When geoinformatics engineering researchers at the Department of Energy’s Oak Ridge National Laboratory wanted to better understand changes in land areas and points of interest around the world, they turned to the locals — their data, at least.

Through an intelligent combination of geotagged social media, global location and natural language data, ORNL’s Junchuan Fan and Gautam Thakur developed MapSpace, a publicly available, scalable land-use modeling framework. By providing data characteristics broader and deeper than satellite imagery alone, MapSpace can generate population analytics invaluable for urban planning and disaster response. The researchers’ findings were published in the International Journal of Digital Earth.

“While the land cover — land, sea, water or desert — doesn’t change, the use of that land changes all the time,” said Thakur, leader of ORNL’s Location Intelligence group. “Understanding how land-use patterns change is essential for development of new services.”

Thakur said challenges with traditional satellite data are twofold. First, processing data accurately is an enormous task because of long download times and requirements of high-resolution imagery. Second, satellite images show only the tops of structures rather than their facades, which are more familiar vantage points. By using points of interest and geosocial data, Thakur and Fan can achieve multiple levels of semantic granularity, a measure of how accurately land use can be characterized.

For example, MapSpace could allow users to see that an area is commercial, zoom down to see it’s used for restaurants, then zoom in further to see the specific type of food served at a restaurant in the area.

The ability to capture land-use characteristics includes not only how buildings and areas are used but also how their function can change over weeks or even throughout a single day.

“Land-use layers are traditionally static, but there are various places in the world where the use of land changes during the day,” such as a town square used as a farmer’s market on weekend mornings, Thakur said. “How to capture these dynamics of spaces and how they change is also one of the things Junchuan has been spearheading.”

By understanding change over time, researchers could suggest new land-use purposes that may not have been possible before. For example, desolate urban areas that once contained thriving shopping malls could potentially be put to better use for developing apartments or industrial centers.

Perhaps almost as impressive as the capabilities they’ve developed is how quickly Thakur and Fan can develop them across a geographic area. Fan was able to develop land-use data for the entire continent of Africa in just two weeks. Before MapSpace, this would have taken months, if not years, he said. The program’s speed further expands its reach into areas such as national and human security. Fan provided examples of emergency support after a hurricane or response to a public health crisis as needs for rapid land-use mapping. MapSpace data could provide insight into safe places to send emergency vehicles or the most accessible locations to set up aid stations.