Remote sensing (RS)-based models play an important role in estimating and monitoring
terrestrial ecosystem gross primary productivity (GPP). Several RS-based GPP models have …

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

The use of correlative ecological niche models has highly increased in the last decade.
Despite all literature and textbooks in this field, few practical guidelines exist on the correct …

Hydrological model calibration combining Earth observations and in situ measurements is a
promising solution to overcome the limitations of the traditional streamflow‐only calibration …

Abstract Smart, real-time, low-cost, and distributed ecosystem monitoring is essential for
understanding and managing rapidly changing ecosystems. However, new techniques in …

Satellite remote sensing is a power tool for the long-term monitoring of vegetation. This work,
with reference to a regional case study, investigates remote sensing potentialities for …

Forest aboveground biomass (AGB) is a prime forest parameter that requires global level
estimates to study the global carbon cycle. Light detection and ranging (LiDAR) is the state …

Due to the strong variation of precipitation in time and space, it is necessary to generate
accurate precipitation data with high spatiotemporal resolution. This is essential for many …

The water and carbon cycles are tightly linked and play a key role in the material and energy
flows between terrestrial ecosystems and the atmosphere, but the interactions of water and …

The benefits nature provides to people, called ecosystem services, are increasingly
recognized and accounted for in assessments of infrastructure development, agricultural …