Environmental Monitoring Commons^™

Hazmat Storage Near Nyc Waterways Endangers Communities, Brett E. Dahlberg, Nicole Acevedo

Capstones

New York City has 520 miles of shoreline--that’s more than Miami and Los Angeles combined. These waterfronts are home to some of the city’s most polluted sites because major part of it is zoned for industrial use. Dozens of industrial plants in this area store toxic chemicals in flood zones: substances that are hazardous to our health, like Benzene, which is used in rocket fuel, toluene, a paint thinner, and lead a neurotoxin. In a flood, these chemicals can easily get caught up in moving waters and pollute entire neighborhoods.

That’s exactly what happened when Hurricane Sandy hit in 2012. …

Machine Learning Algorithms For Automated Satellite Snow And Sea Ice Detection, George Bonev

Dissertations, Theses, and Capstone Projects

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research.

In response to these challenges, …

Machine Learning Approach To Retrieving Physical Variables From Remotely Sensed Data, Fazlul Shahriar

Dissertations, Theses, and Capstone Projects

Scientists from all over the world make use of remotely sensed data from hundreds of satellites to better understand the Earth. However, physical measurements from an instrument is sometimes missing either because the instrument hasn't been launched yet or the design of the instrument omitted a particular spectral band. Measurements received from the instrument may also be corrupt due to malfunction in the detectors on the instrument. Fortunately, there are machine learning techniques to estimate the missing or corrupt data. Using these techniques we can make use of the available data to its full potential.

We present work on four …

Land Change History Of Oil Palm Plantations In Northern Bengkulu Province, Sumatra Island, Reconstructed From Landsat Satellite Archives, Atsushi Tomita

Dissertations, Theses, and Capstone Projects

The aim of this study is to reconstruct the history of land conversion to oil palm plantation in tropical Asia using multi-temporal satellite data. A new method was constructed with a newly developed computer model, Land Change Detection and Land Definition Model (LC/LD Model) to map out spatio-temporal distribution of land changes. A comprehensive, cloud-free Landsat dataset was created from all the available Landsat data from 1988 to 2015. The pixel-based dataset was converted into a polygon-based dataset by applying the multi-temporal image segmentation method. The representation of the spectral information was also reduced to a single index of IB45, …