Toward carbon neutral cities: A comparative analysis between Sentinel 2 and WorldView 3 satellite image processing for tree carbon stock mapping in Brussels

Abstract

Because of the high costs associated with data sources, urban policymakers struggle to employ cost-effective remote sensing methods for evaluating trees and their potential contributions to atmospheric Carbon Stock (CS). While free data sources like Copernicus Sentinel satellite data could be explored, there are a few studies illustrating its potential for mapping urban tree C. Here, the Sentinel 2 (S2)-derived Normalized Difference Vegetation Index (NDVI) was used to model CS for street trees in Brussels. In parallel, the WorldView 3 (WV3)-derived NDVI layer was also used for a similar study area to compare the CS mapping outcomes regarding dominant tree species. The accuracy level was around 90 % (R²=0.89, r=0.94, and RMSE= 97 kg) in the case of WV3 data, whereas it was about 60 % (R²=0.60, r=0.79, and RMSE = 189.6 kg), even with a coarse resolution regarding the S2 data. This study also shows the strength and scope of using S2 data over WV3 data, illustrating the convenience in terms of accuracy and cost-effectiveness compared to existing methods. The applied methodology could be utilized to monitor urban trees and predict the level of possible carbon sequestration, even considering a larger city like Brussels with a complex agglomeration. It could be a solid additional support for the authorities of European towns and developing countries, especially in terms of being cost-efficient and readily embraced by users.