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 …
Remote sensing of boreal wetlands 2: methods for evaluating boreal wetland ecosystem state and drivers of change
The following review is the second part of a two part series on the use of remotely sensed
data for quantifying wetland extent and inferring or measuring condition for monitoring …
data for quantifying wetland extent and inferring or measuring condition for monitoring …
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Background Above-ground biomass (AGB) is a basic agronomic parameter for field
investigation and is frequently used to indicate crop growth status, the effects of agricultural …
investigation and is frequently used to indicate crop growth status, the effects of agricultural …
Comparison between geostatistical and machine learning models as predictors of topsoil organic carbon with a focus on local uncertainty estimation
F Veronesi, C Schillaci - Ecological Indicators, 2019 - Elsevier
In recent years, the environmental modeling community has moved away from kriging as the
main map** algorithm and embraced machine learning (ML) as the go-to method for …
main map** algorithm and embraced machine learning (ML) as the go-to method for …
Large-scale high-resolution coastal mangrove forests map** across West Africa with machine learning ensemble and satellite big data
Coastal mangrove forests provide important ecosystem goods and services, including
carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are …
carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are …