[HTML][HTML] Advances in Earth observation and machine learning for quantifying blue carbon
Blue carbon ecosystems (mangroves, seagrasses and saltmarshes) are highly productive
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
A review of carbon monitoring in wet carbon systems using remote sensing
Carbon monitoring is critical for the reporting and verification of carbon stocks and change.
Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and …
Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and …
Land use and land cover map** using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A comparison of two composition methods
Accurate and real-time land use/land cover (LULC) maps are important to provide precise
information for dynamic monitoring, planning, and management of the Earth. With the advent …
information for dynamic monitoring, planning, and management of the Earth. With the advent …
[HTML][HTML] Integrating forest cover change and carbon storage dynamics: Leveraging Google Earth Engine and InVEST model to inform conservation in hilly regions
Forests are vital in combating climate change by storing and sequestrating CO 2 from the
atmosphere. Measuring the influence of land use/land cover (LULC) changes on the …
atmosphere. Measuring the influence of land use/land cover (LULC) changes on the …
Multi-hazard exposure map** using machine learning for the State of Salzburg, Austria
We live in a sphere that has unpredictable and multifaceted landscapes that make the risk
arising from several incidences that are omnipresent. Floods and landslides are widespread …
arising from several incidences that are omnipresent. Floods and landslides are widespread …
[HTML][HTML] Seagrass map** using high resolution multispectral satellite imagery: A comparison of water column correction models
Satellite remote sensing is an efficient and economical technique for studying coastal
bottoms in clear and shallow waters. Accordingly, the main objective of this study is the …
bottoms in clear and shallow waters. Accordingly, the main objective of this study is the …
A new hybrid firefly–PSO optimized random subspace tree intelligence for torrential rainfall-induced flash flood susceptible map**
Flash flood is one of the most dangerous natural phenomena because of its high
magnitudes and sudden occurrence, resulting in huge damages for people and properties …
magnitudes and sudden occurrence, resulting in huge damages for people and properties …
Spatiotemporal map** and monitoring of mangrove forests changes from 1990 to 2019 in the Northern Emirates, UAE using random forest, Kernel logistic …
Mangrove forests are acting as a green lung for the coastal cities of the United Arab
Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting …
Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting …
Semantic segmentation of seagrass habitat from drone imagery based on deep learning: A comparative study
E Jeon, S Kim, S Park, J Kwak, I Choi - Ecological Informatics, 2021 - Elsevier
In this study, the utilization of drone images and deep learning to monitor the seagrass
habitat, which is important in the marine ecosystem, is evaluated. Two experiments were …
habitat, which is important in the marine ecosystem, is evaluated. Two experiments were …
Temporal stability of seagrass extent, leaf area, and carbon storage in St. Joseph Bay, Florida: a semi-automated remote sensing analysis
Seagrasses are globally recognized for their contribution to blue carbon sequestration.
However, accurate quantification of their carbon storage capacity remains uncertain due, in …
However, accurate quantification of their carbon storage capacity remains uncertain due, in …