SIMDEO: An integrated system for landfill detection and monitoring using EO data

Cadau, Enrico; Putignano, C.; Aurigemma, Renato; Melchiorre, Andrea; Bosco, Pasquale; Tesseri, Andrea; Battazza, Fabrizio

doi:10.1109/igarss.2013.6723534

Cited by 3 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cadau et al [45] proposed an integrated system for landfill detection and monitoring using EO data, particularly by involving multispectral and SAR data. While optical data are used mainly for 2D monitoring purposes, SAR information is useful for detecting both 2D and 3D landfill variations.…”

Section: Sar-and Multi-optical-parameters-based Analysismentioning

confidence: 99%

“…where Entropy is a statistical measure of randomness that can be used to characterize the texture of an input image around a target pixel [45]. In this context, it is applied to the vegetation index images through the gray-level co-occurrence matrix.…”

Section: Ddi and Savimentioning

confidence: 99%

“…Indeed, since multispectral data provide details concerning the radiometric characterization of the observed surface, SAR acts as a complementary technology due to its geometry-based observables. Moreover, with SAR data, it is also possible to measure a variation occurring on the landfill surface when the optical signal is saturated or not exploitable because of weather conditions [45]. From an operational perspective, the radar signal is transmitted by the satellite down to the Earth's surface and scattered back towards the satellite's antenna by the Earth's surface itself.…”

Section: Backscatter Coefficientmentioning

confidence: 99%

See 2 more Smart Citations

Satellite Data Potentialities in Solid Waste Landfill Monitoring: Review and Case Studies

Papale

Guerrisi

Santis

et al. 2023

Sensors

View full text Add to dashboard Cite

Remote sensing can represent an important instrument for monitoring landfills and their evolution over time. In general, remote sensing can offer a global and rapid view of the Earth’s surface. Thanks to a wide variety of heterogeneous sensors, it can provide high-level information, making it a useful technology for many applications. The main purpose of this paper is to provide a review of relevant methods based on remote sensing for landfill identification and monitoring. The methods found in the literature make use of measurements acquired from both multi-spectral and radar sensors and exploit vegetation indexes, land surface temperature, and backscatter information, either separately or in combination. Moreover, additional information can be provided by atmospheric sounders able to detect gas emissions (e.g., methane) and hyperspectral sensors. In order to provide a comprehensive overview of the full potential of Earth observation data for landfill monitoring, this article also provides applications of the main procedures presented to selected test sites. These applications highlight the potentialities of satellite-borne sensors for improving the detection and delimitation of landfills and enhancing the evaluation of waste disposal effects on environmental health. The results revealed that a single-sensor-based analysis can provide significant information on the landfill evolution. However, a data fusion approach that incorporates data acquired from heterogeneous sensors, including visible/near infrared, thermal infrared, and synthetic aperture radar (SAR), can result in a more effective instrument to fully support the monitoring of landfills and their effect on the surrounding area. In particular, the results show that a synergistic use of multispectral indexes, land surface temperature, and the backscatter coefficient retrieved from SAR sensors can improve the sensitivity to changes in the spatial geometry of the considered site.

show abstract

Section: Sar-and Multi-optical-parameters-based Analysismentioning

confidence: 99%

Section: Ddi and Savimentioning

confidence: 99%

Section: Backscatter Coefficientmentioning

confidence: 99%

See 1 more Smart Citation