Address geocoding
Address geocoding, or simply geocoding, is the process of taking a text-based description of a location, such as an address or the name of a place, and returning geographic coordinates to identify a location on the Earth's surface. Reverse geocoding on the other hand converts geographic coordinates to the description of a location, usually the name of a place or an addressable location. Geocoding relies on a computer representation of address points, the street / road network, together with postal and administrative boundaries.
- Geocode : provide geographical coordinates corresponding to.
- Geocode : is a code that represents a geographic entity.
- Geocoder : a piece of software or a service that implements a geocoding process i.e. a set of interrelated components in the form of operations, algorithms, and data sources that work together to produce a spatial representation for descriptive locational references.
History
Geocoding – a subset of Geographic Information System spatial analysis – has been a subject of interest since the early 1960s.1960s
In 1960, the first operational GIS – named the Canada Geographic Information System – was invented by Dr. Roger Tomlinson, who has since been acknowledged as the father of GIS. The CGIS was used to store and analyze data collected for the Canada Land Inventory, which mapped information about agriculture, wildlife, and forestry at a scale of 1:50,000, in order to regulate land capability for rural Canada. However, the CGIS lasted until the 1990s and was never available commercially.On 1 July 1963, five-digit ZIP codes were introduced nationwide by the United States Post Office Department. In 1983, nine-digit ZIP+4 codes were brought about as an extra identifier in more accurately locating addresses.
In 1964, the Harvard Laboratory for Computer Graphics and Spatial Analysis developed groundbreaking software code – e.g. GRID, and SYMAP – all of which were sources for commercial development of GIS.
In 1967, a team at the Census Bureau – including the mathematician James Corbett and Donald Cooke – invented Dual Independent Map Encoding – the first modern vector mapping model – which ciphered address ranges into street network files and incorporated the "percent along" geocoding algorithm. Still in use by platforms such as Google Maps and MapQuest, the "percent along" algorithm denotes where a matched address is located along a reference feature as a percentage of the reference feature's total length. DIME was intended for the use of the United States Census Bureau, and it involved accurately mapping block faces, digitizing nodes representing street intersections, and forming spatial relationships. New Haven, Connecticut, was the first city on Earth with a geocodable streets network database.
1980s
In the late 1970s, two main public domain geocoding platforms were in development: GRASS GIS and MOSS. The early 1980s saw the rise of many more commercial vendors of geocoding software, namely Intergraph, ESRI, CARIS, ERDAS, and MapInfo Corporation. These platforms merged the 1960s approach of separating spatial information with the approach of organizing this spatial information into database structures.In 1986, Mapping Display and Analysis System became the first desktop geocoding software, designed for MS-DOS. Geocoding was elevated from the research department into the business world with the acquisition of MIDAS by MapInfo. MapInfo has since been acquired by Pitney Bowes, and has pioneered in merging geocoding with business intelligence; allowing location intelligence to provide solutions for the public and private sectors.
1990s
The end of the 20th century had seen geocoding become more user-oriented, especially via open-source GIS software. Mapping applications and geospatial data had become more accessible over the Internet.Because the mail-out/mail-back technique was so successful in the 1980 census, the U.S. Bureau of Census was able to put together a large geospatial database, using interpolated street geocoding. This database – along with the Census' nationwide coverage of households – allowed for the birth of TIGER.
Containing address ranges instead of individual addresses, TIGER has since been implemented in nearly all geocoding software platforms used today. By the end of the 1990 census, TIGER "contained a latitude/longitude-coordinate for more than 30 million feature intersections and endpoints and nearly 145 million feature 'shape' points that defined the more than 42 million feature segments that outlined more than 12 million polygons."
TIGER was the breakthrough for "big data" geospatial solutions.
2000s
The early 2000s saw the rise of Coding Accuracy Support System address standardization. The CASS certification is offered to all software vendors and advertising mailers who want the United States Postal Services to assess the quality of their address-standardizing software. The annually renewed CASS certification is based on delivery point codes, ZIP codes, and ZIP+4 codes. Adoption of a CASS certified software by software vendors allows them to receive discounts in bulk mailing and shipping costs. They can benefit from increased accuracy and efficiency in those bulk mailings, after having a certified database. In the early 2000s, geocoding platforms were also able to support multiple datasets.In 2003, geocoding platforms were capable of merging postal codes with street data, updated monthly. This process became known as "conflation".
Beginning in 2005, geocoding platforms included parcel-centroid geocoding. Parcel-centroid geocoding allowed for a lot of precision in geocoding an address. For example, parcel-centroid allowed a geocoder to determine the centroid of a specific building or lot of land. Platforms were now also able to determine the elevation of specific parcels.
2005 also saw the introduction of the Assessor's Parcel Number. A jurisdiction's tax assessor was able to assign this number to parcels of real estate. This allowed for proper identification and record-keeping. An APN is important for geocoding an area which is covered by a gas or oil lease, and indexing property tax information provided to the public.
In 2006, Reverse Geocoding and reverse APN lookup were introduced to geocoding platforms. This involved geocoding a numerical point location – with a longitude and latitude – to a textual, readable address.
2008 and 2009 saw the growth of interactive, user-oriented geocoding platforms – namely MapQuest, Google Maps, Bing Maps, and Global Positioning Systems. These platforms were made even more accessible to the public with the simultaneous growth of the mobile industry, specifically smartphones.
2010s
The 2010s saw vendors fully support geocoding and reverse geocoding globally. Cloud-based geocoding application programming interface and on-premises geocoding have allowed for a greater match rate, greater precision, and greater speed. There is now a popularity in the idea of geocoding being able to influence business decisions. This is the integration between the geocoding process and business intelligence.The future of geocoding also involves three-dimensional geocoding, indoor geocoding, and multiple language returns for the geocoding platforms.
Geocoding process
Geocoding is a task which involves multiple datasets and processes, all of which work together. Some of the components are provided by the user, while others are built into the geocoding software.Input dataset
Input data are the descriptive, textual information which the user wants to turn into numerical, spatial data through the process of geocoding. These are often included in a table with other attributes of the locations. Input data is classified into two categories:; Relative input data
; Absolute input data
To achieve the greatest accuracy, the geocodes in the input dataset need to be as correct as possible, and formatted in standard ways. Thus, it is common to first go through a process of data cleansing, often called "address scrubbing," to find and correct any errors. This is especially important for databases in which participants enter their own location geocodes, frequently resulting in a variety of forms and misspellings.
Geocoder algorithm
The third component is software that matches each geocode in the input dataset to the attributes of a corresponding feature in the reference dataset. Once a match is made, the location of the reference feature can be attached to the input row. These algorithms are of two types:; Direct match
; Interpolated match
The algorithm is rarely able to perfectly locate all of the input data; mismatches can occur due to misspelled or incomplete input data, imperfect reference data, or unique regional geocoding systems that the algorithm does not recognize. Many geocoders provide a follow-up stage to manually review and correct suspect matches.
Address interpolation
A simple method of geocoding is address interpolation. This method makes use of data from a street geographic information system where the street network is already mapped within the geographic coordinate space. Each street segment is attributed with address ranges. Geocoding takes an address, matches it to a street and specific segment. Geocoding then interpolates the position of the address, within the range along the segment.Example
Take for example: 742 Evergreen TerraceLet's say that this segment of Evergreen Terrace runs from 700 to 799. Even-numbered addresses fall on the east side of Evergreen Terrace, with odd-numbered addresses on the west side of the street. 742 Evergreen Terrace would be located slightly less than halfway up the block, on the east side of the street. A point would be mapped at that location along the street, perhaps offset a distance to the east of the street centerline.