Detection of Construction and Demolition Illegal Waste Using Photointerpretation of DEM Models of LiDAR Data

Manuel Sánchez-Fernández (), Lorea Arenas-García and José Antonio Gutiérrez Gallego
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Manuel Sánchez-Fernández: INTERRA (University Institute of Research for Sustainable Territorial Development), Avda. de la Universidad s/n, 10003 Cáceres, Spain
Lorea Arenas-García: Departamento de Derecho Público, Facultad de Derecho, Universidad de Extremadura, Avda. de la Universidad s/n, 10004 Cáceres, Spain
José Antonio Gutiérrez Gallego: INTERRA (University Institute of Research for Sustainable Territorial Development), Avda. de la Universidad s/n, 10003 Cáceres, Spain

Land, 2023, vol. 12, issue 12, 1-16

Abstract: Illegal waste is a global problem with negative impacts on human health and the environment. This article focuses on detection using remote sensing of sites of demolition and construction waste. We hypothesise that construction and demolition waste represent a human modification of terrain and, as a result, will be sensible to detection using visualisation models of terrain, specifically DEM (digital elevation model). To this effect, we start with a DEM of 0.25 m per pixel developed using data from the second iteration of the PNOA LiDAR project by the Spanish National Geographic Institute (IGN). We evaluate seven modelling tools of the Relief Visualisation Toolbox (RVT) for the visual detection of waste. The study area includes the city of Mérida (Extremadura, Spain). Our fieldwork identified 494 points of illegal waste in this area. These points were classified according to five categories in relation to land use, and we established a total of 14 areas with a surface area of 450 m by 450 m. Our results suggest that three of the seven models employed allow us to differentiate with clarity what is anthropic from the natural terrain and, in some scenarios, the location of construction and demolition waste. The LD model was the one with the best results, allowing an increase in the number of locations of illegal dumping of CDW in the study area.

Keywords: construction and demolition waste (CDW); LiDAR; remote sensing; DEM; RVT; photointerpretation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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