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Analysis of the soil sealing in the urban area of Rome through automatic processing of satellite data with neural networks

机译:利用神经网络自动处理卫星数据,分析罗马市区的土壤封闭性

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Satellite data represent a very powerful tool for monitoring soil sealing in metropolitan areas with a significant level of detail and with a possibility of systematic updating. However, the full exploitation of such capabilities in the application domains requires that two main conditions are satisfied: availability of the data and use of automatic and reliable procedures for data processing. Moreover, to make the methodology largely used, it is important to set up low-cost processing chains that can be afforded by different user communities. This paper presents the first results of a study aiming at the design of new and low-cost procedures for soil sealing monitoring in the city of Rome, Italy. The procedure relies on the use of the software "Neumapper," based on neural network algorithms, and "Landsat" multispectral satellite data. Both the software and the data are freely distributed, so their combined exploitation represents an interesting method for systematically obtaining thematic maps on an issue of great environmental importance. The obtained results show a classification accuracy of 78.46 %. Overall, we found that 29.36 % of the study area, of about 939 km~2, was occupied by a sealed surface. The advantages of reproducibility, and consequently of exportability, of the method open important perspectives both on the free sharing of the geographic data as a powerful factor of democracy and on the development of geospatial data market.
机译:卫星数据是监测大城市地区土壤密闭性的非常强大的工具,具有很高的详细程度,并且可以进行系统更新。但是,要在应用程序域中充分利用此类功能,需要满足两个主要条件:数据的可用性以及使用自动可靠的过程进行数据处理。此外,要使该方法得到广泛使用,重要的是要建立可以由不同用户社区提供的低成本处理链。本文介绍了旨在设计意大利罗马市土壤密封监测的新的低成本程序的研究的第一个结果。该过程依赖于基于神经网络算法的软件“ Neumapper”和“ Landsat”多光谱卫星数据的使用。软件和数据都可以自由分发,因此它们的联合开发代表了一种有趣的方法,可以有系统地获取对环境具有重大意义的主题地图。所得结果表明分类精度为78.46%。总体而言,我们发现约939 km〜2的研究区域中有29.36%被密封表面占据。该方法具有可重现性以及可导出性的优点,这为自由共享地理数据(作为民主的有力因素)和地理空间数据市场的发展打开了重要的前景。

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