TY - GEN
T1 - Shiny Dashboard - NYC Trees Benefit Estimation
AU - Zharri, Elona
AU - Robila, Stefan A.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - data visualization
KW - open science data
KW - patter recognition
KW - shiny dashboard
UR - http://www.scopus.com/inward/record.url?scp=85141937544&partnerID=8YFLogxK
U2 - 10.1109/LISAT50122.2022.9923953
DO - 10.1109/LISAT50122.2022.9923953
M3 - Conference contribution
AN - SCOPUS:85141937544
T3 - 2022 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2022
BT - 2022 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2022
Y2 - 6 May 2022
ER -