Utility of image point cloud data towards generating enhanced multitemporal multisensor land cover maps
Multitemporal land cover classification over urban areas is challenging, especially when using heterogeneous data sources with variable quality attributes.A prominent challenge is that classes with similar spectral signatures (such as trees and grass) tend to be confused with one another.In this paper, we evaluate the efficacy of image point cloud