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Buffer zone analysis. Anomalous D-REP values are in black. Blue line represent the border of 90 m buffer distance, in black 180 m distance. D-REP kriging map in transparency. In the background the orthophoto of 2006.
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This work shows a downscaling approach for environmental changes study using multi- and hyper-spectral remote sensing data. The study area, located in the south-east of Mt. Vesuvius National Park, has been affected by two main activities during the last decades: mining and consecutive municipal solid waste dumping. These activities had an environme...
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... c 0 is the random component near the origin of the axes (nugget variance), c 1 is the partial sill and a is the practical range distance at which the semivariogram achieves 95% of the a priori variance ( s 2 1⁄4 1.89) (Chil es and Del fi ner, 1999), representing the highest distance of pixel correlation. Model fi tting provided the values of parameters of the equation [6] ( c 0 1⁄4 0.23; c 1 1⁄4 1.63; a 1⁄4 90 m). The kriging interpolation of Delta REP around the anthropic area was based on this semivariogram model providing a RMSE of 0.56. The semivariogram analysis identi fi ed the buffers in 90 m from anthropic activity border. In this area the Delta REP has low variability considering the strong variation of land cover in comparison with other variation of vegetation in the two images (see NDVI and SAM in Figs. 8 and 9). Moving out from the buffer there is a strong variation of this index in particular in the south of WZ3 where there is a reduction going from 90 m distance from the anthropic area in the unchanged vegetated pixels (Fig. 18). Another anomaly is visible in the north- ern part of study area. The statistical analysis of the distribution of values in the buffer at 90 m is signi fi cantly different (p- value < 0.05) from the values in the buffer at 180 m and in the whole study area. In particular in the southern part of WZ3, where vegetation unchanged from 2004 to 2010, the Delta REP values are in the tail of the distribution highlighting an increase in stress ...
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... Regarding the location or the geography of waste, the scientific contributions can be broadly classified into two groups: studies oriented to the probabilistic prediction of waste in a given location [7,[12][13][14][15] and studies focused on trying to identify existing waste sites [16][17][18][19][20]. The cited studies use spatial data and remote-sensing approaches with GIS. ...
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.
... 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. ...
... Many researchers [ [8][9][10][11][12][13][14][15][16][17][18]] advocated prohibiting the disposal of solid waste in open areas owing to the inherent threat of air and groundwater pollution, serious health, aesthetic and environmental problems, property depreciation, fire, and explosion owing to spontaneous combustion and slope instabilities in some hilly areas. Researchers [ [27][28][29][30][31][32][33][34]] have highly recommended the application of geospatial techniques for integrating waste management strategies (WMS) into urban planning to replace expensive and time-consuming ground measurements for solid waste landfill selection and management [4,19,39]. successfully used applied the advanced tools of GIS, MCDA and AHP to locate sustainable landfills and optimize the waste transportation network rather than solely relying on economic criteria when selecting a solid waste landfill. ...
Social, environmental, and technical factors must be combined to solve the complex problem of ever-growing municipal solid waste (MSW) and minimize its negative impact on the environment. Saudi Arabia has launched a US$13 billion tourism strategy to transform the Asir region into a year-round tourist destination and has pledged to welcome 10 million local and foreign visitors by 2030. The estimated share of Abha-Khamis will increase to 7.18 million tons of household waste per year. With a gross domestic product (GDP) of USD 820.00 billion by the end of 2022, Saudi Arabia can no longer afford to neglect the issue of waste production and its safe disposal. In this study, to account for all factors and evaluation criteria, a combination of remote sensing, geographic information systems and an analytical hierarchy process (AHP) was used to determine the best locations for municipal solid waste (MSW) disposal in Abha-Khamis. The analysis revealed that 60% of the study area consists of faults (14.28%), drainage networks (12.80%), urban (11.43%), land use (11.41%) and roads (8.35%), while 40% of the suitable area for landfill. Of these, a total of 20 sites ranging in size from 100 to 595 ha are distributed at reasonable distances from the cities of Abha-Khamis, which meet all the critical criteria for suitable landfill sites mentioned in the literature. Current research shows that the use of integrated remote sensing, GIS and the AHP-GDM approach significantly improves the identification of land suitability for MSW management.
... By observing the distribution pattern of the scores of PC2, which Hg strongly influences, it is possible to hypothesise that the fire at Mt. Somma-Vesuvius probably involved waste. This hypothesis is supported by the information provided by Manzo et al. [50], which reports a considerable number of quarries (converted into landfill sites) and landfill sites, especially in correspondence with the eastern slopes of the volcanic complex. ...
The worldwide increase in fire events has attracted global attention, as potentially toxic elements (PTEs) have been widely recognised within the produced ash. Ash is transported, dispersed by wind, and deposited into the soil and surficial waters even far from fires. Considering that their composition can be enriched in PTEs, they represent a potential hazard for humans and other animals exposed to airborne particles and, afterwards, to resuspended matter, even at a considerable distance from the source. This study aimed to assess the environmental impact of fire events that occurred during the 2017 summer season at two different sites in the Campania region (Southern Italy). One of the fires affected a waste disposal site west of Caserta, and one involved a forest on the slopes of Mt. Somma-Vesuvius, a few kilometres southeast of Naples, the regional capital. Changes to the PTE concentration in the topsoil in the surroundings of both sites, after the fire events, were investigated. Enrichment factors (EFs) of a selection of PTEs were determined by comparing geochemical data from two sampling campaigns, one completed before and one after the fire events. A combined application of multivariate statistics (based on robust principal component analysis; RPCA) and geospatial analysis was used to determine the materials affected by the fire on the slopes of Mt. Somma-Vesuvius, and roughly locate their place. Specifically, a statistically significant enrichment of Hg was identified in the topsoil of both study areas. In addition, in soil samples collected at Mt. Somma-Vesuvius, more PTEs showed significant changes in their concentration. For both areas, Hg enrichments were related to the deposition of ash proceeding from waste burning; furthermore, as regards the soil of the Vesuvian area, Cr and Cd enrichments were associated with the fallout of ash generated during biomass combustion, and the increase in Cu and Zn concentrations was linked to the burning of crops on cultivated lands. Apart from the specific results obtained, concerning the examined case studies, the methods applied can be seen as a reliable option to determine the compositional characteristics of materials burned during a fire event, even with the prospect of improving the eventual assessment process of the related environmental hazards.
... The multitemporal analysis of images from 2000 to 2020 allowed the identification of solid waste hotspots and their variation over time, using the time domain of the Landast satellite data already used in other investigations [29], that despite being a year old, Landsat time series change detection applications cover a wide range of subjects with applications limited to small areas. In the detection of solid waste, information from the thermal infrared band was used, because each body reflects different temperatures, which allows detecting areas according to the researcher's interest, this band provides information of the general area with capabilities in the particular analysis of monitoring and detecting warning areas [30], allowing the integration of multisensory data with processing techniques and information in the interpretation of environmental phenomena. ...
Given the problem of the presence of waste in public spaces generated without control by the population, the objective of the research was to identify the critical points where solid waste generated in the district of Comas is deposited from January to April 2020. The methodology used was remote sensing and the use of images from Google maps and Google Earth. The population of the District of Comas is located in Metropolitan Lima, it has a south latitude of 11° 56' 00" and a west longitude of 77° 04' 00". As a result, 40 critical points of solid waste were identified in various zones of Comas, of which the largest number are located in zones 14 and 8, with 9 and 8 critical points, respectively. Where common waste from housing, weeds, construction, and demolition is predominant. The accumulation of solid waste detected by remote sensing was located in avenues, streets, sidewalks, and open green areas, which were validated and verified by Google Earth and on-site visits to the sites. In this way, the research provides a support method to manage the generation of solid waste left on public roads quickly through remote sensing and is viable for this purpose with the advantage of its low cost for the benefit environmental sustainability.
... Rating, weighting, and ranking have been the most common basis of landfill site selection so far with which many novelties have been offered in terms of model integration, data inclusion/ configuration, and geographical toolboxes with setback spatial criteria go forth. Developing a GIS tool underpinned by the ensemble of Not-In-My-Backyard (NIMBY) syndrome and nuisance score (Simsek et al. 2014a, b) and incorporating different multi-criteria decision-making methods such as simple additive weighting (SAW), analytical hierarchy process (AHP), and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) (Rahmat et al. 2017(Rahmat et al. , 2018Chabuk et al. 2017;Spigolon et al. 2018;Khan et al. 2018;Șener et al. 2010;Kamdar et al. 2019;Chabuk et al. 2019;Özkan et al. 2019), remote sensing studies with employing aerial photography, airborne and spaceborne sensors (Manzo et al. 2016;Mahmood et al. 2017), novel Thiessen polygon-based ranking schemes integrated with remotely examined environmental criteria (Richter et al. 2019), and electrical resistivity combined with a MCDM method (Goulart Coelho et al. 2017;Yousefi et al. 2018;Akintorinwa and Okoro 2019) are some of these endeavors. ...
This study sets out to propose a new ensemble of probabilistic spatial modeling and multi-criteria decision-making comprised of stepwise areal constraining and Mahalanobis distance algorithms in order to assess areal suitability for landfilling. The Ardak watershed was selected as the study area due to encountering several cases of open garbage dumps and uncontrolled landfills which are one of the main sources of river water pollution in the upstream of the Ardak dam. The results revealed that the proposed algorithm successfully assists in inventory-irrespective probabilistic modeling of landfill siting which is mainly indebted to the role of areal constraining in providing training and validation samples for the Mahalanobis distance model. The latter also showed a robust pattern recognition results from which a discernible differentiation of the area was attained while the spatial dependencies between the environmental factors were taken into account. Mahalanobis distance also gave an outstanding performance in terms of goodness of fit (area under the success rate 89.367) and prediction power (area under the success rate 89.252). Based on a five-point scale classification scheme, about 2.7% and 2.6% of the study area, respectively, have high and very high suitability for landfilling, while the remaining area is shared between very low-to-moderate suitability classes. According to the current trail of literature regarding landfill site selection which mostly relies on mere areal filtering, a probabilistic model would give invaluable inferences regarding the pattern of suitability/susceptibility of the area of interest and causative role of the influential factors.
Graphical Abstract
... 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. ...
... Coastal Aerosol (1), 0.443-1.375 Water Vapour (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. ...
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.
... In order to analyse the flow direction of the waste-slide towards watershed areas, the analysis of dynamic changes of Jiaojiapo Waste Landfill (in China) has been done basing on satellite stereophotos in a different period of time (Qingsheng and Gaohuan, 2010). Having applied multi-and hyper-spectral satellite images of Manzo et al. (2016), the possibility to analyse the environment condition before the creation of landfills in Southeast of Mt. Vesuvius National Park (Italy) in 2004 and after its creation in 2010 appeared. ...
Geodetic monitoring of the dangerous waste-slide area of Lviv Municipal Solid Waste (MSW) Landfill presents the results of conducting trial measurements by remote and contact methods. It was established that the use of a robotic total station in the reflex-free mode is an effective tool to observe processes in a dangerous waste-slide area. The technology of geodetic monitoring of waste-slide areas of waste disposal facilities was developed. During June 2016 - December 2017, 14 monitoring cycles were performed, the absence of critical movements was recorded, and the results were used to eliminate and prevent further emergency situations. Using of this technology is a justified means to collect geospatial information over long distances in difficult meteorological conditions and, most importantly, it is safe from the point of view of occupational safety in case of re-landslide. Recommendations were developed for monitoring the spatial displacement of landfill area and environmental monitoring. The obtained results made it possible to develop a series of measurements to strengthen the slope and became one of the reasons for the closure of Lviv Municipal Solid Waste Landfill. Based on the results generated by the city authorities, the first steps were taken to develop a project for reclamation and construction of a waste recycling plant, as well as to develop a strategy for the collection treatment and disposal of solid waste for Lviv.
... According to Faisal (2011), remote sensing (RS) techniques are useful to various aspects of landfill management, including: siting of landfills, detection of illegal disposal sites, and contamination of areas surrounding the facilities. Aerial photography, spaceborne, and airborne sensors allow for continued improvement in planning and management of solid waste sites (Manzo et al., 2016); and may replace costly and time consuming ground measurements (Mahmood et al., 2017). Table 1 presents recent waste studies using various geospatial techniques in the field of waste management. ...
Landfilling is the most common method for final treatment of municipal solid waste worldwide. Canadians generated 973 kg/cap of waste in 2016, and 73% of that was sent to landfills or incinerators. This study proposes a novel method which combines remote sensing and vector data to rank the suitability of current landfill sites and their area of influence for expansion in Saskatchewan, Canada; where there are currently more than 500 active landfills. This study found that using average normalized data, 55.3% of the land in the study area was suitable or moderately suitable for landfill expansion while 45% of the area was unsuitable for landfill expansion. Polygon 32, an area dominated by agriculture and pasture land, is the most suitable for landfill expansion based on the mean normalized rank and was ranked 9th (out of 39) in terms of standard deviation. Polygon 27 is the least suitable for landfill expansion, having the largest mean normalized rank, and was ranked 38th (out of 39) in terms of standard deviation. This method is advantageous compared to other decision-making tools which rely on expert opinion. This method relies solely on remote sensing and vector data; but is flexible enough that weighting of data sets can be applied by policy makers if so desired. Results show that using remote sensing data and vector data together are capable of capturing distinctly different aspects of the study area, and that vector data can be used as a proxy for imagery where cloud cover is present.
... 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. ...
The daily presence of the garbage in the society makes necessary the reflection of the environments of the same deposition: Which can be uncontrolled, configured as
dumps and causing various adversities for the surrounding population; or controlled,
this passive of monitoring their properties in order to reduce the effects they can
cause to the environment. Considering this perspective, remote sensing contributes
positively to the monitoring of these areas; analyzes can only be maintained in the
evolution of area size or other sensitive parameters. Understanding the importance
of temperature and its interactions with solid waste, this work aims to analyze thermal
remote sensing for landfill monitoring. It was used Landsat 5 and 8 images for the
region of Muribeca-PE (2006, 2016) and the Lixão da Estrutural-DF (2005, 2016)
applying radiative, reflectance, SAVI, IAF, emissivity and surface temperature. The
results showed a variation in the temperature of the Muribeca Landfill (2006) of 6.1
degrees from the hottest point to the edge point; The new area of the Muribeca landfill
in 2016 ranged from 7.8; In turn, the old area remained at 3.1 degrees. The Structural
Landfill had a variation of 5.2 and 8 degrees in the years 2005 and 2016, respectively.
Thermal remote sensing is of great relevance in the support of controlled and
uncontrolled landfill analyzes, however, several mishaps such as the periodicity of
the images and climatic conditions highlight the junction of the remote data with
those of the field for research.
... The analysis of airborne thematic imagery allows to establish a relationship with soil condition and gas migration (Jones and Elgy 1994) or between vegetation covers and methane leakage (Noomen et al., 2008). In addition, image differencing and spatial autocorrelation techniques can be used to detect contaminated ar-eas by analyzing multi-and hyper-spectral sensors (Brivio et al., 1993;Slonecker et al. 2010;Manzo et al., 2015Manzo et al., , 2017. ...
Landfills play an important role in urban society. Consequently, an accurate management and planning of such anthropic activities are essential to improve decision making eco-strategies. The application of remote sensing techniques may improve the monitoring of different environmental matrices and the assessment of both gas emission in the atmosphere and leachate migration. This work describes a multi-source approach based on remote sensing and field data. To achieve this goal a downscaling and multi-temporal approach was adopted by using aerial photos, multispectral and hyperspectral imagery and overnight thermal and photogrammetric surveys. The integration of such different geomatic processing techniques allows to detect Environmental Point of Interest (EPI) inside and around the landfill.
