Earth Observation methodologies in Carbon Credit Domain

Earth observation methodologies in the carbon credits domain. Overview of Carbon Sequestration Carbon sequestration is the process of capturing and storing atmospheric carbon dioxide (CO2). It is one of the most promising methods to mitigate the increasing levels of greenhouse gases in the atmosphere, which are contributing to global climate change. Forests, soils, and oceans are natural carbon sinks where this CO2 is stored. Various techniques such as afforestation, reforestation, and soil management practices play a crucial role in capturing carbon. Remote sensing technologies provide a cost-effective and scalable way to monitor these carbon sequestration efforts across large areas. Relevance in Climate Mitigation and Carbon Trading As the world seeks solutions to mitigate the impact of climate change, carbon trading has emerged as an important market mechanism under the Paris Agreement. Carbon credits represent the reduction or removal of CO2 emissions, and they can be traded in both compliance and voluntary markets. Remote sensing technologies allow for accurate estimation of carbon stocks, enabling verification of carbon credits and supporting the carbon trading system. Effective monitoring of carbon sequestration is essential for maintaining transparency and integrity in carbon markets. Remote Sensing’s Role in Carbon Stock Estimation Remote sensing technologies, particularly satellite-based methods, play a key role in estimating carbon stocks by providing detailed, frequent, and reliable data. These methods allow for the monitoring of vegetation health, land-use changes, and biomass estimation, which are critical for assessing carbon sequestration potential. With the development of new sensors and satellite missions like Landsat and Sentinel, the capacity to monitor carbon stocks at a global scale has improved significantly. Literature Review Current Methods of Biomass and Carbon Stock Estimation Biomass estimation has traditionally been carried out through ground-based field measurements, but these are costly and time-consuming, making remote sensing a more feasible option for large-scale estimations. Common methods involve the use of vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and other spectral data obtained from satellites. These indices are used to correlate the amount of vegetation cover with carbon content. Vegetation Indices in Carbon Stock Assessment Vegetation indices like NDVI and EVI have been widely used for estimating vegetation biomass and carbon stocks. NDVI is particularly useful for detecting the presence and health of 3 vegetation, while EVI enhances sensitivity to areas with high biomass. However, the effectiveness of these indices varies depending on the vegetation type, seasonality, and environmental conditions. Calibration with ground-based measurements is often required for more accurate assessments. Challenges in Biomass Estimation Using Remote Sensing Despite the advancements in remote sensing, several challenges remain in accurately estimating biomass and carbon stocks. These include the complexity of vegetation structure, seasonal variations, cloud cover, and the varying spatial resolutions of satellite imagery. Additionally, the relationship between vegetation indices and biomass is not always linear, requiring further calibration and validation through ground-truthing techniques.