Monitoring and Analyzing $(CO_{2})$ Concentrations and Vegetation Health in Lima, Peru Using Satellite Images

Climate change, driven significantly by carbon diox-ide (CO2) emissions, poses a major threat globally, contributing to extreme weather events and health impacts. This study focuses on Lima, Peru, a city facing severe air pollution, to monitor and analyze CO2 concentrations using satellite imagery. By leveraging Sentinel-2 and OCO-3 data, we examine the relationship between CO2 levels and vegetation health, using vegetation indices such as NDVI. Our findings reveal temporal variability in these relationships, underscoring the complex interactions between atmospheric CO2 and possible vegetation influenced by seasonal and environmental factors. The study recommends increasing the frequency of satellite observations and integrating these findings with climate models to improve urban green space management and climate change mitigation strategies. This approach enhances spatial and temporal resolution of CO2 data, facilitating informed decision-making for environmental and public health interventions.

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Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/intercon63140.2024.10833497
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
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article

Monitoring and Analyzing $(CO_{2})$ Concentrations and Vegetation Health in Lima, Peru Using Satellite Images

A.S. Andres, Alby Robson Benjamin, Armas Jose Ignacio
Air Quality Monitoring and Forecasting
article

Monitoring and Analyzing $(CO_{2})$ Concentrations and Vegetation Health in Lima, Peru Using Satellite Images

A.S. Andres, Alby Robson Benjamin, Armas Jose Ignacio
article en

Abstract

Climate change, driven significantly by carbon diox-ide (CO2) emissions, poses a major threat globally, contributing to extreme weather events and health impacts. This study focuses on Lima, Peru, a city facing severe air pollution, to monitor and analyze CO2 concentrations using satellite imagery. By leveraging Sentinel-2 and OCO-3 data, we examine the relationship between CO2 levels and vegetation health, using vegetation indices such as NDVI. Our findings reveal temporal variability in these relationships, underscoring the complex interactions between atmospheric CO2 and possible vegetation influenced by seasonal and environmental factors. The study recommends increasing the frequency of satellite observations and integrating these findings with climate models to improve urban green space management and climate change mitigation strategies. This approach enhances spatial and temporal resolution of CO2 data, facilitating informed decision-making for environmental and public health interventions.

University of the Pacific (PE)
Openalex Percentile: Top 78%
Air Quality Monitoring and Forecasting
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Monitoring and Analyzing $(CO_{2})$ Concentrations and Vegetation Health in Lima, Peru Using Satellite Images — A.S. Andres, Alby Robson Benjamin, et al. · (2024) | TGRS Research Map | TGRS