Smartphone-Based Participatory Soundscape Mapping for a More Sustainable Acoustic Environment

The urban environmental planning, a fundamental dynamic process for cities’ sustainability, could benefit from the soundscape approach, dealing with the perception of the acoustic environment in which sound is considered as a resource rather than a waste (noise). Noise and soundscape maps are useful tools for planning mitigation actions and for communication with citizens. Both mappings can benefit from crowdsourcing and participatory sound monitoring that has been made possible due to the large use of internet connections and mobile devices with dedicated apps. This paper is a “scoping review” to provide an overview of the potential, benefits, and drawbacks of participatory noise monitoring in noise and soundscape mapping applications, while also referring to metrological aspects. Gathering perceptual data on soundscapes by using digital questionnaires will likely be more commonly used than printed questionnaires; thus, the main differences between the experimental protocols concern the measurement of acoustic data. The authors propose to classify experimental protocols for in-field soundscape surveys into three types (GUIDE, MONITOR, and SMART) to be selected according to the survey’s objectives and the territorial extension. The main future developments are expected to be related to progress in smartphone hardware and software, to the growth of social networks data analysis, as well as to the implementation of machine learning techniques.

BUILDING EXTRACTION OF POLARIMETRIC SAR IMAGE BASED ON ASSOCIATED FEATURE AND SVM

The identification and extraction of building is a vital task in urban environmental planning and research. High-resolution SAR technology has the advantages of all-day, all-weather and strong penetration, and has become one of the important technical means to study urban areas. A novel method for building extraction using both associated features and SVM that based on the full polarization SAR image of GF-3 is proposed in this paper. Firstly, filtering the GF-3 image to reduce the speckles of the image, then texture features based on Span map are extracted by using GLCM. Principal component analysis is used to remove the correlation between them and select the best texture features. The normalized circular-pol correlation coefficient is introduced as the polarization feature and combines with the best texture features. Finally, the image is classified and extracted by SVM. In this paper, the extraction results are compared with the results of the texture feature building extraction method. The experimental results show that the proposed method can obtain higher extraction precision, and the extraction effect is obviously optimized.

Guarani Aquifer System Transboundary Management

This chapter presents the Guarani Aquifer System (GAS), its location and its characteristics, and discusses its management, since it is located in four countries, Argentina, Brazil, Paraguay, and Uruguay. The GAS is a transboundary aquifer, which goes beyond political boundaries, watersheds, and hydrogeological provinces. After briefly highlighting the technical aspects of the GAS, an overview of the groundwater management legislation of each country will be offered, with emphasis on Brazil. International Environmental Law and international treaties and agreements involving this territory will also be discussed, to present the characteristics of the Guarani Aquifer Agreement formulated by these four MERCOSUR countries, which, although not in force, provides for the protection of this environmental good. Finally, it is proposed to create an urban environmental planning tool to protect the GAS recharge areas, innovating the legal system to unite environmental law with urban law in search for GAS protection. This special environmental zoning tool will be called ZEA.