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A method for the remote sensing identification of uncontrolled landfills: formulation and validation

机译:遥感识别不受控制的垃圾填埋场的方法:制定和验证

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摘要

The identification of uncontrolled landfills is a central environmental problem in all developed and developing countries, where several illegal waste deposits exist as a result of rapid industrial growth over the past century. Remote sensing can potentially provide crucial information for the identification of contaminated sites, but surprisingly there is a marked lack of rigorously validated approaches. In this paper we introduce and validate a method that uses remotely sensed information and a geographic information system (GIS) to identify unknown landfills over large areas. The method is applied to a study area located in NE Italy (part of the Venice lagoon watershed) using IKONOS satellite data. Soil contamination effects on the radiometric properties of vegetation, calibrated using spectral signatures of stressed vegetation from known illegal landfill sites, were used to define numerous candidate sites that are most likely to host waste materials. Distributed geographical information, such as the position of the road network, the population density, and historical aerial photographs, have then been used to select the most likely contaminated sites among the candidates identified through remote sensing. The importance of the integration of GIS and remote sensing is highlighted and represents a key instrument for environmental management and for the spatially distributed characterization of possible uncontrolled landfill sites.
机译:在所有发达国家和发展中国家,识别不受控制的垃圾填埋场都是一个中心环境问题,在过去的一个世纪中,由于上世纪工业的快速发展,这里存在着一些非法废物堆积。遥感有可能为识别受污染的地点提供关键信息,但令人惊讶的是,明显缺乏严格验证的方法。在本文中,我们介绍并验证了一种使用遥感信息和地理信息系统(GIS)来识别大面积未知垃圾填埋场的方法。使用IKONOS卫星数据,将该方法应用于位于意大利东北部(威尼斯泻湖流域的一部分)的研究区域。土壤污染对植被辐射特性的影响已通过使用来自已知非法垃圾填埋场的受应力植被的光谱特征进行了校准,用于定义许多最有可能容纳废物的候选站点。然后,已使用分布的地理信息,例如路网的位置,人口密度和历史航空照片,在通过遥感识别的候选对象中选择最可能受污染的地点。强调了集成GIS和遥感的重要性,它代表了环境管理和可能的不受控制的垃圾填埋场的空间分布特征的关键工具。

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