The UConn Global Environmental Remote Sensing (GERS) Lab has developed a new remote sensing method to continuously monitor primary forest loss and determine what factors are driving that loss.

Conifer and mesquite encroachment into prairie chicken habitats. Understanding vulnerability to burning. Soil erosion risk assessment. Spectral detection of near-surface moisture content. Conducting ...

The Agriculture and Forest Ecosystems Team analyses a valuable collection of earth observation time series data for regions of Earth characterized by agriculture and forests. The team develops ...

The accurate and automatic detection of individual trees is crucial for forestry, monitoring of biodiversity, and various other applications. Very high resolution RGB data from manned and unmanned ...

The solar-induced chlorophyll fluorescence (SIF) remote sensing data contain an abundance of plant physiological and biochemical information, which can directly reflect the dynamic process changes ...