Application of Transfer Entropy Measure to Characterize Environmental Sounds in Urban and Wild Parks.

Anthropized green zones in urban areas and their surroundings develop complex soundscapes, characterized by the presence of multiple sound sources. This makes the interpretation of the sound environment challenging. To accurately distinguish between different sound components, a combination of selective analysis techniques is necessary.

Biases in Ecoacoustics Analysis: A Protocol to Equalize Audio Recorders.

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices' values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs.

Toward the Definition of a Soundscape Ranking Index (SRI) in an Urban Park Using Machine Learning Techniques.

The goal of estimating a soundscape index, aimed at evaluating the contribution of the environmental sound components, is to provide an accurate "acoustic quality" assessment of a complex habitat. Such an index can prove to be a powerful ecological tool associated with both rapid on-site and remote surveys. The soundscape ranking index (SRI), introduced by us recently, can empirically account for the contribution of different sound sources by assigning a positive weight to natural sounds (biophony) and a negative weight to anthropogenic ones.

Self-Consistent Soundscape Ranking Index: The Case of an Urban Park.

We have performed a detailed analysis of the soundscape inside an urban park (located in the city of Milan) based on simultaneous sound recordings at 16 locations within the park. The sound sensors were deployed over a regular grid covering an area of about 22 hectares, surrounded by a variety of anthropophonic sources. The recordings span 3.

Mapping of the Acoustic Environment at an Urban Park in the City Area of Milan, Italy, Using Very Low-Cost Sensors.

The-growing influence of urbanisation on green areas can greatly benefit from passive acoustic monitoring (PAM) across spatiotemporal continua to provide biodiversity estimation and useful information for conservation planning and development decisions. The capability of eco-acoustic indices to capture different sound features has been harnessed to identify areas within the Parco Nord of Milan, Italy, characterised by different degrees of anthropic disturbance and biophonic activity. For this purpose, we used a network of very low-cost sensors distributed over an area of approximately 20 hectares to highlight areas with different acoustic properties.