Global Partitioning Elevation Normalization Applied to Building Footprint Prediction

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 13; pp. 3493 - 3502
• Main Authors: Fafard, Alexander, van Aardt, Jan, Coletti, Mark, Page, David L.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Anthropogenic factors; Artificial neural networks; Classification; Coders; Connectors; Couplings; Data; Data processing; Dynamic range; Earth; Elevation; Encoders-Decoders; ENGINEERING; Footprints; Geology; Histograms; Human influences; Learning algorithms; Machine learning; Machine vision; Neural networks; Optical data processing; Partitioning; Preprocessing; Remote sensing; Task analysis; Three-dimensional displays

Understanding and exploiting topographical data via standard machine learning techniques is challenging, mainly due to the large dynamic range of values present in elevation data and the lack of direct relationships between anthropogenic phenomena and topography, when considering topographic-geology...