Getting various types of GEOINT to end-users quickly and in the correct format remains a complex process.

Systems, technologies, people, concepts of operations, standards, formats and protocols all must all come together to create a standard and sharable geospatial foundation. Yet there's also a massive amount of data being gleaned from geospatial intelligence (GEOINT), which poses a big-data challenge that complicates the efficient and flawless sharing of geospatial intelligence across echelons.

"We have data from satellites, unmanned aerial vehicles, sea- and land-based sensors, social networks and a proliferation of mobile devices generating an avalanche of location-based information," observed Rich Campbell, chief technologist for the federal division of McLean, Va.-based cloud computing provider EMC. Yet in the field, bandwidth remains scarce and limited. This critical choke point is leading the Defense Department and an array of networking and IT contractors to look for solutions. "Increased bandwidth and better bandwidth management strategies will [ultimately] enable more effective data sharing," Campbell said.

As potential bandwidth enhancements are identified and evaluated, close attention is also being paid to data analytics. Powerful analytical tools are used to transform raw data into actionable intelligence in real time, thereby enabling vital information to be efficiently delivered to end users. "Data analytics provides the ability to refine the data sets needed by mission commanders," Campbell said. "Analysts can refine data into smaller sub sets using data analytics, and mission commanders see only the relevant GEOINT."

Campbell noted that increased virtualization promises more effective information management and sharing. "As the GEOINT community moves toward a more virtualized environment, we're seeing a convergence of the compute, analytics and storage infrastructures and a series of significant benefits ranging from improved analytics across a distributed infrastructure to reduced costs," he said. 

Data and Policy

Data management, classification and policy are also widely viewed as roadblocks that are hampering the rapid and efficient sharing of GEOINT across echelons. "For sharing to become easier, our military and defense agencies will need to increase bandwidth, classification and management [efforts] and then adjust policy to accommodate and more effectively prioritize mission commanders' information needs," Campbell said.

The term ‘geocoding’ has become one of the latest buzzwords in the business space, and is touted for its ability to deliver a host of benefits. Geocodes provide a precise location, expressed as latitude and longitude co-ordinates, and as such, have many applications across different industries. This data is not new, but is becoming more useful with the introduction of spatial business intelligence tools that present business information on a map.

Geocodes can be beneficial to any business which uses or manages address information in any way, says Gary Allemann, MD of Master Data Management, as it allows objects which have an address, such as customers, to be plotted on a map and compared to objects that do not have an address, such as the customer demographic, or risk profile, of the area.

The benefits and challenges of linking address and spatial data are explored in detail in the white paper: "An Introduction to Geocoding", which can be downloaded here.

One of the applications of geocoding is to improve service delivery, both for retail and government sectors. Geocoding data can be used to determine the density of populations or the density of customers in specific areas, as well as the layout and distance of these customers or populations to existing stores or facilities such as hospitals, schools and so on. A visual plot of store coverage overlaid with customer locations allows retailers to plan the locations for new stores, thus providing convenience to customers and therefore more likely foot traffic in the stores. For government service delivery, new facilities such as hospitals and schools can be planned for precisely where they are needed, and costs can be allocated to the correct service area.

Location is also important for risk management. By plotting the location of an insured risk on a map, and overlaying this with risk factors such as flood plains, or crime levels, insurance firms can optimally calculate risk for each insured address. Location data can be critical disaster management, making it simpler to ensure that emergency services arrive as quickly as possible.

Another common application is to use location data for route planning. Shipping and logistics firms can optimise productivity by plotting delivery and collection addresses on a map, reducing errors in delivery and plotting the most efficient routes for each vehicle. This helps to optimise efficiency of the delivery chain, saving time, fuel and resources, while at the same time improving customer service.

Geocoding data is available from various sources. However, it is often not a simple matter to add this data into existing address information, since lack of standardisation and poor quality data can negatively impact the applicability of geocoding data.

For example, the spatial data, or data from the geocoding database, may recognise “CAPE TOWN” as a city. However, in a company’s records, the name may be misspelled, as CAPE TWON or CAPETOWN, or even be in another language, such as KAAPSTAD, or may be buried in the wrong field in the database. These are common issues which can cause a failure in the lookup of geocoding data, meaning that accurate locations cannot be added.

In order to reap the benefits of geocoding data, it is critical to apply sophisticated cleansing and matching to improve address quality before geocodes are applied. Data quality and standardisation tools, such as the Trillium Software System, find these common errors and correct them, as well as identifying the same address that may be represented in two different ways, based on its elements. For example, data cleansing for geocoding should be able to recognise that KERKSTRAAT 11, Pretoria, is the same address as 11 Church Street, Pretoria. By addressing data quality and standardisation issues, the probability of finding a match and being able to add an accurate location is vastly improved.

Geocoding data adds another dimension of information for businesses, and enables enhanced analytics to be conducted using geospatial information. Quality address data is a prerequisite for realising the benefits that geocoding can deliver! Download the white paper to find out more.