RESUMO Uma realidade ainda muito comum nos países em desenvolvimento é a utilização de lixões como forma de destinação final de resíduos sólidos urbanos, implicando em consequências como contaminação ...dos recursos naturais e problemas de saúde pública. Assim, torna-se urgente a efetivação das políticas públicas, de modo a promover a destinação adequada dos resíduos sólidos urbanos e a remediação dos lixões. Nesse sentido, este artigo teve como objetivo desenvolver uma ferramenta de apoio à decisão, com a finalidade de auxiliar os municípios brasileiros no diagnóstico de seus lixões, os quais devem funcionar de forma a estabelecer prioridades de remediação. A ferramenta foi construída em três etapas: 1) elaboração de um questionário de campo para diagnosticar lixões; 2) estabelecimento de um sistema de pontuação para o questionário de campo, visando mensurar o nível de impacto de cada lixão diagnosticado; 3) Codificação da ferramenta na forma de um programa e de testes de validação. O usuário fornece as informações do formulário de campo para o programa calcular a pontuação, estabelecer o nível de impacto e gerar o diagnóstico do lixão. A ferramenta foi aplicada em quatro lixões, que serviram como objetos do estudo de caso. Mesmo com as poucas informações disponíveis sobre os lixões diagnosticados, os resultados demonstraram que a ferramenta é capaz de atingir seus objetivos, contribuindo para a melhoria da gestão de resíduos sólidos no Brasil.
► This study proposes a new needs analysis method for the land-use planning of contaminated sites. ► Our new method can produce economically and socially feasible land-use plans. ► Our new method can ...reflect the highly diverse potential needs of the residents to the land-use plan.
Land use at contaminated sites, following remediation, is often needed for regional redevelopment. However, there exist few methods of developing economically and socially feasible land-use plans based on regional needs because of the wide variety of land-use requirements. This study proposes a new needs analysis method for the conceptual land-use planning of contaminated sites and illustrates this method with a case study of an illegal dumping site for hazardous waste. In this method, planning factors consisting of the land-use attributes and related facilities are extracted from the potential needs of the residents through a preliminary questionnaire. Using the extracted attributes of land use and the related facilities, land-use cases are designed for selection-based conjoint analysis. A second questionnaire for respondents to the first one who indicated an interest in participating in the second questionnaire is conducted for the conjoint analysis to determine the utility function and marginal cost of each attribute in order to prioritize the planning factors to develop a quantitative and economically and socially feasible land-use plan. Based on the results, site-specific land-use alternatives are developed and evaluated by the utility function obtained from the conjoint analysis. In this case study of an illegal dumping site for hazardous waste, the uses preferred as part of a conceptual land-use plan following remediation of the site were (1) agricultural land and a biogas plant designed to recover energy from biomass or (2) a park with a welfare facility and an athletic field. Our needs analysis method with conjoint analysis is applicable to the development of conceptual land-use planning for similar sites following remediation, particularly when added value is considered.
Managing unregulated dumpsites in urban environments is a pressing issue, but determining their locations presents persistent challenges due to their irregular distribution. Recently, researchers ...have begun employing aerial view remote sensing imagery coupled with deep learning detection to identify open dumpsites. However, due to interference from scenes with similar visual features in the satellite imagery, the false alarm rate remains high. A model named CascadeDumpNet is proposed by this study, which integrates deep learning and automated machine learning for open dumpsite detection, effectively combining the visual characteristics of open dumpsites with the features of the surrounding environment to eliminate erroneous detection and improve detection precision. Notably, the model is equipped with a novel Contextual Feature Synthesis (CFS) module that was specifically designed to enhance object detection in bird-view remote sensing imagery. This module is adept at leveraging remote sensing contextual information, thereby significantly refining the detection process by considering the broader environmental features of dumpsites. The performance of the model was compared with six advanced object detection architectures to demonstrate its superiority. High-resolution multispectral satellite imagery from the Pléiades satellite, featuring a spatial resolution of 0.5 m, was utilized to analyze the dumpsite distribution in Shenzhen, China. The model was applied to this densely urbanized area, demonstrating its effectiveness in detecting open dumpsites within such environments. Additionally, the transferability of the model was verified through successful applications in two other major Chinese cities, Shanghai and Guangzhou. Furthermore, the distribution pattern of dumpsites was analyzed, which revealed that the density of dumpsites is predominantly concentrated in highly urbanized areas, which are characterized by high population densities, and a strong correlation was observed between the locations of these dumpsites and proximities to forests, elevated highways, and industrial zones. Overall, the development of the CascadeDumpNet model provides new insights into urban waste management, offering a novel, efficient, and precise approach to the detection and analysis of open dumpsites.
•High-resolution satellite imagery aids urban open dumpsite detection.•CascadeDumpNet is proposed by integrating CNN and AutoML, decreasing false alarms.•A CFS module is proposed for remote sensing object detection challenges.•Dumpsite density decreases from urban to rural areas.•Dumpsites are often located near elevated highways, industrial zones, and forests.
With the soaring generation of hazardous waste (HW) during industrialization and urbanization, HW illegal dumping continues to be an intractable global issue. Particularly in developing regions with ...lax regulations, it has become a major source of soil and groundwater contamination. One dominant challenge for HW illegal dumping supervision is the invisibility of dumping sites, which makes HW illegal dumping difficult to be found, thereby causing a long-term adverse impact on the environment. How to utilize the limited historic supervision records to screen the potential dumping sites in the whole region is a key challenge to be addressed. In this study, a novel machine learning model based on the positive-unlabeled (PU) learning algorithm was proposed to resolve this problem through the ensemble method which could iteratively mine the features of limited historic cases. Validation of the random forest-based PU model showed that the predicted top 30% of high-risk areas could cover 68.1% of newly reported cases in the studied region, indicating the reliability of the model prediction. This novel framework will also be promising in other environmental management scenarios to deal with numerous unknown samples based on limited prior experience.
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Ljubljansko polje is a gravel plain lying along the Sava River north of Ljubljana. Although built-up areas are steadily expanding, the water protection area has helped preserve the character of ...relatively intensely cultivated agricultural land at least in its central part. However, illegal dumping sites pose a threat to the groundwater in the gravel aquifer. In the narrowest and narrow water protection areas of Ljubljansko polje, we have found, registered, and studied 1,445 illegal dumping sites with a total surface area amounting to 120,816 m2 and a total volume of 209,422 m3. A good seventh (13.5%) of the total waste is hazardous. In the area surveyed, we also registered 86 gravel pits, 47 information and warning signs, and 57 road barriers on access roads. In time, it will be necessary to rehabilitate all the illegal dumping sites; however, due to the large quantity of waste it is unrealistic to expect this to happen in one go, and we have therefore established a priority schedule for the rehabilitation.
Recently, the analysis of geographical features by digital elevation models (DEM) which are made fromsatellite images, has become a widely researched topic. However, espacially in the case of old ...satelliteimage, DEM or the stereo pair to make it might be hard-to-find. Then we developed the estimation methodfor three-dimensional detailed geographical features shape using shadow of satellite images. In this study, weinvestigated the influence on the result of estimation by choosing the boundary of a shadow. Also, weexamined the threshold of the brightness to discern the shadows of geographical features from old satelliteimages.