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entities are tagged with location reporting devices. These devices report their location at specified intervals to a central data management center from where this data is aggregated and the tagged entities pattern of movement within the city is tracked on representational maps. 2. Sensor networks with fixed sensing probes: In this type of projects, sensors are distributed all over the city and they monitor changes in particular aspect of their context and report this information in specified intervals to a central data management center from where this information is aggregated and represented on representational maps. To this effect the received information from each fixed sensing probe is associated with its unique, and again fixed, geographical location on the representational map which allows the navigation of real-time information received from various sensing probes interfacing with the map or comparative monitoring of multiple sensors visible within a certain map view at the same time. 3. Sensor networks with dynamic sensing probes: In this type of projects, sensors are distributed all over the city that are dynamic and constantly navigate the city and monitor changes in particular aspect of their context and report this information along with their real-time location at specified intervals to a central data management center from where this information is aggregated and represented on representational maps. To this effect the received information from each sensing probe is associated with its reported real-time geographical location and is mapped on the representational map. 4. Urban Sensing projects that map previously geo-tagged information: In this type of projects an already existing repository of content that is associated with geographical location exists and a representational map is utilized to demonstrate how content is related to geographical location.

Absolute geographical location comes in the format of Latitude/Longitude pairs:

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In some urban sensing projects geographical location becomes important. Geographical location can be relevant in four types of sensing projects: 1. Tag and Track urban sensing projects : - PowerPoint PPT Presentation

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Page 1: Absolute geographical location comes in the format of Latitude/Longitude  pairs:

In some urban sensing projects geographical location becomes important. Geographical location can be relevant in four types of sensing projects:

1. Tag and Track urban sensing projects :In this type of projects particular material or human entities are tagged with location reporting

devices. These devices report their location at specified intervals to a central data management center from where this data is aggregated and the tagged entities pattern of movement within the city is tracked on representational maps.

2. Sensor networks with fixed sensing probes:In this type of projects, sensors are distributed all over the city and they monitor changes in

particular aspect of their context and report this information in specified intervals to a central data management center from where this information is aggregated and represented on representational maps. To this effect the received information from each fixed sensing probe is associated with its unique, and again fixed, geographical location on the representational map which allows the navigation of real-time information received from various sensing probes interfacing with the map or comparative monitoring of multiple sensors visible within a certain map view at the same time.

3. Sensor networks with dynamic sensing probes:In this type of projects, sensors are distributed all over the city that are dynamic and constantly

navigate the city and monitor changes in particular aspect of their context and report this information along with their real-time location at specified intervals to a central data management center from where this information is aggregated and represented on representational maps. To this effect the received information from each sensing probe is associated with its reported real-time geographical location and is mapped on the representational map.

4. Urban Sensing projects that map previously geo-tagged information:In this type of projects an already existing repository of content that is associated with

geographical location exists and a representational map is utilized to demonstrate how content is related to geographical location.

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Absolute geographical location comes in the format of Latitude/Longitude pairs:

Latitude (shown as a horizontal line) is the angular distance, in degrees, minutes, and seconds of a point north(+) or south (-) of the Equator. Lines of latitude are often referred to as parallels. Longitude (shown as a vertical line) is the angular distance, in degrees, minutes, and seconds, of a point east (+) or west (-) of the Prime (Greenwich) Meridian. Lines of longitude are often referred to as meridians.

There are two different formats in taking note of lattitude and longitude of geographical coordinates:1. deg-min-sec suffixed with N/S/E/W (e.g. 40°44′55″N, 73 59 11W), where for precision purposes, degrees of longitude and latitude have been divided into minutes (') and seconds ("). There are 60 minutes in each degree. Each minute is divided into 60 seconds. Seconds can be further divided into tenths, hundredths, or even thousandths. 2. signed decimal degrees without compass direction, where negative indicates west/south (e.g. 40.7486, -73.9864)

Here is how one format is translated to the other format:

deg-min-sec suffixed with N/S/E/W to signed decimal degrees

signed decimal degrees to deg-min-sec suffixed with N/S/E/W

Lon= dd° mm’ ss” E/WLon= +/- dd+mm/60+ss/3600

Lon=+/- xx.yyyydd= xx0.yyyy*60 =zz.wwwwmm=zz0.wwww*60=vv.qqqqss=vv.qqqqLon=xx ° zz’ vv.qqqq” E/W

Lat= dd° mm’ ss” N/SLat= +/- dd+mm/60+ss/3600

Lat=+/- xx.yyyydd= xx0.yyyy*60 =zz.wwwwmm=zz0.wwww*60=vv.qqqqss=vv.qqqqLat=xx ° zz’ vv.qqqq” N/S

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If the longitude and latitude of two points are known, the following formulas allow for deducing further information about relative position of two points.

This is for calculation of distance between the two points. Take note that this is to calculate great-circle distances between the two points – that is, the shortest distance over the earth’s surface – giving an ‘as-the-crow-flies’ distance between the points (ignoring any hills!).

d = acos(sin(lat1).sin(lat2)+cos(lat1).cos(lat2).cos(long2−long1)).RR= radius of earth =6371 km

This is the midpoint along a great circle path between the two points.

Bx = cos(lat2).cos(Δlong)By = cos(lat2).sin(Δlong)latm = atan2(sin(lat1) + sin(lat2) , √((cos(lat1)+Bx)² + By²))lonm = lon1 + atan2(By, cos(lat1)+Bx)

This is for the initial bearing (sometimes referred to as forward azimuth) which if followed in a straight line along a great-circle arc will take you from the start point to the end point:

θ = atan2( sin(Δlong).cos(lat2) , cos(lat1).sin(lat2) − sin(lat1).cos(lat2).cos(Δlong) )For final bearing, simply take the initial bearing from the end point to the start point and reverse it (using θ = (θ+180) % 360). Point 1 Point 2

http://www.movable-type.co.uk/scripts/latlong.html

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float calculateDistance(float lat1,float lat2, float lon1, float lon2){ float lat1Rad=radians(lat1); float lat2Rad=radians(lat2); float lon1Rad=radians(lon1); float lon2Rad=radians(lon2); int R=6371; // Calculating the distance between two points //d = acos(sin(lat1).sin(lat2)+cos(lat1).cos(lat2).cos(long2−long1)).R float dis= acos(sin(lat1Rad) * sin(lat2Rad) + cos(lat1Rad) * cos(lat2Rad) * cos(lon2Rad-lon1Rad))*R; return dis;}

Processing Function to Calculate Distance Between Two Points with Known Geographical Coordinates

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float [] calculateMidPointCoordinates(float lat1,float lat2, float lon1, float lon2){ float lat1Rad=radians(lat1); float lat2Rad=radians(lat2); float lon1Rad=radians(lon1); float lon2Rad=radians(lon2); // Calculating the coordinates of the midpoint //Bx = cos(lat2).cos(Δlong) //By = cos(lat2).sin(Δlong) //latm = atan2(sin(lat1) + sin(lat2) , √((cos(lat1)+Bx)² + By²)) //lonm = lon1 + atan2(By, cos(lat1)+Bx) float Bx = cos(lat2Rad)*cos(lon2Rad-lon1Rad); float By = cos(lat2Rad)*sin(lon2Rad-lon1Rad); float latmRad = atan2( sin(lat1Rad) + sin(lat2Rad) , pow( pow(cos(lat1Rad)+Bx,2) + pow(By,2) ,.5) ); float lonmRad=lon1Rad+atan2(By, cos(lat1Rad)+Bx); float latm=degrees(latmRad); float lonm=degrees(lonmRad); float[] coordinates=new float[2]; coordinates[0]=latm; coordinates[1]=lonm; return coordinates;}

Processing Function to Calculate the Coordinates of the Mid-point Between Two Points with Known Geographical Coordinates

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String LontoDDMMSSFormat(float lonm){ float lonmRad=lonm; lonm=abs(lonm); int lonmDD=int(lonm); int lonmMM=int((lonm-lonmDD)*60); float lonmSS=((lonm-lonmDD)*60-int((lonm-lonmDD)*60))*60; String lonmDDMMSS=lonmDD+"°"+lonmMM+"'"+lonmSS+"\""; if (lonmRad>0) lonmDDMMSS=lonmDDMMSS+ " E"; else lonmDDMMSS=lonmDDMMSS+ " W"; return lonmDDMMSS;}

String LattoDDMMSSFormat(float latm){ float latmRad=latm; latm=abs(latm); int latmDD=int(latm); int latmMM=int((latm-latmDD)*60); float latmSS=((latm-latmDD)*60-int((latm-latmDD)*60))*60; String latmDDMMSS=latmDD+"°"+latmMM+"'"+latmSS+"\""; if (latmRad>0) latmDDMMSS=latmDDMMSS+ " N"; else latmDDMMSS=latmDDMMSS+ " S"; return latmDDMMSS;}

String signedDecimaltoDDMMSS (float Angle){ //Change format from Signed Decimal to DDMMSS int AngleDD=int(Angle); int AngleMM=int((Angle-AngleDD)*60); float AngleSS=((Angle-AngleDD)*60-int((Angle-AngleDD)*60))*60; String AngleDDMMSS=AngleDD+"°"+AngleMM+"'"+AngleSS+"\""; return AngleDDMMSS; }

Processing Functions to Convert Latitude, Longitude and Bearing Angle from Signed Decimal Format to Degree-Minute-Second (DDMMSS) Format

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float calculateInitialBearing(float lat1,float lat2, float lon1, float lon2){ float lat1Rad=radians(lat1); float lat2Rad=radians(lat2); float lon1Rad=radians(lon1); float lon2Rad=radians(lon2); //Caclulating the initial bearing //θ = atan2( sin(Δlong).cos(lat2) , cos(lat1).sin(lat2) − sin(lat1).cos(lat2).cos(Δlong) ) float initialBearingAngleRad=atan2( sin(lon2Rad-lon1Rad)*cos(lat2Rad) , cos(lat1Rad)*sin(lat2Rad) - sin(lat1Rad)*cos(lat2Rad)*cos(lon2Rad-lon1Rad) ); float initialBearingAngle=degrees(initialBearingAngleRad); return initialBearingAngle;}

float calculateFinalBearing(float lat1,float lat2, float lon1, float lon2){ float lat1Rad=radians(lat1); float lat2Rad=radians(lat2); float lon1Rad=radians(lon1); float lon2Rad=radians(lon2); //Calculating the final bearing //θ = (θ+180) % 360). float finalBearingAngleRad=atan2( sin(lon1Rad-lon2Rad)*cos(lat1Rad) , cos(lat2Rad)*sin(lat1Rad) - sin(lat2Rad)*cos(lat1Rad)*cos(lon1Rad-lon2Rad) ); float finalBearingAngle=degrees(finalBearingAngleRad); finalBearingAngle=(finalBearingAngle+180)%360; return finalBearingAngle;}

Processing Functions to Calculate Initial Bearing and Final Bearing Between Two Points with Known Geographical Coordinates

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In urban sensing projects that the geographical location is of importance in deciphering the dynamics of the city representational maps are the best interface to convey the sensed or extracted information to the users.To this effect two different map interfaces can be used:1. In cases that the only thing to be presented is the geographical location, or that the geo-localized sensed or deduced information can be overlaid on the map, two-dimensional maps are the

interfaces of choice.2. In cases that certain quantitative sensed or deduced information is to be associated with their corresponding locations, the representational map needs to accommodate the third dimension

which would be populated by this information.

Representational Maps for Interfacing with Urban Information with Geographical Coordinates/Location Relevance

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Representational Maps for Interfacing with Urban Information with Geographical Coordinates/Location Relevance2D Maps and Representing Pattern of Movement

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Representational Maps for Interfacing with Urban Information with Geographical Coordinates/Location Relevance2D Maps and Representing Sensed Presence or Pattern of Crowding

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Representational Maps for Interfacing with Urban Information with Geographical Coordinates/Location Relevance2D Maps and Representing Situated Sensor Data with Size as Indicator of Magnitude

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Representational Maps for Interfacing with Urban Information with Geographical Coordinates/Location Relevance2D Maps and Representing Situated Sensor Data with Color Coding as Indicator of Magnitude

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

The highlighted code allows for changing the mode of the map. Options are: ArialProvider, RoadProvider, and HybridProvider.

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

Google Maps set to RoadProvider Mode

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

Google Maps set to Arial Provider Mode

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

Google Maps set to Arial Provider Mode

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

The highlighted code allows for changing the color composition of the map. The applied Filter() command filters the display window as defined by one of the following modes:

THRESHOLD - converts the image to black and white pixels depending if they are above or below the threshold defined by the level parameter. The level must be between 0.0 (black) and 1.0(white). If no level is specified, 0.5 is used.GRAY - converts any colors in the image to grayscale equivalentsINVERT - sets each pixel to its inverse valuePOSTERIZE - limits each channel of the image to the number of colors specified as the level parameterBLUR - executes a Guassian blur with the level parameter specifying the extent of the blurring. If no level parameter is used, the blur is equivalent to Guassian blur of radius 1.OPAQUE - sets the alpha channel to entirely opaque.ERODE - reduces the light areas with the amount defined by the level parameter.DILATE - increases the light areas with the amount defined by the level parameter.

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(INVERT); map = new InteractiveMap(this, new Microsoft.RoadProvider());

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(GRAY); map = new InteractiveMap(this, new Microsoft.RoadProvider());

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(POSTERIZE,3); map = new InteractiveMap(this, new Microsoft.AerialProvider());

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(THRESHOLD,.4); map = new InteractiveMap(this, new Microsoft.AerialProvider());

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(DILATE); filter(ERODE); map = new InteractiveMap(this, new Microsoft.AerialProvider()); map = new InteractiveMap(this, new Microsoft.AerialProvider());

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Librarytallows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.

filter(THRESHOLD); filter(INVERT); filter(THRESHOLD); map = new InteractiveMap(this, new Microsoft.AerialProvider()); map = new InteractiveMap(this, new Microsoft.AerialProvider());

Multiple Filters can be applied together to achieve more complex visual effects

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Library allows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.Blend() command can be applied to the map to manipulate its color scheme. It blends a region of pixels from one image into another (or in itself again) with full alpha channel support. There is a choice of modes to blend the source pixels (A) with the ones of pixels in the destination image (B):

blend(x, y, width, height, dx, dy, dwidth, dheight, MODE) blend(srcImg, x, y, width, height, dx, dy, dwidth, dheight, MODE)

Parameters : x int: X coordinate of the source's upper left corner y int: Y coordinate of the source's upper left corner width int: source image width height int: source image height dx int: X coordinate of the destinations's upper left corner dy int: Y coordinate of the destinations's upper left corner dwidth int: destination image width dheight int: destination image height srcImg PImage: a image variable referring to the source image

MODE

BLEND - linear interpolation of colours: C = A*factor + BADD - additive blending with white clip: C = min(A*factor + B, 255)SUBTRACT - subtractive blending with black clip: C = max(B - A*factor, 0)DARKEST - only the darkest colour succeeds: C = min(A*factor, B)LIGHTEST - only the lightest colour succeeds: C = max(A*factor, B)DIFFERENCE - subtract colors from underlying image.EXCLUSION - similar to DIFFERENCE, but less extreme.MULTIPLY - Multiply the colors, result will always be darker.SCREEN - Opposite multiply, uses inverse values of the colors.OVERLAY - A mix of MULTIPLY and SCREEN. Multiplies dark values, and screens light values.HARD_LIGHT - SCREEN when greater than 50% gray, MULTIPLY when lower.SOFT_LIGHT - Mix of DARKEST and LIGHTEST. Works like OVERLAY, but not as harsh.DODGE - Lightens light tones and increases contrast, ignores darks. Called "Color Dodge" in Illustrator and Photoshop.BURN - Darker areas are applied, increasing contrast, ignores lights. Called "Color Burn" in Illustrator and Photoshop.

All modes use the alpha information (highest byte) of source image pixels as the blending factor. If the source and destination regions are different sizes, the image will be automatically resized to match the destination size. If the srcImg parameter is not used, the display window is used as the source image.

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Library allows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.Blend() command can be applied to the map to manipulate its color scheme. It blends a region of pixels from one image into another (or in itself again) with full alpha channel support. There is a choice of modes to blend the source pixels (A) with the ones of pixels in the destination image (B):

blend(x, y, width, height, dx, dy, dwidth, dheight, MODE) blend(srcImg, x, y, width, height, dx, dy, dwidth, dheight, MODE)

For manipulating the color of the map you can apply the blend function and an image that is as big as the screen window and contains the base color to be used in blend function:void draw(){ background(0); map.draw(); //BLEND, ADD, SUBTRACT, LIGHTEST, DARKEST, DIFFERENCE, EXCLUSION //MULTIPLY, SCREEN, OVERLAY, HARD_LIGHT, SOFT_LIGHT, DODGE, BURN PImage colorImage=loadImage("colorImage.jpg"); blend(colorImage, 0, 0, width, height, 0, 0, width, height, SCREEN); checkCursor();}

PImage 1200*700 Display Window 1200*700

MODE=BURN

MODE=SUBTRACT

MODE= DIFFERENCE

MODE= SCREEN

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Library allows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.Blend() command can be applied to the map to manipulate its color scheme. It blends a region of pixels from one image into another (or in itself again) with full alpha channel support. There is a choice of modes to blend the source pixels (A) with the ones of pixels in the destination image (B):

blend(x, y, width, height, dx, dy, dwidth, dheight, MODE) blend(srcImg, x, y, width, height, dx, dy, dwidth, dheight, MODE)

For manipulating the color of the map you can apply the blend function without specifying a source image to be blended. This way the displaywindow itself would be the default source image for the blend operation.void draw(){ background(0); map.draw(); //BLEND, ADD, SUBTRACT, LIGHTEST, DARKEST, DIFFERENCE, EXCLUSION //MULTIPLY, SCREEN, OVERLAY, HARD_LIGHT, SOFT_LIGHT, DODGE, BURNblend(0, 0, width, height, 0, 0, width, height, SCREEN); checkCursor();}

MODE=ADD

MODE= EXCLUSION

MODE= DIFFERENCE

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Processing and Modestmaps Library : Interactive Navigatable Geo-localized Maps

Modest Maps is a library that displays tile-based maps, from GoogleMaps. The provided Processing code that utilizes Modest Maps Library allows for seamless zooming and panning and also has an integral Google Map API which allows to zoom to a semantically specified geographical location such as an indicated city name or street address.

Different lines of code in this applet allows for control over graphical and color characteristics of the base representational map.For manipulating the color scheme of the map customized functions can be incorporated that apply pixel manipulation to the map area in display window.

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PImage myImage; //define an image objectmyImage = loadImage(“test.jpg"); //load itsize(myImage.width,myImage.height); //size it to fit the windowimage(myImage, 0,0); //display the image

for(int y=0; y<myImage.height; y++) //for all pixels in the y directionfor(int x=0; x<myImage.width; x++){ //for all pixels in the x directioncolor myPixel = get(x,y); //get a pixel's colorint r = int(red(myPixel)); //extract the red valueint g = int(green(myPixel)); //extract the green valueint b = int(blue(myPixel)); //extract the blue valuecolor inverse = color(255-r,255-g, b); //make a color by inverting (255-value)set(x,y,inverse); //set the pixel’s color in the image}

Base code for Image Processing

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void changeMapColor(){ for(int y=0; y<height; y++) //for all pixels in the y direction { for(int x=0; x<width; x++){ //for all pixels in the x direction color myPixel = get(x,y); //get a pixel's color int r = int(red(myPixel)); //extract the red value int g = int(green(myPixel)); //extract the green value int b = int(blue(myPixel)); //extract the blue value r=255-r;//Specify how red factor is changed g=255-g;//Specify how green factor is changed b=b;//Specify how blue factor is changed color newColor = color(r,g,b); set(x,y,newColor);//Set the pixel's color in the image } }}

Custom Function for Pixel –base manipulation of map interface color scheme based on Image Processing Code

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void setup(){ setupInterface(); // Map Mode Options would be "new Microsoft.HybridProvider()" or "new Microsoft.AerialProvider()" or "new Microsoft.RoadProvider()" map = new InteractiveMap(this, new Microsoft.AerialProvider()); map.setCenterZoom(new Location(43.688484,-79.413445), 18);// zoom 0 is the whole world, 19 is street level // the parameters passed to new location( ) are lat and lon of the intended center of the map}

Initial Zoom Level and Zoom Center of the Interactive Map Interface

map.setCenterZoom(new Location(43.688484,-79.413445), 19); map.setCenterZoom(new Location(43.688484,-79.413445), 3);

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Now that we have covered all the aspects of controlling the visual quality of the interactive 2D map interface, it is time to go through various possibilities in terms of plotting information with geo-locational relevance to the interactive map. In each exercise that follows a hypothetical scenario is discussed. For each scenario a data set is presented that is populated with relevant geo-localized data. Different applets are discussed that each allow for plotting the data to the map.

2Dmap and Data Visualization

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2Dmap and Data Visualization-Plotting Presence data or Pattern of Distribution

Hypothetical Scenario:Flickre API is used to retrieve images with geo-location information that fit the query for particular semantic tags. The result is a text file containing a series of Latitude/Longitude pairs each representing the location to which a particular image has been associated by the contributing user of the digital file. Each data record in the file has the following format: Latitude*Longitude

The first step is to add the txt file t o the processing applet:

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2Dmap and Data Visualization-Plotting Presence data or Pattern of Distribution

Hypothetical Scenario:Flickre API is used to retrieve images with geo-location information that fit the query for particular semantic tags. The result is a text file containing a series of Latitude/Longitude pairs each representing the location to which a particular image has been associated by the contributing user of the digital file. Each data record in the file has the following format: Latitude*Longitude

The second step is to write a function for plotting the information and calling it in draw loop of the processing applet:

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2Dmap and Data Visualization-Plotting Presence data or Pattern of Distribution

Hypothetical Scenario:Flickre API is used to retrieve images with geo-location information that fit the query for particular semantic tags. The result is a text file containing a series of Latitude/Longitude pairs each representing the location to which a particular image has been associated by the contributing user of the digital file. Each data record in the file has the following format: Latitude*Longitude

The second step is to write a function for plotting the information and calling it in draw loop of the processing applet.

The function has two major sections. In the first section –highlighted in red here- the data file is read by the applet and geographical coordinate pairs are retrieved. In the second section-highlighted in blue- the corresponding x/y coordinates form each lat/lon geo-location pair is computationally deduced . Each x/y pair is used to place a circle on the map at the point that corresponds to the coordinates pair. Here is the function :

void plotInformation(){

//Read data file and extract location pairs

String[] data=loadStrings("MultiplePoints-LatLon.txt"); float[] lat=new float[data.length]; float[] lon=new float[data.length]; for(int i=0; i<data.length; i++){ float []temp=float(split(data[i], '*')); lat[i]=temp[0]; lon[i]=temp[1]; //println(lat[i]+","+lon[i]); }

//Plot location to map

fill(255,0,0); noStroke(); for(int i=0; i<data.length; i++){ //Grab the X/Y of a point on the map from known Lat/Long Location locTemp = new Location(lat[i], lon[i]); Point2f pointTemp = map.locationPoint(locTemp); int pointX=int(pointTemp.x); int pointY=int(pointTemp.y); //Draw a pointer at extracted x and y coordinates ellipse(pointX, pointY,5,5); }

}

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of MovementHypothetical Scenario:10 moving agents that are navigating the city have been tagged by location reporting mechanisms and a log file of their location tracking has been created. The result is a text file containing data records that consist of unique identification code of the agent, reported latitude of the agent location, reported longitude of the location, time of the location report. Each data record in the file has the following format: ID*Latitude*Longitude *TimeStamp

The first step is to add the txt file t o the processing applet:

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of MovementHypothetical Scenario:10 moving agents that are navigating the city have been tagged by location reporting mechanisms and a log file of their location tracking has been created. The result is a text file containing data records that consist of unique identification code of the agent, reported latitude of the agent location, reported longitude of the location, time of the location report. Each data record in the file has the following format: ID*Latitude*Longitude *TimeStamp

The second step is to write a function for plotting the information and calling it in draw loop of the processing applet.

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of MovementHypothetical Scenario:10 moving agents that are navigating the city have been tagged by location reporting mechanisms and a log file of their location tracking has been created. The result is a text file containing data records that consist of unique identification code of the agent, reported latitude of the agent location, reported longitude of the location, time of the location report. Each data record in the file has the following format: ID*Latitude*Longitude *TimeStamp

The second step is to write a function for plotting the information and calling it in draw loop of the processing applet.The function has two major sections. In the first section –highlighted in red here- the data file is read by the applet and geographical coordinate pairs are retrieved along with the timestamp of each location read and the unique Identification number of the location read that represents the corresponding agent. In the second section-highlighted in blue- the corresponding x/y coordinates form each lat/lon geo-location pair is computationally deduced . Each x/y pair is used to place a circle on the map at the point that corresponds to the coordinates pair. A line is drawn between each location read and the previous location read for each and every unique identification number. The result is ten separate lines each color coded based on the identity of the mobile agent, representing the trajectory of its movement. A keyPressed function is also incorporated to enable the user to specify which agent’s trajectory is to be plotted on interactive map. Here is the function:

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of Movementvoid plotInformation(){ //Read data file and extract location pairs String[] data=loadStrings("MultipleMobileAgents-IDLatLonTime.txt"); color[] Color={ color(255,0,0),color(0,255,0),color(0,0,255),color(255,255,0),color(255,0,255), color(0,255,255),color(0,200,100), color(0,100,200), color(200,100,0), color(100,200,0) }; int[] id=new int[data.length]; float[] lat=new float[data.length]; float[] lon=new float[data.length]; long[] time=new long[data.length]; for(int i=0; i<data.length; i++){ String []temp=split(data[i], '*'); id[i]=int(temp[0]); lat[i]=float(temp[1]); lon[i]=float(temp[2]); time[i]=Long.parseLong(temp[3]); //println(id[i]+","+lat[i]+","+lon[i]+","+time[i]); } //Plot the tragectory of Movement to map int[]prevX=new int[10]; int[]prevY=new int[10]; for(int i=0; i<data.length; i++){ if(id[i]==state || state==10){ if(state!=10) { text("Agent"+state,50,10); } fill(Color[id[i]]); stroke(Color[id[i]]); strokeWeight(1); //Grab the X/Y of a point on the map from known Lat/Long Location locTemp = new Location(lat[i], lon[i]); Point2f pointTemp = map.locationPoint(locTemp); int pointX=int(pointTemp.x); int pointY=int(pointTemp.y); //Draw a pointer at extracted x and y coordinates ellipse(pointX, pointY,10,10); if(prevX[id[i]]+prevY[id[i]]!=0){ line(prevX[id[i]],prevY[id[i]],pointX,pointY); } prevX[id[i]]=pointX; prevY[id[i]]=pointY; } }}

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of Movement

A keyPressed function is also incorporated to enable the user to specify which agent’s trajectory is to be plotted on interactive map. The default state is -1 which means nothing is plotted on the map. Pressing any key from 0 to 9 results in the tragectory of movement of the corresponding mobile agent to be plotted on the map. Stroking the ‘a’ key would result in plotting of all the ten tragectories at the same time. Stroking the ‘n’ key results in change of state to the default -1 state which means nothing is going to be plotted to the map. Here is the function:

void keyPressed(){ if (key=='0') state=0; if (key=='1') state=1; if (key=='2') state=2; if (key=='3') state=3; if (key=='4') state=4; if (key=='5') state=5; if (key=='6') state=6; if (key=='7') state=7; if (key=='8') state=8; if (key=='9') state=9; if(key=='a') state=10; if(key=='n') state=-1;}

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2Dmap and Data Visualization-Plotting Tracked Entities or Patterns of Movement-Incorporating Time for Time-Based Visualization of Location

In the previous version the identity field of the data records along with the longitude and latitude fields were used to recreate the trajectory of movement of each and every monitored agent. The last field of the data records in the previously discussed dataset is the UNIX Time Stamp of the location read. Incorporating the time of location read into the data visualization algorithm would allow for time-base visualizations including rewinding the trajectory of movement and/or visualizing how the agents move in the space through time.