Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …

Accurate measuring, mapping, and monitoring of mangrove forests support the sustainable
management of mangrove blue carbon in the Asia-Pacific. Remote sensing coupled with …

Crops' above-ground biomass (AGB) is a crucial indicator that reflects crop health and
predicts crop yield. However, using only optical vegetation indices (VIs) can produce …

Mangroves are well-recognized for their very high carbon sequestration potential. However,
studies on their role in global carbon cycling and climate change are hindered due to lack of …

Soil total nitrogen (STN) is a crucial component of the ecosystem's nitrogen pool, and
accurate prediction of STN content is essential for understanding global nitrogen cycling …

As agricultural land expansion is the primary driver of deforestation, agroforestry could be an
optimal land use strategy for climate change mitigation and reducing pressure on forests …

Quantifying above ground biomass (AGB) and its spatial distribution can significantly
contribute to monitor carbon stocks as well as the carbon storage dynamics in forests. For …

The high-precision estimation of mangrove leaf area index (LAI) using a deep learning
regression algorithm (DLR) always requires a large amount of training sample data …

Forest canopy height estimates, at a regional scale, help understand the forest carbon
storage, ecosystem processes, the development of forest management and the restoration …

Abstracts Study region Euiam Lake in the Republic of Korea Study focus This study
establishes a framework to prioritize total phosphorus (TP) management strategies based on …