학술논문
Forest Height Estimation Using Multi-Frequency Sar and a Stacking Regression
Document Type
Conference
Source
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2023 - 2023 IEEE International. :1353-1356 Jul, 2023
Subject
Language
ISSN
2153-7003
Abstract
The knowledge of the Forest Height (FH) is important for monitoring the forests, and it can be used as a proxy variable of other forest parameters as the aboveground biomass. It is also important for understanding the climate change and prepare the wildfire seasons. The most effective way to map the FH is through field campaigns or airborne laser scanning, but both are expensive and not scalable. Alternatively, spaceborne Synthetic Aperture Radar (SAR) data may be used. However, it often relies on the acquisition of large ground truth datasets. In this paper, a new Regression Methodology (RM) that makes use of SAR data and a Stacking Regressor that minimises the amount of data needed to map the FH of a region is presented. Tested on a total of 16 regions between Portugal and Spain, plus one in California, the RM achieved a R 2 between 42.12%-62.62%, and a RMSE between 0.96m-4.49m.