The History of the Internet (Infographic)

January 15, 2013 By News Staff

Though there may be some question as to who really, really invented the Internet, the Net's milestones through history are clear, as detailed by this infographic from security software firm AVG -- from the birth of Arpanet in 1969 to the first virus in 1971, all the way through the number of Internet users breaking 2.4 billion in 2012.

GIS Interview Questions

GIS interview questions from questions-interviews.com. 

What is spatial interpolation?
1. The process of establishing values for areas outside the boundary of an existing set of data points.
2. The process of modelling spatial pattern from a set of one or more data layers
3. The process of establishing values for areas between an existing set of discrete observations
4. The process of establishing a statistical relationship between two spatially correlated variables

The process of establishing values for areas between an existing set of discrete observations.

Which of the following are considered the main problems facing overlay operations in GIS?
1. Selecting threshold criteria
2. Topological inconsistencies
3. The Modifiable Arial Unit Problem (MAUP)
4. Processing overheads
5. Visual complexity

Selecting threshold criteria
The Modifiable Arial Unit Problem (MAUP)
Visual complexity

Assuming a pair of binary raster data layers, which of the following could be used as the equivalent of a Boolean AND overlay in cartographic modelling?
1. Layer 1 – layer 2
2. Layer 1 + layer 2
3. Layer 1 / layer 2
  4. Layer 1 * layer 2

Layer 1 – layer 2
Layer 1 + layer 2
Layer 1 * layer 2

What is point-in-polygon overlay?
1. A method interpolating point data
2. An overlay method used to determine which points lay within the boundary of a polygon
3. An overlay method used to determine the distance between a point and it is nearest neighboring polygon
4. An overlay method used to reclassify polygon data

An overlay method used to determine which points lay within the boundary of a polygon

Which of the following overlay methods would you use to calculate the length of road within a forest polygon?
1. Erase
2. Union
3. Line-in-polygon
4. Point-in-polygon

Line-in-polygon

Which of the following could you use a buffer operation?
1. Calculating the distance from one point to another
2. Calculating the area of overlap between two polygon data layers
3. Determining the area within a set distance from a point, line or area feature
4. Calculating the number of observations within a set distance of a point, line or area feature

Determining the area within a set distance from a point, line or area feature

Calculating the number of observations within a set distance of a point, line or area feature

What is reclassification?
1. The process of combining one or more data ranges into a new data range to create a new data layer.
2. The process of combing two or more data layers
3. The process of simplifying data in a data layer
4. An analytical technique based on point data.

The process of combining one or more data ranges into a new data range to create a new data layer.

What is Manhattan distance?
1. The distance between two points in a raster data layer calculated as the number of cells crossed by a straight line between them.
2. The distance between two points in a vector data layer calculated as the length of the line between them.
3. The distance between two points in a raster data layer calculated as the sum of the cell sides intersected by a straight line between them.

The distance between two points in a raster data layer calculated as the sum of the cell sides intersected by a straight line between them.

Which of the following spatial interpolation techniques is an example of a local, exact, abrupt, and deterministic interpolator?
1. Thiessen polygons
2. TIN
3. Spatial moving average

Thiessen polygons

What is the difference between slope and aspect?
1. Slope is the gradient directly down the fall line, while aspect is the direction of the fall line relative to north.
2. Slope is the direction of the fall line, while aspect is the gradient of the fall line.
3. Slope is the distance down the fall line from the top of the slope to its bottom, while aspect is the percentage gradient of this line averaged over its full distance.
4. Slope is the gradient of the fall line relative to vertical, while aspect is the direction of the fall line relative to the line of greatest slope.

Slope is the gradient directly down the fall line, while aspect is the direction of the fall line relative to north.

What is location-allocation modelling?
1. A method of site location based on overlaying multiple siting criteria maps.
2. A method of allocating resources within an area of interest using buffer analyses
3. A method of matching supply with demand across a network by locating a limited set of resources using network analysis
4. A method within network analysis used to determine delivery routes

A method of matching supply with demand across a network by locating a limited set of resources using network analysis

What is the possible number of combinations in which a delivery van can visit five different points on a network?
1. 25
2. 120
3. 10
4. 3125

120

For the Happy Valley ski resort example, which GIS analyses could be used to determine which hotels are within 200m of a main road.
1. Union overlay and line-in-polygon overlay
2. Buffer analysis and erase overlay
3. Buffer and point-in-polygon overlay
4. Intersect overlay and buffer analysis
5. Proximity analysis and reclassification

Proximity analysis and reclassification
Buffer and point-in-polygon overlay

A buffer zone around a point feature will be a circle.
1. True
2. False

True

Filtering is used on raster data to change the value of a cell based on the attributes of neighboring cells.
1. True
2. False

True

Filtering could be used to smooth noisy data caused by problems with data collection devices.
1. True
2. False

True

The Jordan method used for point in polygon analysis is also known as the Intersect method.
1. True
2. False

False

It is an ecological fallacy to assume that all the individuals within a defined area have the same level of income.
1. True
2. False

True

Exact interpolation methods are so called because they give very accurate results.
1. True
2. False

False

The most common use of Theissen s Polygons is to create contour lines.
1. True
2. False

False

Slope can be calculated from the formula S = b2 - c2.
1. True
2. False

False

Ray tracing is a technique used in network analysis.
1. True
2. False

False

ZVI is the abbreviation for Zone of Varying Intensity.
1. True
2. False

False

NYC to Add Citywide ‘Wayfinding’ Maps to Encourage Walking, Business

Source: http://transportationnation.org/2013/01/14/look-nyc-to-add-citywide-wayfinding-maps-to-encourage-walking/

By Alex Goldmark | 01/14/2013 – 12:02 am

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(Image courtesy of NYC DOT)

Even with smartphone maps, a waffle iron street grid and numbered streets in most of Manhattan, too many pedestrians are getting lost in New York City according to the NYC Department of Transportation. The solution, or part of it, will begin rolling out in March: maps. Lots of them. Designed just for pedestrians to be placed on sidewalks and eventually on bike share stations all around the five boroughs.
“We have a great system of signage for cars, but we don’t have a good system of signage for people,” said Jeanette Sadik-Khan, NYC’s Transportation Commissioner. (Earlier this week she unveiled newly designed, and less cluttered, parking signs). Starting in March, New York City will install 150 ‘wayfinding’ signs on sidewalks in Manhattan, Brooklyn and Queens as part of a citywide system that will roll out in phases at a cost of $6 million, most of it borne by local business improvement districts.

A sample of what NYC's new wayfinding maps will look like. Courtesy NYC DOT.

The sidewalk signage will show pedestrians where they are and which way they are facing — a study last year found that many New Yorkers couldn’t point to north when asked. Transit, local attractions, and businesses are placed on a large map of the local street grid with  circles indicating where you can reach with a five minute walk, and how long it will take to get to other attractions. Like countdown clocks in subways, knowing the time and effort involved in a trip can make it more appealing. The signs, the DOT hopes, will encourage more walking.
“We’re very excited about it and think it will be a big boon, not only for visitors … but also for business.” A slowly ambling customer visiting a new neighborhood, or a new route, is much more likely to check out a new shop than a driver is to stop, park, and peek in.
“New York is a perfect place to have a wayfinding system because nearly one third of all trips are made by foot,” Sadik-Khan said. A little encouragement to walk could be a tipping point to leave the car at home, she says, pointing out that a quarter of all car trips in NYC are less than a mile, a distance people could walk.
The signs will roll out in Chinatown, Midtown Manhattan, Long Island City, Prospect Heights and Crown Heights. ”These are heavily foot trafficked areas,” she says. “The lessons that we learn there… will help us as we build a bigger system citywide.”
When bike share stations are installed in May, they will include these maps. That would add several hundred more pedestrian maps in many new neighborhoods.
Here’s a full length sample:

Sample design of NYC's wayfinding maps. Courtesy NYC DOT.

PostGIS Solution to Create Parallel Lines for Two-Way Travel Direction

For almost all GIS road network data, if there is no physical barrier (e.g., road median or center island for pedestrians) separating the two directional traffic flows, the road segment will be represented by single link. When you need to show the two-way traffic on a map, you need a function to separate the single link into two parallel links for visualization purpose. The most popular transportation-GIS software tools such as ArcGIS and TransCAD do not provide a ready-to-use function for this link dualization job. Thanks for the release of PostGIS 2.0; it includes a new function "ST_OffsetCurve" that can do this job easily. For details of the function, please refer to the PostGIS function documentation:

http://postgis.refractions.net/docs/ST_OffsetCurve.html

Latest INRIX Gridlock Index (IGI) of Road Traffic Congestion Mirrors Slowly Improving US Economy

http://www.inrix.com/pressrelease.asp?ID=186 

Data through November 2012 show a continued increase in overall traffic congestion

Kirkland, Washington – January 7, 2013 – The November 2012 aggregate score for the INRIX Gridlock Index (IGI), a monthly measurement of road traffic congestion in 10 of the largest U.S. metropolitan areas, is 17.7, meaning that gridlock in these cities made the average driving trip 17.7 percent longer than necessary. Published by INRIX, a leading international provider of traffic information and driver services, the latest IGI score shows a sluggish yet enduring rebound in national traffic congestion aligned with the U.S. economy’s slow recovery. At 17.7 the IGI score for November 2012 is only slightly above October’s score of 17.6, but rising well above its historic low-point of 14.04, reached in July 2012.

“The good news is that IGI continued to show signs of an economic recovery. However, it’s less robust than we all would have liked, or expected, as we head into 2013,” said Bryan Mistele, CEO of INRIX. “In fact, some of the lower IGI scores we saw from last November are flashing yellow warning lights – for these local economies and possibly for the nation as a whole.”

Several metropolitan areas experienced month-over-month decreases below the aggregate level for the U.S.:

·       Atlanta’s IGI score decreased from 11.7 in October 2012 to 11.1 in November 2012, providing a precautionary note to the University of Georgia Terry College of Business Dean Robert Sumichrast’s recent prediction that the state will outpace national economic growth in 2013.

·       Chicago’s IGI score decreased from 15.4 in October 2012 to 13.4 in November 2012, aligned with a slowdown also seen in the University of Illinois’ November Flash Index, which measures Illinois’ growth rates in corporate earnings, consumer spending and personal income.

·       Detroit’s IGI score decreased from 8.5 in October 2012 to 6.6 in November 2012, and was the lowest of the Index’s 10 cities during the same period. November’s data confirm the city’s consistent place as an IGI laggard, highlighting its deep-seated economic issues.

The mixed economic picture captured in the November 2012 IGI is all the more notable given the backdrop of lower national gas prices in recent months.

While headline unemployment rates in IGI’s 10 metropolitan areas also have declined, the high number of discouraged workers nationwide (979,000 in November 2012) may exert downward pressure on overall traffic congestion.

Other highlights from the latest IGI release:

·       New York’s November 2012 IGI score was up 20% over the previous month, possibly reflecting a rebound from the reduced access seen in the aftermath of Hurricane Sandy.

·       A November 2012 IGI score of 17.2 shows that Boston is regaining the ground it lost after dropping from 17.23 in September 2012 to 16.8 in October 2012. Like all of the cities in the IGI, it has yet to retain the highs last seen in 2010.

·       Dallas’ November 2012 IGI score of 11.6 was little changed from its October 2012 score of 11.7, remaining stable in the face of the relatively upbeat assessment seen in the last quarterly survey of the Dallas Regional Chamber.

·       San Francisco’s November 2012 IGI score saw a very slight decrease month-over-month from 27 to 26.9. The tech-hub’s score remained well above its 2012 low-point of 18.7 (observed in July).

·       Los Angeles once again took top honors with the highest IGI score in the nation of 31.6, meaning that gridlock forced its drivers to endure an increase of almost 32% in the duration of their average driving trip.

·       Miami and Washington D.C. are the only IGI cities whose scores have increased every month since July 2012.

IGI Scores: November Averages

Percentage increase in the duration of the average road trip due to gridlock

Metro Area                 November 2010                     November 2011           November 2012

Atlanta                                 16.29                           11.91                           11.10

Boston                                 18.34                           15.67                           17.20

Chicago                               18.59                           15.27                           13.40

Dallas                                  13.51                           11.05                           11.60

Detroit                                  8.07                             7.64                             6.60

Los Angeles                         38.42                           29.46                           31.60

Miami                                   16.79                           15.04                           15.10

New York                             25.42                           21.71                           25.10

San Francisco                     26.01                           26.30                           26.90

Washington D.C.                 23.45                           18.86                           18.00

Month Average:                   20.49                           17.29                           17.70

IGI Scores: November Year-to-Date Averages

Percentage increase in the duration of the average road trip due to gridlock

Metro Area                           November YTD 2010   November YTD 2011   November YTD 2012

Atlanta                                 18.46                           14.73                           11.00

Boston                                 22.37                           19.41                           14.80

Chicago                               23.80                           18.23                           14.00

Dallas                                  16.07                           13.24                           10.70

Detroit                                  14.53                           10.43                           7.20

Los Angeles                         39.90                           31.85                           28.90

Miami                                   20.69                           17.26                           14.00

New York                             28.40                           24.35                           19.70

San Francisco                     27.25                           25.33                           23.50

Washington D.C.                 25.09                           20.20                           16.50

Month YTD Average:           23.66                           19.50                           16.00

INRIX Gridlock Index (IGI) Methodology

The INRIX Gridlock Index draws data from the INRIX Traffic Data Archive http://scorecard.inrix.com/scorecard/, a historical traffic information database comprised of data collected from hundreds of public and private sources, including a crowdsourced network of approximately 100 million vehicles and mobile devices.

Drawing on almost three years of trend data, INRIX has developed methods to interpret real-time traffic data to establish monthly and annual averages of traffic patterns in all major U.S. cities. These same methods can aggregate data over periods of time to provide reliable information on speeds and congestion levels for given segments of roads. Using this proprietary data collected from INRIX’s extensive network, the IGI analyzes and measures traffic trends in 10 of the top metropolitan markets in the U.S. The metropolitan areas used in the IGI are defined by the Core-Based Statistical Areas (CBSA), as determined by the United States Census Bureau.

There are two key building blocks for the analysis used in the IGI:

• Reference Speed (RS): An uncongested “free-flow” speed is determined for each road segment using the INRIX Traffic Data Archive.

• Calculated Speed (CS): Speed data from the INRIX Traffic Data Archive is analyzed to determine the “calculated speed” for each 15-minute period of each day, for each road segment every month (e.g. Monday from 06:00 to 06:15 for April 2012). Thus, each road segment has 672 corresponding calculated speed values per week – representing four 15-minute time windows for each hour of the day, multiplied by seven days in a week.

To assess congestion across a metropolitan area, INRIX utilizes and adapts several concepts that have been used in similar studies and previous INRIX analyses.

The IGI represents the barometer of congestion intensity. For a road segment with no congestion, the IGI would be zero. Each additional point in the IGI represents a percentage point increase in the average travel time of a commute above free-flow conditions during peak hours. An IGI of 30, for example, indicates a 20-minute free-flow trip will take 26 minutes during the peak travel time periods, which is a 6-minute (30 percent) increase over the free-flow travel time.

For each road segment, an IGI Index is calculated for each 15-minute period of the week, using the formula IGI= (RS/CS) – 1.

“Drive Time" Congestion: To assess and compare congestion levels year to year and between metropolitan areas, only “peak hours” are analyzed. Consistent with similar studies, peak hours are defined as the hours from 06:00 to 10:00 and 15:00 to 19:00, Monday through Friday – 40 of the 168 hours of a week.

For each metropolitan area, an overall level of congestion is determined for each of the 40 peak hours by determining the extent and amount of average congestion on the analyzed road network. This is computed as follows, once IGI's are calculated for each road segment:

• STEP 1: For each of the 40 peak hours, all road segments analyzed in the CBSA are checked. Each road segment where the IGI > 0 is contributing congestion and it is analyzed further.

• STEP 2: For each road segment contributing congestion, the amount the IGI is greater than 1 is multiplied by the length of the road segment, resulting in a congestion factor.

• STEP 3: For each 15-minute period, the overall metropolitan area congestion factor is the sum of the congestion factors calculated in STEP 2.

• STEP 4: To establish the metropolitan IGI for a given 15-minute period, the metropolitan congestion factor from STEP 3 is divided by the number of road miles analyzed.

• STEP 5: A peak period IGI is determined by averaging the 15-minute indices from STEP 4.¬¬

About INRIX

INRIX® is a leading traffic intelligence platform delivering smart data and advanced analytics to solve transportation issues worldwide. INRIX crowd sources real-time data from approximately 100 million vehicles and devices to deliver traffic and driving-related insight, as well as sophisticated analytical tools and services, across five industries in 35 countries.

With more than 200 customers and partners including Audi, ADAC, ANWB, BMW, the BBC, Ford Motor Company, the I-95 Coalition, MapQuest, Microsoft, NAVIGON, Telmap, Toyota and Vodafone, INRIX’s real-time traffic information and traffic forecasts help drivers save time every day. visit www.INRIX.com.