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The Ultimate Guide to Map Data 2021
What is Map Data?
Over the last few years the usage and development of maps has increased dramatically. Now everyone and everything has become connected, Map Data has become more important than ever. Increased use cases has meant Map Data analytics have had to evolve rapidly to support increased demand for more accurate and detailed data. Map Data analyzes information about locations and populations and is used in the creation of responsive and interactive maps and location intelligence and analyse geographic content.
Map Data systems supply a wide variety of maps, including weather and traffic maps and information on global populations. Map Data high resolution global maps can be realtime, recent or historic. For example, Ordinance survey alone make over 20,000 changes a day to the map of Great Britain. Map Data is important for many sectors, including health, education, business, manufacturing and insurance. Building a digital representation of reality that is always accurate and fresh is one of Map Data ‘s greatest challenges. Map Data is at the forefront of mapping innovations. It serves automotive OEMs, businesses and governments that require the most accurate location intelligence, using cutting-edge technology and industrial processes.
Who uses Map Data and for what use cases?
Map Data analysis can be used by a great many people for a lot of different purposes. It can help find the best locations for investment. It supplies information about the Earth’s natural and built environments, which can be used for building and planning decisions. Map Data can be used for location purposes for staff, by building an accurate picture of your services and customer and staff locations and calculating customer drive times. It can be used by businesses for site selections for new business locations. It can identify potential development sites for installations, such as wind turbines. It can be used by police to map areas by volume of crime and types of crime, to decide priority areas for patrol. It can determine who or what is within a short distance of a facility so businesses can choose locations close to highly populated areas. It can identify changing trends over time periods so businesses can see how their customer demographics have changed. It can locate sites which are most prime for development. It can use competitor, demographic and economic data to locate new market opportunities. It can show the optimized routes for deliveries. It can identify vulnerable people during emergencies. It can be used by utilities to keep customers informed of maintenance works.
Map Data helps advertisers measure performance and gain deeper insights into campaign attribution by applying real-world location context to consumer behaviour. It helps marketers create more relevant campaigns by applying location intelligence to their marketing strategy. This can help them build a more targeted campaign that improves customer experience. Map Data can help with getting an in-depth understanding of consumer behaviour by combining places people visit, traffic patterns, weather, seasonality and a host of other variables to build up a precise picture of your consumers. You can then leverage these location insights to create a more engaging customer experience.
Map Data can be utilized by cities to solve transportation problems such as traffic congestion and to increase efficiency and scalability. It can help improve transport planning and create frictionless end-to-end journeys, thereby improving customer experience.
What are typical Map Data attributes?
There are numerous Map Data attributes depending on what it is you wish to measure, for instance, geographical attributes for a city might include: population, types of public transport, and land-use patterns. Census data might include ethnicity, marital status and types of heating used. Ordinal data might analyse political boundaries and transportation routes. Social surveys of preferences and perceptions also usually come under ordinal map data. Interval map data measures temperature and year. Ratio level map data measures area and distance. The usefulness of Map Data analytics is that they don’t just use base maps. Instead, with the uses of a GIS system, several types of data are merged together, much like one would add ingredients to make a cake. The result is something much greater than the separate components.
How is Map Data typically collected?
Map Data may come from many sources. It may be already collected or you may need to source it yourself. Primary sources of data may include taking photos or videos, conducting interviews, marking locations or site surveys. Secondary source data is data that is already collected and can come from many sources, such as paper maps, Digital Globe, VGI, geovisualisation, digital imaging, laser scanners, stereo images, GPS, remote sensing and photogrammetry. This primary or secondary sourcing is your base layer. It is then typically combined with a GIS system to get the information you require. Intuitive spatial analysis tools help you learn more from your data. Map data can be combined with demographical and lifestyle data to add valuable context. You can create Map data with a variety of tools and then adjust your data on an interactive map to find the answers you need. BMW is a cased in study of applying Map Data to find real-world solutions.
BMW employs smart technology to increase safety for drivers. They employ the latest HD maps, which show a wealth of detail, not just roads and routes. They are created using billions of pixels to create realistic detail, which is displayed in three-dimensional images. The raw material is not provided by a camera, but by Lidar (Light Detection and Ranging). This is a highly sensitive vehicle-mounted laser scanner which shoots high-frequency pulses of laser light. These are reflected by objects and returned to the sensor, which can measure the distance from each individual point.
NASA, for example, used this technology to accurately measure the exact topography of the moon.
Radar and ultrasound are also used to measure distances to other vehicles and objects in the vicinity. Optical cameras provide information about the driving environment and traffic and recognize road signs and traffic lights. They are not 100% accurate. It’s always possible a road sign may be obscured but they can be compared with HD maps to check for accuracy. The HD map is used as an additional sensor and this double checking increases driving safety. BMW play as many traffic situations as possible to their computer, together with an assessment of the situations. Gradually, the computer develops its own understanding of which driving strategies are most suitable. According to BMW the computer is being trained by reinforcement learning. The goal for BMW is to create cars that are so intelligent in automated mode that they behave correctly in any traffic situation. So far, the BMW 5 series can regulate the speed of the vehicle depending on traffic conditions, make sure that the vehicle stays in its lane, and assist in manoeuvres such as switching lanes. BMW hopes to have a fully automated car by 2021.
How to assess the quality of Map Data?
One of the most important issues with Map Data is the quality of the data. Map Data should be specific, relevant and as error free as possible. It is impossible for Map Data to be completely error free, but data should be as valid, accurate and precise as possible. Map data should be ‘fit for purpose’ depending on the accuracy required. Some projects are more quality sensitive than others. System errors usually follow a pattern and can often be corrected by adjusting the measurements by a constant factor. Random errors are more difficult to detect and correct. Accuracy can be improved by taking the average data point from multiple measurements. As with other forms of data analytics, regular testing and measurements by quantitive systems designed to do so can assess data quality. Freshness is an integral part of accurate mapping. And accuracy is necessary for smooth organizational operations, enabling businesses to give accurate ETAs to customers, deliver on time and meet stringent specifications.
How is Map Data typically priced?
Map Data is usually paid for as a pay-as-you go service, with tiered prices depending on the volume of maps you request. Most providers will supply a monthly bill for the Map Data you have used the previous month.
What are the common challenges when buying Map Data?
One of the common challenges when purchasing Map Data is ensuring the information is accurate and up-to-date. Otherwise any results gathered will be inaccurate and outdated. Challenges to obtaining accurate Map Data include human error, environmental characteristics changing over time and instrument errors as instruments can only be so precise, even if the error is so small as to be undetectable.
What to ask Map Data providers?
If you are considering purchasing a Map Data analytics system, here are some questions you might want to ask your provider:
- Will the Map data system meet the needs of my business?
- How comprehensive is the Map Data coverage?
- How often is it updated?
- How accurate is the Map Data system and how is this measured?
- How detailed is the map data?
- How soon will it be delivered?
- Will it link with other systems?
- Will it integrate with my existing systems or do I need new IT?
Who are the best Map Data providers?
Finding the right Map Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Map Data providers that you might want to buy Map Data from are OpenStreetMap, Mapbox, 2GIS, MapData Services, and MapKing.
Where can I buy Map Data?
Data providers and vendors listed on Datarade sell Map Data products and samples. Popular Map Data products and datasets available on our platform are Weather API by Ambee, HERE Map Rendering by MBI Geodata, and OnPoint Geospatial by Weather Source.
How can I get Map Data?
You can get Map Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Map Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Map Data APIs, feeds and streams to download the most up-to-date intelligence.