictive Results of Buildings With Laplace Filter

We compute the area of an intersection vector mask obtained from the filter and a ground truth OSM mask and use a 14% threshold to reduce false positives (Figure 14).

Figure 14. Calculations: Buildings With Laplace Filter (Yellow) Before Damage (Green), Using 14% Threshold

As a result, we can see a very impressive new mask that describes houses that have survived the hurricane (Figure 15) and a vector of the ruined buildings (Figure 16).

Figure 15. Before and After Disaster With Laplace Filter
Figure 16. Destroyed Buildings With Laplace Filter

After we have found the ruined houses, we can also pinpoint their location. For this task OpenStreetMap comes in handy. We have installed an OSM plugin in QGis and added an OSM layer to the canvas (Figure 17). Then, we added a layer with the destroyed houses and we can see all their addresses. If we want to get a file with the full addresses of the destroyed buildings we have to:

  1. In QGis use Vector / OpenStreetMap / Download the data and select the images with the desired information.
  2. Then in QGis use Vector / OpenStreetMap / Import a topology from XML and generate a DataBase from the area of interest.
  3. QGis / Vector / Export the topology to Spatialite and select all the required attributes. (Figure 18)
Figure 17. Destroyed Houses Location
Figure 18. Required Attributes Selection To Load Vector Into Ruined Buildings

As a result, we can get a full list, with addresses, of the destroyed buildings (Figure 19).

Figure 19. Address List of Ruined Houses

If we compare these two different approaches to building recognition, we notice that the CNN-based method has 78% accuracy in detecting destroyed houses, whereas the Laplace filter reaches 96.3% accuracy in recognizing destroyed buildings. As for the recognition of existing buildings, the CNN approach has a 93% accuracy, but the second method has a 97.9 % detection accuracy. So, we can conclude that the flat surface recognition approach is more efficient than the CNN-based method.

The demonstrated method can immediately be very useful and let people compute the extent of damage in a disaster area, including the number of houses destroyed and their locations. This would significantly help while estimating the extent of the damage and provide more precise measurements than currently exist.

Source: Dariia Gordiiuk from Earth Observatory System (EOS) 

OSM Based Android Apps for Mapping

Though there are a significant numbr of apps are available for tracking, routing, navigation, POI saving but OpenStreetMap based are more useful than others interms of licene, freedom and customization. Below are a short detail of few OSM based mapping app for android

 OSM Tracker

One of the key apps, is something that can track where you are, providing a record of where you’ve been and allowing you to upload it to the OpenStreetMap website. OSM’s heritage is built around collecting data using a GPS, and it still remains a powerfull way of mapping an area without requiring other sources. And we actually are all carrying a GPS device around with us in our pocket it is very easy to do.

I use OSM Tracker it’s a simple app, and does it well, as well as recording a GPS trail, it also allows you to take pictures, and display the track on a map.

Use is really simple, start a new track:

Once it is running, it displays the currently GPS Position, shortcuts for taking a picture, and noting various features:

It is also possible to view the track on a map, this is really useful for checking the current area mapped, and seeing where you’ve been:

Finally, it’s possible to tag save and upload the track:


Editing is generally done as after mapping on a computer, but it can be really helpful to be able to make some changes from your phone, especially once you’re more experienced, I would recommend using Vespucci, Vespucci is getting better and better all the time, and does a really good job editing using the touch interface. This isn’t necessary a beginners tool, but a good tool that continues to improve that’s definitly worth looking at.

When you click on the map, it allows you to choose what item you wish to edit, which is a good solution to the problem of never being able to select accurately enough with your finger. Geometries can then we tweaked as neccessary.

Although I tend to use it to make small changes such as editing tags rather than big edits, it’s a powerfull tool that only gets better.

Data Gathering

Wheelmap for Accessibilty

Wheelmap is a great example of a simple data gathering app. The wheelchair app collects accessibilty information as well as some simple addressing information to be displayed on the Wheelmap Site


Keypadmapper for Addressing

As we have mapped a significant proportion of the road network, there is now a big push to collect addressing data Keypadmapper is a simple app to collect addressing data as you move down the road simply enter the numbers as you pass them. Later the address points can be loaded into JOSM for adding into OpenStreetMap.

Find the apps in play store from below link:

Google Map Maker vs. OpenStreetMap: Which mapping service rules them all?

You have a choice when it comes to maps, and the answer isn’t as clear as it used to be. Google’s maps are still king, but OpenStreetMap is making a name for itself, gaining favor among many apps and services that rely heavily on maps, such as Foursquare and Evernote.

OpenStreetMap launched in the UK in July 2004 as an alternative to the large number of proprietary maps that were big in the country at the time. Where does OpenStreetMap get its granular data from? You. Not in an NSA-eye-in-the-sky type of spying, but from information manually input from thousands of casual cartographers. It is truly the Wikipedia of maps. In September 2012, MapBox, developer of the iD mapping editor and one of the main contributors behind OpenStreetMap, received a stipend of $575,000 from Knight News Challenge to further improve OSM’s core infrastructure.

As for Google, it has recognized the usefulness of a ground team – particularly in far flung locations where its Street View contraptions haven’t reached yet. In June 2008, the company introduced Google Map Maker, which allows casual cartographers to add or correct information on Google’s maps. Sounds familiar, doesn’t it?

Though there are similarities between the two community mapping programs, what’s the best one to invest time into if you want to see your mad mapping skillz reflected online?

Open vs. closed data system

osm-screenshot-2The biggest difference between Google Map Maker and OpenStreetMap is how it treats the data you feed it, which may influence your decision on which one to use. OSM describes itself as an open data source, meaning that any person or company is able to use the map information contained in OpenStreetMap. Bear in mind that companies such as Foursquare and Evernote pay MapBox, which creates APIs for OSM, to use the maps for their app, but any information that Foursquare or its users add to it becomes part of and available to all OSM users. In other words, there’s no specialized OSM map that a paying company has access to that a regular Joe doesn’t also have access to.

OpenStreetMap recently switched from a Creative Commons license to an Open Database License (ODbL), which is a share-alike license. It’s similar to the previous Creative Commons license as both allow OSM to be shared and used as long as all of the data one person or company puts into it is made available to all of OSM’s users.

Google Maps and, by extension, Google Map Maker, is a closed system. All of the information you submit becomes property of Google. From the always thrilling Terms of Service page:

By submitting User Submissions to the Service, you give Google a perpetual, irrevocable, worldwide, royalty-free, and non-exclusive license to reproduce, adapt, modify, translate, publish, publicly perform, publicly display, distribute, and create derivative works of the User Submission. You confirm and warrant to Google that you own or have all of the necessary rights or permissions to grant this license. You also grant to end users of Google services the right to access and use, including the right to edit, the User Submissions as permitted under the applicable Google terms of service.

Depending on your personal stance, this may not be a big deal for you. It is, after all, a way to contribute to a map that is pretty much the online standard around the world. Speaking of that, because of Google Maps omnipresence, there’s not always a lot of information to add to heavily populated areas. Much of the major road information missing from Google Maps is in remote parts of the world, such as parts of Africa and Asia.

Speed of updates

As someone just getting started with mapping, you’ll want to see the changes you make as soon as possible, right? Much like Wikipedia, updates made via the Javascript-based iD editor for OpenStreetMap are able to be viewed instantly. However, like Wikipedia, vigilant editors dedicated to keeping the maps correct will remove or alter erroneous edits or additions. So if you label your ex-boyfriend’s house “Dirtbag Manor,” it’s going to be removed between a few hours to a couple of days.

Google Map Maker lets you instantly view your edits, but it cautions that your edit will need to be reviewed before it’s officially added. Oddly enough, even if it’s your first edit to a map, you can still review other people’s edits. In fact, reviewing others’ edits is a way to get your edit reviewed more quickly. However, there’s no telling how long it will take to get reviewed. One edit in our neighborhood had been waiting for review since October 2012.


Google-map-maker-edit-dtGoogle’s Map Maker looks a lot like Google Maps before the most recent update. There’s a column on the left side and the map is on the right. The big difference is that the left column has a header for “My Neighborhoods.” This isn’t the traditional Mr. Rogers definition of neighborhood, but rather geographical locations that you’re interested in. We had a little bit of difficultly adding locations other than where we were currently located, but we were able to add them once we included a city name and state instead of just a zip code. Adding neighborhoods isn’t required to edit a map, but it does provide a general area for viewing and reviewing map edits made by others.

id-ed-area-edit_dtBy comparison, you can view any area on OpenStreetMap with the iD editor and not have to specify geographical areas of interest or expertise.

Adding a road, building, place of interest, or town boundary is similar in both applications. In our experience, the OSM iD editor seemed more user friendly and straight forward. We found it much easier to add a business within a building using the iD editor than it was in Map Maker.

Social component

google-map-maker-welcom-dtIt’s no secret that Google is pushing Google+ extra hard, and Map Maker is no exception. The company encourages Map Maker fans to gather for “MapUps” where amateur cartographers meet up to update Google Maps together. Sounds pretty geeky, right? The MapUp may be held in person or virtually (through Google Hangouts, of course). Google suggests MapUps as a project for a cycling club that wants to add bike paths. The host of an in-person MapUp is elevated in the Map Maker world to an Advocate, as long as at least 20 people attend who each make at least five approved edits.

If that’s not enough cred for you, there’s also a club for Power Mappers. This is for cartographers who make numerous edits and reviews to Map Maker. There’s a private forum and a “unique opportunity to work behind the scenes toward mapping initiatives and product improvements.” Google is really pushing the social side of Map Maker to the point where it seems a little contrived.

Make no mistake, OpenStreetMap is not without its social entities, either. There are numerous mapping meet ups we found listed on openstreetmap.meetup.com and many were taking place this month. We can’t say the same for Google’s MapUps. We only found two events for the month of July, one of which was in Romania. To be fair, Google says it has over 25,000 Map Maker users, while OSM says it has over 1 million.

End of the Road

Ultimately, if you’re interested in cartography, OpenStreetMap is more readily accessible and it’s easier to find others in your locale who share the same interest. Google’s Map Maker is not without its benefits, but our overall experience with it felt more like we were navigating a ghost town instead of a thriving community.

Ref: www.digitaltrends.com

State of the Map Asia 2016 Conference: Sharing experience

It has been a great experience attending the State of the Map Asia 2016 Conference as a open data and geospatial expert from Bangladesh in Manila, Philippines in 1-2 October 2016 where I met many sharp international colleagues, friends, experienced veterans of geospatial field, specialists in various geospatial disciplines, open street map and GIS practitioners from different cultures.


 I was invited to take part in two full days of OpenStreetMap-related presentations, technical workshops, learning sessions, software demonstration, and numerous interaction opportunities between contributors, communities and institutional supporters of Openstreetmap with the rest of Asia and the world. SOTM Asia also hosted the third VISIONS Asia Resilience Forum which aims to bring together representatives from ICT communities, private and public sector to discuss experiences and best practice on developing civic apps for community – based disaster resilience in the Asian region. I was a fruitful gathering of likeminded people from more than 12 countries comprising not only from Asia but also from other countries like USA, Sweden, Russia and Australia. It was the event just after the crisis mappers’ conference held in Manila. Personally I think this conference was very well organized and very successful. I fully enjoyed the two days event with so many interesting sessions and discussions on various geospatial topics. Several of the sessions, delivered by several OSM communities which I attended had been very informative and insightful on their particular subjects. I would like to take this chance to reflect upon my enriching experiences in Manila and summarize in what ways this SOTMA conference helps me to benefit from exchange of ideas, sharing of legal expertise , socializing with international counterparts etc, in the meantime examine the its relevance to our community in Bangladesh.

The event was kicked off in 1st Oct, by Kate Chapman, Chairman OSM Foundation and with her summary speech on fundraising initiative. I enjoyed the presentations by my longtime friend and amazing guy Mr. Taichi Furuhashi who talked about some fantastic projects in Japan and their future idea to establish for future funding. The event was not only for OSM data talk but also showcased the Asian experience and use cases for disaster risk and resilience. Among them some of the talk were much interesting and insightful, like:

  • Project NOAH and Openstreetmap: The Role of Science and Crowdsourced Mapping in DRR. Presented by Ervin Malicdem; Dinnah Feye Andal
  • Development of a Disaster Resilient Campus Land Use Plan of Bicol University using Open Source Softwares. Presented by Michael T. Cobill
  • Mapping for flood exposure with OpenStreetMap the Sri Lanka experience. Presented by Robert Banick; Srimal Priyantha Samansiri
  • Meet the super girls from Marunda who utilize OSM to build their community resilience map. Presented by Wulansari Khairunisa
  • Significance of open source in participatory vulnerability mapping. Presented by Melvin B. Purzuelo
  • OSM, ODK and OMK, Oh my. Mapping and Surveying in Habitat for Humanity’s Nepali Earthquake Response. Presented by Robert Banick, EwanOglethorpe
  • Map the Philipine (MapPH) Presented by Celina Agaton

And some other use cases of OpenStreetMap were presented through:

  • Lowiki – share local knowledge with Lowiki and OSM. Presented by Pomin Wu
  • Mapping the Cordillera Great Traverse Hiking Trail. Presented by Leonard G. Soriano
  • Openstreetmap data for Navigation guidance and Trekking. Presented by Ervin Malicdem


The schedule of the event was assorted by different fields of open map data like disaster, osm data , validation, data collection and editing tools, use cases like navigation, hiking, trailing, locating birds, crowdsourcing and Ubuntu etc. what made it more interesting rather than monotonous.  The map data presentations helped us to understand the tiring job of data cleaning, aligning and validation behind the scene.

  • Building a Data Team in the Open. by Maning Sambale
  • Validating the map. by Chethan H A
  • io: Updating and validating health facility locations in OSM. by Nate Smith
  • Openstreetmap data for Navigation guidance and Trekking. by Ervin Malicdem

The most attraction of the event was the training workshops in parallel session what was very much useful for the new learners. The list of the workshops held is :

  • Mapillary Workshop. Conducted by Edoardo Neerhut
  • Map Box Studio . Conducted by Srividya Bharadwaj and Mapbox India Team
  • InaSAFE and its use for disaster response . Conducted by Adityo Dwijananto and Wulansari Khairunisa
  • Local knowledge is king – Maps.me. Conducted by  Eugene Lisovsky

And all the inspiring country talks from Japan, Indonesia, Myanmar, Philipines and other countries including Bangladesh given by me. My talk was on “OSM community development issues and challenges in Bangladesh” where I had focused on the issues in terms of community mapping and the sustainability of it, in-situ and ex-situ challenges for developing community as well as the success stories too.  The key note speakers Taichi Furuhashi from Japan and Dr. Dr. Nama Raj Budhathoki, executive director of Katmandu Living Lab was above all for their speech and the “Act Locally Change Globally” presentation by famous dancer Jun Amanto had given a  diverse insight of the open data initiative. Finally the Social event supported by MapBox at Vikings SM City Marikina was one of the best in my life.


The beautiful University of Philippines Dilliman’s Department of Geodetic Engineering was the venue of the partner and the center point for all these events. I would like to express my gratitude to SOTMA team for inviting me and to take awesome role for getting my super-fast visa. My special thanks goes to the “visions” BeGood Cafe and Mapbox for funding me. It was an awesome gathering and more effective and sucessful event than ever in Asia. Salute to the organizing team for all their efforts for make the program happen and fruitful. Special thanks goes to the mastermind of this event Mr. Maning Sambale for all his precious time and hard work for making the event successful and memorable for the participants.

Crowd-Sourced Mapping !!!

What is crowd-sourcing?

Crowdsourcing is generating content on the internet, which involves contributions from a large, disparate group of individuals.  These methods rely upon web applications that allow people to upload information easily and allow many others to view and react to this information. Crowdsourcing relies on the principle that a lot of knowledge resides with individual citizens, who are experts of their own local environment.  Mapping sites that utilize crowdsourcing include:  OpenStreetMap project, Google Map Maker, Geo-wiki, andWikimapia. These tools vary in terms of scope of geographical coverage, data entry methods, targeted end-users, data licensing arrangements, and ease of use.  Additionally, they may use different methods of moderating data (verifying that entered data is valid), which influences data quality and speed of publication.

What is crowd source Mapping?

A  vast amount of geodata is available on the internet, through on-line maps, web services and virtual globes. Data providers range from the individual mapper enthusiasts to geo-information professionals. Base data, such as road networks and satellite imagery are made available on a global scale, and more specific and valuable thematic data is often produced within dedicated projects.

Current software applications are changing the web to act more and more as platform for real-time information integration, with many web sites collaboratively controlled.  Geospacial applications range from personal mash-ups, which is the combination of data from two or more sources, to project-based web mapping, where the concept of location adds new possibilities for exploring information.

Why should you map?

Quality geographic data helps empower organizations and communities to make important decisions across a range of environmental, economic and crisis management themes. For many places in the world, this information is incomplete or does not exist at all. Digital humanitarians map online to help give others the data they need to build a more sustainable future.

OpenStreetMap !!!!

Through the Open Data Commons Open Database License 1.0, OpenStreetMap (OSM) contributors own, modify and share data publicly. There are many other free maps on the Internet, but most have legal or technical restrictions preventing others from using the data openly. With OSM both the maps and underlying data can be downloaded for free, for developers or anyone to use or redistribute. Additionally, in many places of the world where there is no commercial motivation to develop this data, OSM is often the best available resource.

Learn OSM: Part-3 (Task Manager)

How to Select&Edit a Task in the OpenStreetMap Tasking Manager

Select a Task and map a tile. You do not need to be at the location and do not need to know the names of roads and buildings. You will look at satellite imagery and trace roads, paths, buildings and areas

    • Select the Task you wish to work on; a new browser tab or window (depends on browser settings) opens, taking you directly to the mapping task on the OpenStreetMap Tasking Manager website.
    • Log in with your OpenStreetMap account. If you are still logged into OpenStreetMap, you will not need to enter your login info.
    • You will see a map and information about the task including instructions on what to map.
    • Select a tile to work on.
    • Use the interactive map and zoom in on the highlighted tiles. The job has been broken up into small tile areas of the map to allow you to do a little bit of mapping rather than trying to map the entire area. This also lets other simultaneously map other tiles, or areas.
    • When you select a tile, your task is to map that specific tile by tracing satellite imagery.
    • Gray tiles represent all of the tasks available in this job. Red tiles are areas that have been marked as done. Green tiles are areas that were marked as done and have been validated. Gray tiles with yellow outlines are areas that are currently being worked on.
    • Click on a gray tile to select it. The task tab opens. Click on the green button that says, “Yes, I want to work on this task”. By selecting a tile you are “checking it out”. No one else will be able to edit this tile while you are working on it. Once you have completed working on the tile you will need to “check it back in” so others can validate or build on your work. The “check in” process is explained later in these instructions.
    • The task tab has a few additional sections: extra instructions (information about the imagery you are about to work with. In some cases, you will need to adjust the imagery in the iD editor), information on how to credit your edits (what you will copy and paste into the iD editor so your edits can be logged correctly) and history of this task.
    • To work on your tile, select iD from the editing tool options. This opens a new tab or window in your browser.
    • If needed, adjust the satellite imagery to match with an existing map edit by:
      • clicking on the layers button
      • scrolling down to “fix alignment”
      • using arrow buttons to line up the high resolution satellite imagery with the existing map edit. You may need to zoom in to do this.
    • Add roads, paths, buildings and areas in your tile. When you make a map edit, a dialogue box will appear. As you trace, you may not know the specific name of the road or building, which is okay. For instance, when you select the “Building” button in the iD editor, your map edit is automatically tagged as a building.
    • Credit your work each time you save your edits. A collection of map edits are called a changeset, and when you save your edits, you are essentially applying a “commit” to the OSM database. The iD editor will ask if you want to provide a “commit message” to your collection of edits. This information will help us understand when an edit was made as part of MapGive.
    • To credit your edits:
      • Click back to the OpenStreetMap tasking manger browser tab.
      • Scroll down to the credit section in the task tab.
      • Copy the credit. Click back on the iD editor browser tab.
      • Paste the credit in the tag section of the dialogue box.
    • When you finish or wish to stop mapping a tile, return to the OpenStreetMap tasking manager.
    • Either “unlock the task” or “mark it as done.” Unlocking the task means that you have done some of the map edits but there are more to do. Marking the task as done means that you have completed the tile.
    • When you unlock a task, the tasking manager allows you to input comments. You may indicate how much of the tile is complete and specific features that need work. If you have no comments, write “no comments”.
    • TIP: Unlocking a task = “checking it back in”
    • If you saved your edits in the iD editor, they will still be there others or for you to come back to.
    • Thank you for learning how to map and also for mapping to make a difference.

Source : http://mapgive.state.gov/
For more plz visit: http://mapgive.state.gov/index.html