A method for the detection of buildings in densely built-up urban areas by the fusion of first
and last pulse laser scanner data and multi-spectral images is presented. The method …

Urban land cover information extraction is a hot topic within urban studies. Heterogeneous
spectra of high resolution imagery—caused by the inner complexity of urban areas—make it …

Trees play an important role in urban areas by improving air quality, mitigating urban heat
islands, reducing stormwater runoff and providing biodiversity habitat. Accurate and up-to …

Automatic extraction of building roofs from remote sensing data is important for many
applications, including 3D city modeling. This paper proposes a new method for automatic …

Promoting the use of solar energy in urban environments requires knowing the geographical
distribution and characteristics of the best places to implement solar systems. In this context …

In this paper, two main approaches for automatic building detection and localization using
high spatial resolution imagery and LiDAR data are compared and evaluated: thresholding …

A method for the automatic detection and vectorization of roads from lidar data is presented.
To extract roads from a lidar point cloud, a hierarchical classification technique is used to …

Land cover classification qfvery high resahutian (VHF) imagery in urba areas is a extremehv
challenging task, because of the low intra-class (vithin-class) and high inter-class (between …

The development of robust and accurate methods for automatic building detection and
regularisation using multisource data continues to be a challenge due to point cloud …

Automatic extraction of buildings from remote sensing data is an attractive research topic,
useful for several applications, such as cadastre and urban planning. This is mainly due to …