Many techniques, using statistics or artificial intelligence, exist that help classify and identify areas on satellite imagery. This includes land use characteristics such as urban spaces, agriculture lands, forests, etc. However, recreating a ground-level image and perspective using satellite imagery has only recently been developed and is now an active area of research. Such work has the potential to not only classify land more accurately but it can also provide a ground-level perspective that indicates how it differs or is like other similar classes. One pioneering technique developed in providing ground-level views from satellite images was developed by the University of California, Merced.

Leonardo da Vinci famously created drawings and paintings that showed a bird's eye view of certain areas of Italy with a level of detail that was not otherwise possible until the invention of photography and flying machines. Indeed, many critics have wondered how he could have imagined these details. But now researchers are working on the inverse problem: given a satellite image of Earth's surface, what does that area look like from the ground? How clear can such an artificial image be? Today we get an answer thanks to the work of Xueqing Deng and colleagues at the University of California, Merced.

Leonardo da Vinci famously created drawings and paintings that showed a bird's eye view of certain areas of Italy with a level of detail that was not otherwise possible until the invention of photography and flying machines. Indeed, many critics have wondered how he could have imagined these details. But now researchers are working on the inverse problem: given a satellite image of Earth's surface, what does that area look like from the ground? How clear can such an artificial image be? Today we get an answer thanks to the work of Xueqing Deng and colleagues at the University of California, Merced.