@inproceedings{f95714ed53784339a49714481308c6e5,
title = "Shiny Dashboard - NYC Trees Benefit Estimation",
abstract = "This project describes the research and development efforts to develop a web-based interface that allows the visualization of how the tree canopy confers ecological, economic, and social benefits and how it can be used to enhance neighborhoods disproportionately affected by environmental challenges such as excessive heat, impervious surfaces, and air pollution. It provides an example how data science can provide communities with tools that employ Open Data to research impact of vegetation spread to aspects such as energy usage, house prices and new planting. Using the analysis and visualization of the NYC trees dataset, an interactive Shiny dashboard representing 2015 New York City Street Tree Census - Tree Data was developed. The data was curated into an easier form to understand, highlighted the trends and outliers as a pictorial and graphical format to illustrate the existing trees planted around a given address, and estimation benefit of the trees based on their age, condition, and type. The application development provides an example how data science can provide communities with tools that employ Open Data to research impact of vegetation spread to aspects such as energy usage or house prices.",
keywords = "data visualization, open science data, patter recognition, shiny dashboard",
author = "Elona Zharri and Robila, {Stefan A.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; null ; Conference date: 06-05-2022",
year = "2022",
doi = "10.1109/LISAT50122.2022.9923953",
language = "English",
series = "2022 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2022",
}