Integrated remote sensing for multi-temporal analysis of anthropic activities in the south-east of Mt. Vesuvius National Park

Manzo, Ciro; Mei, Alessandro; Fontinovo, Giuliano; Allegrini, Alessia; Bassani, Cristiana

doi:10.1016/j.jafrearsci.2015.12.021

Cited by 15 publications

(7 citation statements)

References 42 publications

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“…Level-1C (L1C) is provided in Top Of Atmosphere (TOA) reflectances, and Level-2A (L2A) is provided in Bottom Of Atmosphere (BOA) reflectance images, obtained from the parameters of the L1C. (9), and SWIR (10) The Sentinel-2 images allow obtaining rich information about vegetation, water, and so on. The most common land monitoring applications are based on temporal series of indices, for instance the Normalized Difference Vegetation Index (NDVI) [7], the Normalized Difference Water Index (NDWI) [10], and much more.…”

Section: Sentinel-2mentioning

confidence: 99%

“…Multispectral/Optical images, such as Sentinel-2 or Landsat TM, are mainly employed in applicative scenarios thanks to their capacity to represent natural color images of wide portions of the Earth surface, providing information about vegetation, risk management (floods, forest fires, and so on), water monitoring, and much more [3][4][5][6]. In addition, a plethora of indices, such as the Normalized Difference Vegetation Index (NDVI) [7][8][9], the Normalized Difference Water Index (NDWI) [10][11][12], and others have been developed to provide quantitative estimates of selected surface covers [6]. However, multispectral sensors are unusable in presence of cloud cover and this prevents the possibility to guarantee a continuous monitoring.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Sentinel-1 and Sentinel-2 Data for Land Cover Mapping Using W-Net

Gargiulo

Dell'Aglio

Iodice

et al. 2020

Sensors

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In this paper, we present a new approach to the fusion of Sentinel 1 (S1) and Sentinel 2 (S2) data for land cover mapping. The proposed solution aims at improving methods based on Sentinel 2 data, that are unusable in case of cloud cover. This goal is achieved by using S1 data to generate S2-like segmentation maps to be used to integrate S2 acquisitions forbidden by cloud cover. In particular, we propose for the first time in remote sensing a multi-temporal W-Net approach for the segmentation of Interferometric Wide swath mode (IW) Sentinel-1 data collected along ascending/descending orbit to discriminate rice, water, and bare soil. The quantitative assessment of segmentation accuracy shows an improvement of 0.18 and 0.25 in terms of accuracy and F1-score by applying the proposed multi-temporal procedure with respect to the previous single-date approach. Advantages and disadvantages of the proposed W-Net based solution have been tested in the National Park of Albufera, Valencia, and we show a performance gain in terms of the classical metrics used in segmentation tasks and the computational time.

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Section: Sentinel-2mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration of Sentinel-1 and Sentinel-2 Data for Land Cover Mapping Using W-Net

Gargiulo

Dell'Aglio

Iodice

et al. 2020

Sensors

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“…Além disso, estes pesquisadores observaram que os novos resíduos mantêm temperatura superior aos resíduos mais antigos (Hanson, Yesiller & Swarbrick, 2005 Ainda considerando essa temática, Monsef (2015), manuseando dados socioeconômicos e ambientais, apontou regiões potenciais para aterros nos municípios costeiros do Egito. Manzo et al (2016), através de diversos índices, entre eles de temperatura e vegetação, investigaram a influência antrópica de uso do solo após despejos de extração mineral no Parque Nacional Monte Vesuvius, na Itália. Kwarteng & Al-Enezi (2004), através de um levantamento temporal de imagens de médio e baixa resolução e seus índices, avaliaram um aterro não controlado no Kuwait, o qual causava problemas, desde um forte mau cheiro, até problemas de saúde pública devido à proximidade com habitações.…”

Section: Resultsunclassified

Avaliação do sensoriamento remoto termal para monitoramento de aterros sanitários

Silva

Paz

et al. 2018

J. Env. Anal. Progr.

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A presença cotidiana do lixo na sociedade faz necessário a reflexão dos ambientes de deposição do mesmo; que pode ser não controlado, configurados como lixões e causando diversas adversidades para a população em entorno; ou controlado, este passivo do monitoramento de suas propriedades com propósito de reduzir os efeitos que podem causar ao ambiente. Nessa perspectiva, o sensoriamento remoto contribui positivamente no que tange ao monitoramento dessas áreas; as análises podem manter-se apenas na evolução de tamanho da área ou de outros parâmetros sensíveis. Compreendendo a importância da temperatura e suas interações com os resíduos sólidos, este trabalho tem como objetivo analisar o sensoriamento remoto termal para monitoramento de aterros. Utilizou-se imagens Landsat 5 e 8 para a região de Muribeca-PE (2006, 2016) e o Lixão da Estrutural-DF (2005, 2016) aplicando fórmulas de radiância, reflectância, SAVI, IAF, emissividade e de temperatura da superfície. Os resultados mostraram variação na temperatura do Aterro da Muribeca (2006) de 6,1 graus do ponto mais quente até o ponto de borda; a nova área do aterro da Muribeca em 2016, variou entre de 7,8; por sua vez, a área antiga manteve-se com 3.1 graus. O Lixão da Estrutural mostrou variação de 5,2 e 8 graus nos anos de 2005 e 2016, respectivamente. O sensoriamento remoto termal mostra-se de grande relevância no suporte das análises em aterros controlados e não controlados, todavia, diversos percalços como a periodicidade das imagens e condições climáticas ressaltam a junção dos dados remotos com os de campo para pesquisas.

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“…To integrate waste management strategies into urban planning for healthy and sustainable societies, researchers [ [ [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] ]] have demonstrated the use of remote sensing (RS) and geographic information systems (GIS) methods for planning, landﬁll management; and landfill site selection to replace expensive and time-consuming ground surveys for solid waste landfill selection and management. Other studies [ [ [35] , [36] , [37] ]] have combined the analytical hierarchy process (AHP) with RS and GIS for assessment of complex decision problems in the selection of landfills.…”

Section: Introductionmentioning

confidence: 99%

Sustainable landfill sites selection using geospatial information and AHP-GDM approach: A case study of Abha-Khamis in Saudi Arabia

Arshad,

Hasan,

Al Mesfer

et al. 2023

Heliyon

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Integrated remote sensing for multi-temporal analysis of anthropic activities in the south-east of Mt. Vesuvius National Park

Cited by 15 publications

References 42 publications

Integration of Sentinel-1 and Sentinel-2 Data for Land Cover Mapping Using W-Net

Integration of Sentinel-1 and Sentinel-2 Data for Land Cover Mapping Using W-Net

Avaliação do sensoriamento remoto termal para monitoramento de aterros sanitários

Sustainable landfill sites selection using geospatial information and AHP-GDM approach: A case study of Abha-Khamis in Saudi Arabia

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