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Classifying swimming pool using remote sensing and LIDAR in Staten Island, New York (Robert Abugel, Hunter College)

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Classifying swimming pool using remote sensing and LIDAR in Staten Island, New York (Robert Abugel, Hunter College)

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Swimming pool are hard to find and hard to classify for city assessor. With inground swimming counting at real property and above ground swimming as not it is important to be able to distinguish between them. Using NAIP and LIDAR data from the city of New York this process combine these datasets to identify them across the borough. This an effective way to find above ground swimming pools that are not track by the most cities.

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3D Elevation Profile Analysis for Erie County Park Trails (Tev'ye Davis, Buffalo State College)

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3D Elevation Profile Analysis for Erie County Park Trails (Tev'ye Davis, Buffalo State College)

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Various government agencies and authorities have implemented health safety measures, which include travel restrictions that have curtailed leisure options for Erie County residents.  One of the most accessible and low to no cost leisure options for residents of Erie County, is visiting local parks. In fact, the Center of Disease Control (CDC) states that visiting local parks is one of the best ways people can stay mentally and physically healthy during the covid-19 pandemic.

Due to the increased usage of Erie County local parks in 2020, the Parks, Recreation and Forestry Department of Erie County would like to improve the safety and user experience of certain actively used trails.

With the democratization of LIDAR datasets and digital elevation models (DEM), through the New York State GIS clearinghouse; this GIS service project was completed for Erie County. It illustrates how remote sensing techniques can improve the safety and user experience of local parks. The research also highlights software limitations and alternatives.

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Tev'yeDavis, NYS GIS Association Student Showcase

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A Study of Cyclones in Mozambique Applying Remote Sensing and GIS Mapping (Elizabeth Mahoney, Buffalo State College)

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A Study of Cyclones in Mozambique Applying Remote Sensing and GIS Mapping (Elizabeth Mahoney, Buffalo State College)

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Mozambique is a poor and rapid economic developing nation on the Eastern Coast of Africa. In the spring of 2019, two massive tropical cyclones made landfall on the coast through the Mozambique Channel. The resulting devastation had catastrophic effects including massive loss of life, infrastructure, and crops, among other humanitarian crises.

Using Landsat 8 satellite images obtained from the US Geological Survey Data Center that were taken before and after the two storms, I processed multiple imagery maps using ERDAS imagine software to classify the changes of land use before and after was the cyclones and to access the disaster and damage to the country.

Using the tools and skills in Remote Sensing and GIS, my aim is to visually represent the gravity of the crisis that affected and continues to affect Mozambique. Understanding the impacts of these storms on land use, agriculture, GDP, the loss of human life and many other factors including the HDI (United Nations Human Development Index), we can learn what outcomes can be expected as climate change causes more storms of this nature with increasing strength and frequencies. I hope through this study that we can improve UN disaster relief and humanitarian aids handling and enhance the direct foreign investments.

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Analysis of Impact of COVID-19 on Nitrogen Dioxide and Sulfur Dioxide Concentrations Across the Northeastern United States, 2019-2021 (Bettina Bonfiglio, SUNY Cortland)

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Analysis of Impact of COVID-19 on Nitrogen Dioxide and Sulfur Dioxide Concentrations Across the Northeastern United States, 2019-2021 (Bettina Bonfiglio, SUNY Cortland)

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The COVID-19 pandemic has been called a ‘natural experiment’ in which to analyze the relationship between anthropogenic activities and emissions from fossil fuels. Preliminary studies from NASA satellite monitoring show a decline in commuting for work and reduced electrical consumption are related to a decline in air pollution as evidenced by atmospheric measures of sulfur dioxide (SO2) and nitrogen dioxide (NO2). This study explores this relationship further by comparing rates of SO2 and NO2 using data from NASA’s Ozone Monitoring Instrument (OMI) and second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) Model, gathered from NASA’s GIOVANNI web GIS application. The data are collected at 0.25 by 0.25 degree (OMI) and 0.5 by 0.625 degrees (MERRA-2) spatial resolution. Preliminary results indicate substantial differences in measures of both tropospheric column SO2 and NO2 in the New York City metro area, along the I-95 corridor, and across the state of Pennsylvania.