No abstract

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 have been collected that provides an indication of a sensors’ health. These telemetry data were 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.

Using side-facing observations of the New York City (NYC) skyline, we identify lighting technologies via spectral signatures measured with Visible and Near Infrared (VNIR) hyperspectral imaging. The instrument is a scanning, single slit spectrograph with 872 spectral channels from 0.4–1.0 μm. With a single scan, we are able to clearly match the detected spectral signatures of 13 templates of known lighting types. However, many of the observed lighting spectra do not match those that have been measured in the laboratory. We identify unknown spectra by segmenting our observations and using Template-Activated Partition (TAP) clustering with a variety of underlying unsupervised clustering methods to generate the first empirically-determined spectral catalog of roughly 40 urban lighting types. We show that, given our vantage point, we are able to determine lighting technology use for both interior and exterior lighting. Finally, we find that the total brightness of our scene shows strong peaks at the 570 nm Na-II, 595 nm Na-II and 818 nm Na-I lines that are common in high pressure sodium lamps, which dominate our observations.

Forests in the mountains are a treasure trove; harbour a large biodiversity; and provide fodder, firewood, timber and non-timber forest products; all of these are essential for human survival in the highest mountains on earth. The present paper attempts a spatiotemporal assessment of forest fragmentation and changes in land use land cover (LULC) pattern using multitemporal satellite data over a time span of around a decade (2000-2009), within the third highest protected area (PA) in the world. The fragmentation analysis using Landscape Fragmentation Tool (LFT) depicts a decrease in large core, edge and patches areas by 5.93, 3.64 and 0.66 %, respectively, while an increase in non-forest and perforated areas by 6.59 and 4.01 %, respectively. The land cover dynamics shows a decrease in open forest, alpine scrub, alpine meadows, snow and hill shadow areas by 2.81, 0.39, 8.18, 3.46 and 0.60 %, respectively, and there is an increase in dense forest and glacier area by 4.79 and 10.65 %, respectively. The change analysis shows a major transformation in areas from open forest to dense forest and from alpine meadows to alpine scrub. In order to quantify changes induced by forest fragmentation and to characterize composition and configuration of LULC mosaics, fragmentation indices were computed using Fragstats at class level, showing the signs of accelerated fragmentation. The outcome of the analysis revealed the effectiveness of geospatial tools coupled with landscape ecology in characterization and quantification of forest fragmentation and land cover changes. The present study provides a baseline database for sustainable conservation planning that will benefit the subsistence livelihoods in the region. Recommendations made based on the present analysis will help to recover forest and halt the pessimistic effects of fragmentation and land cover changes on biodiversity and ecosystem services in the region.