Cláudio Silva

Claudio Santos, Maryam Hosseini, João Rulff et al.

The growth of cities calls for regulations on how urban space is used and zoning resolutions define how and for what purpose each piece of land is going to be used. Tracking land use and zoning evolution can reveal a wealth of information about urban development. For that matter, cities have been releasing data sets describing the historical evolution of both the shape and the attributes of land units. The complex nature of zoning code and land-use data, however, makes the analysis of such data quite challenging and often time-consuming. We address these challenges by introducing Urban Chronicles, an open-source web-based visual analytics system that enables interactive exploration of changes in land use patterns. Using New York City's Primary Land Use Tax Lot Output (PLUTO) as an example, we show the capabilities of the system by exploring the data over several years at different scales. Urban Chronicles supports on-the-fly aggregation and filtering operations by using a tree-based data structure that leverages the hierarchical nature of the data set to index the shape and attributes of geographical regions that change over time. We demonstrate the utility of our system through a set of case studies that analyze the impact of Hurricane Sandy on land use attributes, as well as the effects of proposed rezoning plans in Downtown Brooklyn.

Charlie Mydlarz, Mohit Sharma, Yitzchak Lockerman et al.

Noise pollution is one of the topmost quality of life issues for urban residents in the United States. Continued exposure to high levels of noise has proven effects on health, including acute effects such as sleep disruption, and long-term effects such as hypertension, heart disease, and hearing loss. To investigate and ultimately aid in the mitigation of urban noise, a network of 55 sensor nodes has been deployed across New York City for over two years, collecting sound pressure level (SPL) and audio data. This network has cumulatively amassed over 75 years of calibrated, high-resolution SPL measurements and 35 years of audio data. In addition, high frequency telemetry data has been collected that provides an indication of a sensors' health. This telemetry data was analyzed over an 18 month period across 31 of the sensors. It has been used to develop a prototype model for pre-failure detection which has the ability to identify sensors in a prefail state 69.1% of the time. The entire network infrastructure is outlined, including the operation of the sensors, followed by an analysis of its data yield and the development of the fault detection approach and the future system integration plans for this.