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Animating Ground Overlays in Google Maps iOS SDK

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Many maps use overlays to display different types of features on the map. Many examples show old hand drawn maps that have been re-projected to fit on our modern day, online ‘slippy’ map but
very few show these overlays over time. In this tutorial we are going to explore animations using the Google Maps iOS SDK to show the current live weather conditions in the UK.

The Met Office is responsible for reporting the current weather conditions, issuing warnings, and creating forecasts across the UK. They also provide data through their API, called DataPoint, so that
developers can take advantage of the live weather feeds in their apps. I’ve used the ground overlays from DataPoint to create a small iOS application, called Synoptic, to loop around the real-time overlays
and display them on top of a Google Map, very handy if your worried about when it’s going to rain.

Finished App and Source Code

I always find it interesting when these tutorials show you what we’re going to create before digging deep into the code so here is a small animation on the right of the page of what the end product should look like.

What you’re looking at is the real-time precipitation, or rain, observations for the UK on Sunday 19th January 2014. It’s been quite sunny in London today so much of the rain is back home in
the North. You can grab a copy of the code for this tutorial from GitHub.

Before we get started

They’re a few things we need before we can start putting the data onto the map. Firstly, you’ll need an API key for Google Maps iOS SDK and you can access this by turning on the SDK from the
Cloud Console (https://cloud.google.com/console/). If you haven’t created a project yet then click Create Project and give your project a name and a unique id. I have a project called
TestSDK, which I use when I’m playing around with various API’s from Google. Follow the instructions on https://developers.google.com/maps/documentation/ios/start#the_google_maps_api_key
for getting your key. If you’ve downloaded the code from GitHub then the bundle identifier is set up as com.stevenjamesgray.Synoptic.

You’ll also need to sign up for a key for DataPoint. Once you’ve
registered for the API they’ll email you a key and your good to go.

Step 1 – Setting up the keys and running the project

When you have your keys and source code then open the project in Xcode and copy and paste your keys into Constants.m (it’s in the Object folder). If the keys are valid then you’ll be able to
build and run the project and you’ll start to download the overlay images and they’ll start to animate. I’ve already setup the mapView in the project but if you haven’t used the Google Maps
iOS SDK before then you should check out Mano Marks excellent HelloMap example on Google Developers Live. This will get you up to speed with creating a MapView and linking it into your project. The only extra part I’ve added is a custom base layer which will be covered in
another blog post.

Downloading the weather data

Datapoint has 2 types of data that can be visualised – observations and forecasts which, naturally, are contained in 2 separate API endpoints. If you look at Constants.m you’ll see the URL
to both endpoints:

NSString* const api_forecast_layers_cap = @"http://datapoint.metoffice.gov.uk/public/data/layer/wxfcs/all/json/capabilities?key=%@";
NSString* const api_obs_layers_cap = @"http://datapoint.metoffice.gov.uk/public/data/layer/wxobs/all/json/capabilities?key=%@";

If you copy the URL and paste it into your browser along with your key you’ll find that this JSON file lists all the layers that are available from the Met Office and where you can fetch the
images from the server. For observations we fetch the LayerName, ImageFormat (for us on iOS it will be png), the Time of the image (the timestamp of the image given by the time array – watch
out for the Z on the end) and most importantly our API key. Once we have constructed this URL we fetch the image.

-(void) selectLayer: (NSString*)layerID withTimeSteps: (NSArray *)timestep_set{
    for(NSString *timestep in timestep_set){

        NSURL *hourlyCall = [NSURL URLWithString: [NSString stringWithFormat: @"http://datapoint.metoffice.gov.uk/public/data/layer/wxobs/%@/png?TIME=%@Z&key=%@", layerID, timestep, MET_OFFICE_API_KEY]];

        NSLog(@"Calling URL: %@", [hourlyCall absoluteString]);
        NSURLRequest *request = [NSURLRequest requestWithURL: hourlyCall];
        AFImageRequestOperation *operation = [[AFImageRequestOperation alloc] initWithRequest:request];
        [operation setCompletionBlockWithSuccess:^(AFHTTPRequestOperation *operation, id responseObject) {

            //Check for a UIImage before adding it to the array
            if([responseObject class] == [UIImage class]){

                // Setup our image object and write it to our array
                SGMetOfficeForecastImage *serverImage = [[SGMetOfficeForecastImage alloc] init];
                serverImage.image = [UIImage imageWithData: operation.responseData];
                serverImage.timestamp = timestep;
                serverImage.timeStep = nil;
                serverImage.layerName = layerID;

                [overlayArray addObject: serverImage];

                // Increment our expected count so that we know when to start playing the animation
                imagesExpected = @([imagesExpected intValue] + 1);
                }
        } failure:^(AFHTTPRequestOperation *operation, NSError *error) {
                //We didn't get the image but that won't stop us!
                imagesExpected = @([imagesExpected intValue] + 1);
                NSLog(@"Couldn't download image.");
        }];

        [operation start];

    // Start the Timer to check that we have all the images we requested downloaded and stored in the layer array
        checkDownloads = [NSTimer scheduledTimerWithTimeInterval: 1 target:self selector:@selector(checkAllImagesHaveDownloaded:) userInfo: [NSNumber numberWithInt: [timestep_set count]] repeats: YES];
    }
}

This code fetches the images asynchronously and adds them into an array for us to use later in the code. We start a timer to check that we have downloaded all of our images before
starting to loop around the images on the map. The observant reader will notice that if we use loop around this array of images then they would be out of sync as we don’t know what order the images are downloaded so we need to sort them before we
show them on the map. This happens inside our checkAllImagesHaveDownloaded function. This is called every second and checks that all the images are downloaded. If we’ve got all the images then we clear the timer,
sort the array and then kick off the animation on the map. We sort the array using a Comparator which will compare the timestamps of each of the objects and orders them in asending order.

if([imagesExpected isEqualToNumber: imageFiles]){
        [checkDownloads invalidate];

        NSArray *sortedArray;
        sortedArray = [overlayArray sortedArrayUsingComparator:^NSComparisonResult(SGMetOfficeForecastImage *a, SGMetOfficeForecastImage *b) {
             return [a.timestamp compare: b.timestamp];
        }];

        overlayArray = [NSMutableArray arrayWithArray: sortedArray]; 
    ...

Animating the Layers on the Map

When we are ready to animate we create yet another timer which will call the updateLayer method every second. This is where the magic happens! The images we have downloaded from
the Met Office have been created to fit the following bounding box: 48° to 61° North and 12° West to 5° East. This is really easy to convert into decimal degrees using the following rule. Anything west of the
meridian is a negative number and anything east is, of course, positive. Now that we know the bounding box then we create references to the bottom left and top right corners of the
image using the following code:

CLLocationCoordinate2D UKSouthWest = CLLocationCoordinate2DMake(48.00, -12.00);
CLLocationCoordinate2D UKNorthEast = CLLocationCoordinate2DMake(61.00, 5.00);

We grab our current image from the array by using a counter that has been set in the loadView method and then put it on to the map. We set the bearing of the image to 0 (we don’t need
to rotate the image as it’s already in North/South orientation), set the z-index of the image and then add it to the map by setting the ground overlays map property to the mapView we created and set
in the loadView method (our only map object)

GMSCoordinateBounds *uk_overlayBounds = [[GMSCoordinateBounds alloc] initWithCoordinate:UKSouthWest
                                                                             coordinate:UKNorthEast];

GMSGroundOverlay *layerOverlay = [GMSGroundOverlay groundOverlayWithBounds: uk_overlayBounds icon: layerObject.image];
layerOverlay.bearing = 0;
layerOverlay.zIndex = 5  * ([currentLayerIndex intValue] + 1);
layerOverlay.map = mapView;

Increment the counter and check that we haven’t got to the end of the array, if we have then we reset the counter and then wait a second until updateLayer is called again.

// Check if we're at the end of the layerArray and then loop
if([currentLayerIndex intValue] < [overlayArray count] - 1){
    currentLayerIndex = @([currentLayerIndex intValue] + 1);
}else{
    currentLayerIndex = @0;
}

If we run the code like this after we’ve looped around all the images we would get something that looks like this.

Wrong Animation

Unfortunately that’s not quite what we’re looking for! What’s happened is that we have created a new GroundOverlay object and put it on the map above the previous layer without removing the older layer
first. To fix this we need to keep an array of GroundOverlays so that we can remove the layer on the next loop and then remove the old layer from the array. This is done by loop around
the array and setting the map property of the older layer to nil like this:

//Clear the Layers in the MapView
for(GMSGroundOverlay *gO in overlayObjectArray){
    gO.map = nil;
    [overlayObjectArray removeObject: gO];
}

The app is now adding and removing the layers correctly and giving us the illusion of animation on the map.

The complete method to add the current image and remove the old image looks like this:

-(void) updateLayer: (id)selector{
    //Setup the bounds of our layer to place on the map
    CLLocationCoordinate2D UKSouthWest = CLLocationCoordinate2DMake(48.00, -12.00);
    CLLocationCoordinate2D UKNorthEast = CLLocationCoordinate2DMake(61.00, 5.00);

    //Get next layer and place it on the map
    SGMetOfficeForecastImage *layerObject = [overlayArray objectAtIndex: [currentLayerIndex intValue]];

    //Clear the Layers in the MapView
    for(GMSGroundOverlay *gO in overlayObjectArray){
        gO.map = nil;
        [overlayObjectArray removeObject: gO];
    }

    GMSCoordinateBounds *uk_overlayBounds = [[GMSCoordinateBounds alloc] initWithCoordinate:UKSouthWest
                                                                                 coordinate:UKNorthEast];

    GMSGroundOverlay *layerOverlay = [GMSGroundOverlay groundOverlayWithBounds: uk_overlayBounds icon: layerObject.image];
    layerOverlay.bearing = 0;
    layerOverlay.zIndex = 5  * ([currentLayerIndex intValue] + 1);
    layerOverlay.map = mapView;

    [overlayObjectArray addObject: layerOverlay];

    // Check if we're at the end of the layerArray and then loop
    if([currentLayerIndex intValue] < [overlayArray count] - 1){
           currentLayerIndex = @([currentLayerIndex intValue] + 1);
    }else{
           currentLayerIndex = @0;
    }
}

And there you go, animating ground overlays on Google Maps. I hope you’ve found this tutorial useful and if you have then why not share it with your developer friends or
follow me on Twitter (I’m @frogo) or Google+ (+StevenGray).
If you have any questions about this tutorial then either drop me a line via the social links above and I’ll try my very best to answer them. You can also follow the conversation over on Hacker News

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Uncategorized

Assertions on crowdsourced geographic information & citizen science #2

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Following the last post, which focused on an assertion about crowdsourced geographic information and citizen science I continue with another observation. As was noted in the previous post, these can be treated as ‘laws’ as they seem to emerge as common patterns from multiple projects in different areas of activity – from citizen science to crowdsourced […]

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citizen science, Concepts, Crowdsourcing, OpenStreetMap, Spatial Data Quality, VGI, Volunteered Geographic Information

From Rhythmanalyst to Rhythmconductor- Rhythmanalysis: Space, Time and Everyday Life

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Image 1. The book cover of ‘Rhythmanalysis: Space, Time and Everyday Life’

 
In the book, Rhythmanalysis: Space, Time and Everyday Life, French sociologist Henri Lefebvre suggests ‘Rhythm’ as an alternative tool to understand and analyse everyday urban life beyond visual recognition. He argues that we can examine the true nature of cities from the human body, the basic unit of urban life, to substantial urban structures through rhythms.

 

Invisible rhythms are generating, repeating and transforming in cities. Lefebvre categorizes types of rhythm, which deeply intervene the life and make a foundation of law, institution and culture, based on its characteristics. Among them, the author particularly insists to pay attention to two aspects of rhythms that Arrhythmia which is creating discordance between or among two or more rhythms, and Eurhythmia which is staying in the state of harmony and balance. He asserts that it is important to convert Arrhythmia in the city that causes inequality and injustice to Eurhythmia which sustains healthy urban condition.

 

‘Rhythmanlysist’ is a fresh idea from the book published in 1992. Rhythmanlysist hears sounds of the city and reveals hidden systems behind visual images with sensing and analysing the change of spatial aspects in timing. As a rhythmanlysist, Lefebvre investigates Mediterranean cities. He presents some insights that the rhythms of Mediterranean cities are derived from specific geographical and climate environments, and the rhythms have created different political system and exceptional cultural diversity in contrast to Atlantic cities. Physically, it leads the development of plazas and the importance of stairways which link sloping lands.

 

Rhythmanlysist could still be a valuable concept to understand complex urban situations. However, we are living in the digital era. As Mitchell (Mitchell, 1999) denoted, the rhythms of our ordinary life are changing by digital communication. Every day tremendous data, which are invisible and inaudible, are generating, and its flows push us into the massive ocean of heterogeneous rhythms. Therefore, new Rhythmanlysist in the digital age needs other capacities. Capturing the digital data in real time and synthesizing it should be essential requirements to create or maintain Eurhythmia. While the cities of the 20th century needed Rhythmanlysist, now it is the time of ‘Rhythmconductor’ who collects digital rhythms, reorganises its tempos-meters-articulations and resonates new contexts. We can easily find good examples of Rhythmconductor like below.
 

Image 2. London Public Bike share map by Oliver O’Brien. http://bikes.oobrien.com/london/

Image 3. Analysis of Happiness on Twitter during 9th September 2008 to 31stAugust 2011.

Dodds PS,  Harris KD,  Kloumann IM,  Bliss CA,  Danforth CM  (2011) Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE 6(12)

 

This radical change of the rhythm gives an opportunity to redefine the scopes of each social group. Citizens collect and utilize the data by their mobile devices; furthermore, they solve complex urban problems by themselves. (Desouza and Bhagwatwar, 2012) The role of planners is challenging to make new rhythms by spreading effective information and stimulating civic participation using social media instead traditional managers’ role within mainstream planning structures. (Tayebi, 2013) Also, Scientists’ role is shifting. According to Wright (Wright, 2013), scientific researchers had focused to find reasons of urban problems until the last decade, however; their voices are getting stronger to solve problems and provide alternatives in the decision making process with geospatial data and geographical analysis.

 

You can find the detail of Lefebvre’s book from Google and Amazon.

 

Desouza, K C and Bhagwatwar, A, 2012, “Citizen Apps to Solve Complex Urban Problems” Journal of Urban Technology 19(3) 107–136.

Mitchell, W J, 1999 E-topia: “Urban life, Jim–but not as we know it” (MIT Press, Cambridge, MA).

Tayebi, A, 2013, “Planning activism: Using Social Media to claim marginalized citizens’ right to the city” Cities 32 88–93.

Wright, D, 2013, “Bridging the Gap Between Scientists and Policy Makers: Whither Geospatial? | Esri Insider” Esri Insider, http://blogs.esri.com/esri/esri-insider/2013/02/11/bridging-the-gap-between-scientists-and-policy-makers-whither-geospatial/.

 

 

Continue reading »
Big Data, Book, Lefebvre, Rhythmanalysis, Rhythmconductor, Smart city

From Rhythmanalyst to Rhythmconductor- Rhythmanalysis: Space, Time and Everyday Life

Posted on by
 

 

 

 

Image 1. The book cover of ‘Rhythmanalysis: Space, Time and Everyday Life’

 
In the book, Rhythmanalysis: Space, Time and Everyday Life, French sociologist Henri Lefebvre suggests ‘Rhythm’ as an alternative tool to understand and analyse everyday urban life beyond visual recognition. He argues that we can examine the true nature of cities from the human body, the basic unit of urban life, to substantial urban structures through rhythms.

 

Invisible rhythms are generating, repeating and transforming in cities. Lefebvre categorizes types of rhythm, which deeply intervene the life and make a foundation of law, institution and culture, based on its characteristics. Among them, the author particularly insists to pay attention to two aspects of rhythms that Arrhythmia which is creating discordance between or among two or more rhythms, and Eurhythmia which is staying in the state of harmony and balance. He asserts that it is important to convert Arrhythmia in the city that causes inequality and injustice to Eurhythmia which sustains healthy urban condition.

 

‘Rhythmanlysist’ is a fresh idea from the book published in 1992. Rhythmanlysist hears sounds of the city and reveals hidden systems behind visual images with sensing and analysing the change of spatial aspects in timing. As a rhythmanlysist, Lefebvre investigates Mediterranean cities. He presents some insights that the rhythms of Mediterranean cities are derived from specific geographical and climate environments, and the rhythms have created different political system and exceptional cultural diversity in contrast to Atlantic cities. Physically, it leads the development of plazas and the importance of stairways which link sloping lands.

 

Rhythmanlysist could still be a valuable concept to understand complex urban situations. However, we are living in the digital era. As Mitchell (Mitchell, 1999) denoted, the rhythms of our ordinary life are changing by digital communication. Every day tremendous data, which are invisible and inaudible, are generating, and its flows push us into the massive ocean of heterogeneous rhythms. Therefore, new Rhythmanlysist in the digital age needs other capacities. Capturing the digital data in real time and synthesizing it should be essential requirements to create or maintain Eurhythmia. While the cities of the 20th century needed Rhythmanlysist, now it is the time of ‘Rhythmconductor’ who collects digital rhythms, reorganises its tempos-meters-articulations and resonates new contexts. We can easily find good examples of Rhythmconductor like below.
 

Image 2. London Public Bike share map by Oliver O’Brien. http://bikes.oobrien.com/london/

Image 3. Analysis of Happiness on Twitter during 9th September 2008 to 31stAugust 2011.

Dodds PS,  Harris KD,  Kloumann IM,  Bliss CA,  Danforth CM  (2011) Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE 6(12)

 

This radical change of the rhythm gives an opportunity to redefine the scopes of each social group. Citizens collect and utilize the data by their mobile devices; furthermore, they solve complex urban problems by themselves. (Desouza and Bhagwatwar, 2012) The role of planners is challenging to make new rhythms by spreading effective information and stimulating civic participation using social media instead traditional managers’ role within mainstream planning structures. (Tayebi, 2013) Also, Scientists’ role is shifting. According to Wright (Wright, 2013), scientific researchers had focused to find reasons of urban problems until the last decade, however; their voices are getting stronger to solve problems and provide alternatives in the decision making process with geospatial data and geographical analysis.

 

You can find the detail of Lefebvre’s book from Google and Amazon.

 

Desouza, K C and Bhagwatwar, A, 2012, “Citizen Apps to Solve Complex Urban Problems” Journal of Urban Technology 19(3) 107–136.

Mitchell, W J, 1999 E-topia: “Urban life, Jim–but not as we know it” (MIT Press, Cambridge, MA).

Tayebi, A, 2013, “Planning activism: Using Social Media to claim marginalized citizens’ right to the city” Cities 32 88–93.

Wright, D, 2013, “Bridging the Gap Between Scientists and Policy Makers: Whither Geospatial? | Esri Insider” Esri Insider, http://blogs.esri.com/esri/esri-insider/2013/02/11/bridging-the-gap-between-scientists-and-policy-makers-whither-geospatial/.

 

 

Continue reading »
Big Data, Book, Lefebvre, Rhythmanalysis, Rhythmconductor, Smart city

From Rhythmanalyst to Rhythmconductor- Rhythmanalysis: Space, Time and Everyday Life

Posted on by
 

 

 

 

Image 1. The book cover of ‘Rhythmanalysis: Space, Time and Everyday Life’

 
In the book, Rhythmanalysis: Space, Time and Everyday Life, French sociologist Henri Lefebvre suggests ‘Rhythm’ as an alternative tool to understand and analyse everyday urban life beyond visual recognition. He argues that we can examine the true nature of cities from the human body, the basic unit of urban life, to substantial urban structures through rhythms.

 

Invisible rhythms are generating, repeating and transforming in cities. Lefebvre categorizes types of rhythm, which deeply intervene the life and make a foundation of law, institution and culture, based on its characteristics. Among them, the author particularly insists to pay attention to two aspects of rhythms that Arrhythmia which is creating discordance between or among two or more rhythms, and Eurhythmia which is staying in the state of harmony and balance. He asserts that it is important to convert Arrhythmia in the city that causes inequality and injustice to Eurhythmia which sustains healthy urban condition.

 

‘Rhythmanlysist’ is a fresh idea from the book published in 1992. Rhythmanlysist hears sounds of the city and reveals hidden systems behind visual images with sensing and analysing the change of spatial aspects in timing. As a rhythmanlysist, Lefebvre investigates Mediterranean cities. He presents some insights that the rhythms of Mediterranean cities are derived from specific geographical and climate environments, and the rhythms have created different political system and exceptional cultural diversity in contrast to Atlantic cities. Physically, it leads the development of plazas and the importance of stairways which link sloping lands.

 

Rhythmanlysist could still be a valuable concept to understand complex urban situations. However, we are living in the digital era. As Mitchell (Mitchell, 1999) denoted, the rhythms of our ordinary life are changing by digital communication. Every day tremendous data, which are invisible and inaudible, are generating, and its flows push us into the massive ocean of heterogeneous rhythms. Therefore, new Rhythmanlysist in the digital age needs other capacities. Capturing the digital data in real time and synthesizing it should be essential requirements to create or maintain Eurhythmia. While the cities of the 20th century needed Rhythmanlysist, now it is the time of ‘Rhythmconductor’ who collects digital rhythms, reorganises its tempos-meters-articulations and resonates new contexts. We can easily find good examples of Rhythmconductor like below.
 

Image 2. London Public Bike share map by Oliver O’Brien. http://bikes.oobrien.com/london/

Image 3. Analysis of Happiness on Twitter during 9th September 2008 to 31stAugust 2011.

Dodds PS,  Harris KD,  Kloumann IM,  Bliss CA,  Danforth CM  (2011) Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE 6(12)

 

This radical change of the rhythm gives an opportunity to redefine the scopes of each social group. Citizens collect and utilize the data by their mobile devices; furthermore, they solve complex urban problems by themselves. (Desouza and Bhagwatwar, 2012) The role of planners is challenging to make new rhythms by spreading effective information and stimulating civic participation using social media instead traditional managers’ role within mainstream planning structures. (Tayebi, 2013) Also, Scientists’ role is shifting. According to Wright (Wright, 2013), scientific researchers had focused to find reasons of urban problems until the last decade, however; their voices are getting stronger to solve problems and provide alternatives in the decision making process with geospatial data and geographical analysis.

 

You can find the detail of Lefebvre’s book from Google and Amazon.

 

Desouza, K C and Bhagwatwar, A, 2012, “Citizen Apps to Solve Complex Urban Problems” Journal of Urban Technology 19(3) 107–136.

Mitchell, W J, 1999 E-topia: “Urban life, Jim–but not as we know it” (MIT Press, Cambridge, MA).

Tayebi, A, 2013, “Planning activism: Using Social Media to claim marginalized citizens’ right to the city” Cities 32 88–93.

Wright, D, 2013, “Bridging the Gap Between Scientists and Policy Makers: Whither Geospatial? | Esri Insider” Esri Insider, http://blogs.esri.com/esri/esri-insider/2013/02/11/bridging-the-gap-between-scientists-and-policy-makers-whither-geospatial/.

 

 

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Big Data, Book, Lefebvre, Rhythmanalysis, Rhythmconductor, Smart city

University of Edinburgh, Chancellor’s Fellowships

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TweetThe University of Edinburgh are advertising for up to 50 ‘Chancellor’s fellowships’. These are ‘tenure track’ fellowships with very low teaching loads for the first three years and then progressively acquiring the full duties of University Lecturer across the 5 year period of the Fellowship.   The School of Geoscience are looking for applications in […]

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Jobs

Assertions on crowdsourced geographic information & citizen science #1

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Looking across the range of crowdsourced geographic information activities, some regular patterns are emerging and it might be useful to start notice them as a way to think about what is possible or not possible to do in this area. Since I don’t like the concept of ‘laws’ – as in Tobler’s first law of […]

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citizen science, Concepts, Neogeography, OpenStreetMap, Usability, VGI, Volunteered Geographic Information

Protest is nothing new

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Yes, throughout the history of human being, protests have been here and there though fresh protest news cover on GoogleNews every day. [i] [ii] If we only count massive protests from 19th century, there were strong collective voices of French Revolution in 1848, Russian Revolution in 1917, 1968 protests in the world and Eastern Europe in 1989, and these were the generator of social changes each time.  

  

Not going too far away till the 19th century, more than 200 million protests have impacted on the life of people since 1979 despite ignoring hidden and unknown events.[iii] However, the number of protest has not been increasing so far based on the data of GDELT which is a research group to collect global political unrest data and provide daily report with geo-spatial data. It would mean that as growing the opportunities to see the news about protests, we might believe that protests have been common than in the past.[iv]

 

What is the key factor to force people into the street?

Recently, Bridge, Marsh and Sweeting (2013) argue the change of governing structure, from government to governance, is the essence of recent protests.[v] According to their opinion, it stimulates governments work together with private sectors and communities, so the boundary of different organisations is blurring far more than before. The changing forms of the organisations extend to the shifting role of citizens, emphasizing new forms of networks and accountability, and finally the nature of democracy. Amid this transition, people are more interested in direct citizenship, and we have been readily watching one form of direct democracy, protest.


Meanwhile, Castells (2012) insists that we need to consider the transformation of communication to understand current protests.[vi] The development of internet technology facilitates that people can send messages many to many and share resources with horizontal-endless networks by themselves. On the internet, which is an autonomous space and no government control by Castells’ opinion, people try to change power relationships around them for ‘a better humanity’ when the relationships disrupt their life. When desires and goals of people are emerging in urban spaces beyond the internet, we could watch them such as Arab Spring and Occupy movements.

 

[ii] Manuel Castells, The City and the Grassroots: Cross-Cultural Theory of Urban Social Movements, illustrated edition (Hodder Arnold, 1983).
[iii] Joshua Keating, “What Can We Learn from the Last 200 Million Things That Happened in the World?,” Foreign Policy Blogs, April 12, 2013, http://atfp.co/1cXGpaX
[iv] J Dana Stuster, “Mapped: Every Protest On The Planet Since 1979,” accessed January 8, 2014, http://bit.ly/KBBl1H.
[v] Gary Bridge, Alex Marsh, and David Sweeting, “Reconfiguring the Local Public Realm,” Policy&Politics 41, no. 3 (n.d.): 305–309. http://www.policypress.co.uk/journals_pap.asp

[vi] Manuel Castells, Networks of Outrage and Hope: Social Movements in the Internet Age (Polity Press, 2012).

 

Continue reading »
Castells, GDELT, history, internet, protest, social movement

Protest is nothing new

Posted on by
 

Yes, throughout the history of human being, protests have been here and there though fresh protest news cover on GoogleNews every day. [i] [ii] If we only count massive protests from 19th century, there were strong collective voices of French Revolution in 1848, Russian Revolution in 1917, 1968 protests in the world and Eastern Europe in 1989, and these were the generator of social changes each time.  

  

Not going too far away till the 19th century, more than 200 million protests have impacted on the life of people since 1979 despite ignoring hidden and unknown events.[iii] However, the number of protest has not been increasing so far based on the data of GDELT which is a research group to collect global political unrest data and provide daily report with geo-spatial data. It would mean that as growing the opportunities to see the news about protests, we might believe that protests have been common than in the past.[iv]

 

What is the key factor to force people into the street?

Recently, Bridge, Marsh and Sweeting (2013) argue the change of governing structure, from government to governance, is the essence of recent protests.[v] According to their opinion, it stimulates governments work together with private sectors and communities, so the boundary of different organisations is blurring far more than before. The changing forms of the organisations extend to the shifting role of citizens, emphasizing new forms of networks and accountability, and finally the nature of democracy. Amid this transition, people are more interested in direct citizenship, and we have been readily watching one form of direct democracy, protest.


Meanwhile, Castells (2012) insists that we need to consider the transformation of communication to understand current protests.[vi] The development of internet technology facilitates that people can send messages many to many and share resources with horizontal-endless networks by themselves. On the internet, which is an autonomous space and no government control by Castells’ opinion, people try to change power relationships around them for ‘a better humanity’ when the relationships disrupt their life. When desires and goals of people are emerging in urban spaces beyond the internet, we could watch them such as Arab Spring and Occupy movements.

 

[ii] Manuel Castells, The City and the Grassroots: Cross-Cultural Theory of Urban Social Movements, illustrated edition (Hodder Arnold, 1983).
[iii] Joshua Keating, “What Can We Learn from the Last 200 Million Things That Happened in the World?,” Foreign Policy Blogs, April 12, 2013, http://atfp.co/1cXGpaX
[iv] J Dana Stuster, “Mapped: Every Protest On The Planet Since 1979,” accessed January 8, 2014, http://bit.ly/KBBl1H.
[v] Gary Bridge, Alex Marsh, and David Sweeting, “Reconfiguring the Local Public Realm,” Policy&Politics 41, no. 3 (n.d.): 305–309. http://www.policypress.co.uk/journals_pap.asp

[vi] Manuel Castells, Networks of Outrage and Hope: Social Movements in the Internet Age (Polity Press, 2012).

 

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Castells, GDELT, history, internet, protest, social movement

Protest is nothing new

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Yes, throughout the history of human being, protests have been here and there though fresh protest news cover on GoogleNews every day. [i] [ii] If we only count massive protests from 19th century, there were strong collective voices of French Revolution in 1848, Russian Revolution in 1917, 1968 protests in the world and Eastern Europe in 1989, and these were the generator of social changes each time.  

  

Not going too far away till the 19th century, more than 200 million protests have impacted on the life of people since 1979 despite ignoring hidden and unknown events.[iii] However, the number of protest has not been increasing so far based on the data of GDELT which is a research group to collect global political unrest data and provide daily report with geo-spatial data. It would mean that as growing the opportunities to see the news about protests, we might believe that protests have been common than in the past.[iv]

 

What is the key factor to force people into the street?

Recently, Bridge, Marsh and Sweeting (2013) argue the change of governing structure, from government to governance, is the essence of recent protests.[v] According to their opinion, it stimulates governments work together with private sectors and communities, so the boundary of different organisations is blurring far more than before. The changing forms of the organisations extend to the shifting role of citizens, emphasizing new forms of networks and accountability, and finally the nature of democracy. Amid this transition, people are more interested in direct citizenship, and we have been readily watching one form of direct democracy, protest.


Meanwhile, Castells (2012) insists that we need to consider the transformation of communication to understand current protests.[vi] The development of internet technology facilitates that people can send messages many to many and share resources with horizontal-endless networks by themselves. On the internet, which is an autonomous space and no government control by Castells’ opinion, people try to change power relationships around them for ‘a better humanity’ when the relationships disrupt their life. When desires and goals of people are emerging in urban spaces beyond the internet, we could watch them such as Arab Spring and Occupy movements.

 

[ii] Manuel Castells, The City and the Grassroots: Cross-Cultural Theory of Urban Social Movements, illustrated edition (Hodder Arnold, 1983).
[iii] Joshua Keating, “What Can We Learn from the Last 200 Million Things That Happened in the World?,” Foreign Policy Blogs, April 12, 2013, http://atfp.co/1cXGpaX
[iv] J Dana Stuster, “Mapped: Every Protest On The Planet Since 1979,” accessed January 8, 2014, http://bit.ly/KBBl1H.
[v] Gary Bridge, Alex Marsh, and David Sweeting, “Reconfiguring the Local Public Realm,” Policy&Politics 41, no. 3 (n.d.): 305–309. http://www.policypress.co.uk/journals_pap.asp

[vi] Manuel Castells, Networks of Outrage and Hope: Social Movements in the Internet Age (Polity Press, 2012).

 

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Castells, GDELT, history, internet, protest, social movement

Visualising Empathy

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As part of our exploration of how to facilitate empathy by allowing greater communication of emotion we have been putting together some prototypes which explore not textual representations of emotion. In the example here we have ‘hacked’ a candle so that we can change the colour of its flame. There […]

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Why Geographers Should Learn to Code

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This article is published in the January 2014 issue of Geographical Magazine – page 77.

In my opinion, a geography curriculum should require students to learn how to code, ensuring that they’re equipped for a changed job market that’s increasingly detached from geographic information systems (GIS) as they were originally conceived.

The ability to code relates to basic programming and database skills that enable students to manipulate large and small geographic data sets, and to analyse them in automated and transparent ways. Although it might seem odd for a geographer to want to learn programming languages, we only have to look at geography curriculums from the 1980s to realise that these skills used to be taught. For example, it wouldn’t have been unusual for an undergraduate geographer to learn how to programme a basic statistical model (for example, regression) from base principles in Fortran (a programming language popular at the time) as part of a methods course. But during the 1990s, the popularisation of graphical user interfaces in software design enabled many statistical, spatial analysis and mapping operations to be wrapped up within visual and menu-driven interfaces, which were designed to lower the barriers of entry for users of these techniques. Gradually, much GIS teaching has transformed into learning how these software systems operate, albeit within a framework of geographic information science (GISc) concerned with the social and ethical considerations of building representations from geographic data. Some Masters degrees in GISc still require students to code, but few undergraduate courses do so.

The good news is that it’s never been more exciting to be a geographer. Huge volumes of spatial data about how the world looks and functions are being collected and disseminated. However, translating such data safely into useful information is a complex task. During the past ten years, there has been an explosion in new platforms through which geographic data can be processed and visualised. For example, the advent of services such as Google Maps has made it easier for people to create geographical representations online. However, both the analysis of large volumes of data and the use of these new methods of representation or analysis do require some level of basic programming ability. Furthermore, many of these developments have not been led by geographers, and there is a real danger that our skill set will be seen as superfluous to these activities in the future without some level of intervention. Indeed, it’s a sobering experience to look through the pages of job advertisements for GIS-type roles in the UK and internationally. Whereas these might once have required knowledge of a particular software package, they increasingly look like advertisements for computer scientists, with expected skills and experience that wouldn’t traditionally be part of an undergraduate geography curriculum.

Many of the problems that GIS set out to address can now be addressed with mainstream software or shared online services that are, as such, much easier to use. If I want to determine the most efficient route between two locations, a simple website query can give a response within seconds, accounting for live traffic-volume data. If I want to view the distribution of a census attribute over a given area, there are multiple free services that offer street-level mapping. Such tasks used to be far more complex, involving specialist software and technical skills. There are now far fewer job advertisements for GIS technicians than there were ten years ago. Much traditional GIS-type analysis is now sufficiently non-technical that it requires little specialist skill, or has been automated through software services, with a subscription replacing the employment of a technician. The market has moved on!

Geographers shouldn’t become computer scientists; however, we need to reassert our role in the development and critique of existing and new GIS. For example, we need to ask questions such as which type of geographic representation might be most appropriate for a given dataset. Today’s geographers may be able to talk in general terms about such a question, but they need to be able to provide a more effective answer that encapsulates the technologies that are used for display. Understanding what is and isn’t possible in technical terms is as important as understanding the underlying cartographic principles. Such insights will be more available to a geographer who has learnt how to code.

Within the area of GIS, technological change has accelerated at an alarming rate in the past decade and geography curriculums need to ensure that they embrace these developments. This does, however, come with challenges. Academics must ensure that they are up to date with market developments and also that there’s sufficient capacity within the system to make up-skilling possible.Prospective geography undergraduates should also consider how the university curriculums have adapted to modern market conditions and whether they offer the opportunity to learn how to code.

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Why Geographers Should Learn to Code

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This article is published in the January 2014 issue of Geographical Magazine – page 77.

In my opinion, a geography curriculum should require students to learn how to code, ensuring that they’re equipped for a changed job market that’s increasingly detached from geographic information systems (GIS) as they were originally conceived.

The ability to code relates to basic programming and database skills that enable students to manipulate large and small geographic data sets, and to analyse them in automated and transparent ways. Although it might seem odd for a geographer to want to learn programming languages, we only have to look at geography curriculums from the 1980s to realise that these skills used to be taught. For example, it wouldn’t have been unusual for an undergraduate geographer to learn how to programme a basic statistical model (for example, regression) from base principles in Fortran (a programming language popular at the time) as part of a methods course. But during the 1990s, the popularisation of graphical user interfaces in software design enabled many statistical, spatial analysis and mapping operations to be wrapped up within visual and menu-driven interfaces, which were designed to lower the barriers of entry for users of these techniques. Gradually, much GIS teaching has transformed into learning how these software systems operate, albeit within a framework of geographic information science (GISc) concerned with the social and ethical considerations of building representations from geographic data. Some Masters degrees in GISc still require students to code, but few undergraduate courses do so.

The good news is that it’s never been more exciting to be a geographer. Huge volumes of spatial data about how the world looks and functions are being collected and disseminated. However, translating such data safely into useful information is a complex task. During the past ten years, there has been an explosion in new platforms through which geographic data can be processed and visualised. For example, the advent of services such as Google Maps has made it easier for people to create geographical representations online. However, both the analysis of large volumes of data and the use of these new methods of representation or analysis do require some level of basic programming ability. Furthermore, many of these developments have not been led by geographers, and there is a real danger that our skill set will be seen as superfluous to these activities in the future without some level of intervention. Indeed, it’s a sobering experience to look through the pages of job advertisements for GIS-type roles in the UK and internationally. Whereas these might once have required knowledge of a particular software package, they increasingly look like advertisements for computer scientists, with expected skills and experience that wouldn’t traditionally be part of an undergraduate geography curriculum.

Many of the problems that GIS set out to address can now be addressed with mainstream software or shared online services that are, as such, much easier to use. If I want to determine the most efficient route between two locations, a simple website query can give a response within seconds, accounting for live traffic-volume data. If I want to view the distribution of a census attribute over a given area, there are multiple free services that offer street-level mapping. Such tasks used to be far more complex, involving specialist software and technical skills. There are now far fewer job advertisements for GIS technicians than there were ten years ago. Much traditional GIS-type analysis is now sufficiently non-technical that it requires little specialist skill, or has been automated through software services, with a subscription replacing the employment of a technician. The market has moved on!

Geographers shouldn’t become computer scientists; however, we need to reassert our role in the development and critique of existing and new GIS. For example, we need to ask questions such as which type of geographic representation might be most appropriate for a given dataset. Today’s geographers may be able to talk in general terms about such a question, but they need to be able to provide a more effective answer that encapsulates the technologies that are used for display. Understanding what is and isn’t possible in technical terms is as important as understanding the underlying cartographic principles. Such insights will be more available to a geographer who has learnt how to code.

Within the area of GIS, technological change has accelerated at an alarming rate in the past decade and geography curriculums need to ensure that they embrace these developments. This does, however, come with challenges. Academics must ensure that they are up to date with market developments and also that there’s sufficient capacity within the system to make up-skilling possible.Prospective geography undergraduates should also consider how the university curriculums have adapted to modern market conditions and whether they offer the opportunity to learn how to code.

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