Procedure to detect impervious surfaces using satellite images and light detection and ranging (LIDAR) data

Rodríguez-Cuenca, Borja; Alonso-Rodríguez, M. C.; Domenech-Tofiño, E.; Sanz, Núria; Delgado-Hernández, J.; Peces-Morera, Juan José; Arozarena-Villar, Antonio

doi:10.1117/12.2067259

Cited by 3 publications

(1 citation statement)

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“…More recent research by Germaine and Hung [2011] delineates impervious surfaces from multispectral imagery and LiDAR data through a knowledge based expert system. In the same direction, Rodriguez-Cuenca et al [2014] conduct an impervious /non-impervious surface classification using a decision tree system.…”

Section: Introductionmentioning

confidence: 99%

Integrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping

Sturari

Frontoni

Pierdicca

et al. 2017

European Journal of Remote Sensing

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The combination of elevation data together with multispectral high-resolution images is a new methodology for obtaining land use/land cover classification. It represents a step forward for both the accuracy and automation of LULC applications and allows users to setup thematic assignments through rules based on feature attributes and human expert interpretation of land usage. The synergy between different types of information means that LiDAR can give new hints at both the segmentation and hybrid classification steps, leading to a joint use of multispectral, spatial and elevation data. The output is a thematic map characterized by a custom-designed legend that is able to discriminate between land cover classes with similar spectral characteristics (level 3 of the CLC legend). Experimental results from a hilly farmland area with some urban structures (Musone river basin, Ancona, Italy) are used to highlight how the proposed methodology enhances land cover classification in heterogeneous environments.

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Section: Introductionmentioning

confidence: 99%