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Multilevel Semantic Labeling of Mobile Homes from Overhead Imagery...

by Wadzanai D Lunga, Matthew B Seals, Budhendra L Bhaduri
Publication Type
Conference Paper
Journal Name
IEEE Transactions on Geoscience and Remote Sensing
Publication Date
Conference Name
38th annual symposium of the IEEE Geoscience and Remote Sensing Society
Conference Location
Valencia, Spain
Conference Sponsor
Conference Date

Finding where people live and the vulnerabilities of man-made facilities during natural disasters, is not only critical for rescue efforts, but also essential for damage assessment in the aftermath. Leveraging on the availability of high resolution satellite imagery, advances in machine learning and high performance computing hardware, it is now possible to generate geographical maps for man-made facilities at scale. Mapping from satellite imagery can be a daunting task due to the enormous amount of data to be processed over large areas. In this short paper we take advantage of annotated satellite imagery and automate the semantic labeling of mobile home parks using an efficient framework rooted in patch-based and pixel-level classification. This multilevel labeling effort is a precursor to our future goal for deploying very large scale deep convolutional neural networks toward both broad and finer characterization of man-made structures from one-meter resolution NAIP images.