Detailed information on spatial patterns of tree species diversity (TSD) is essential for
biodiversity assessment, forest disturbance monitoring, and the management and …

Abstract Satellite-based Machine Learning (ML) modelling has emerged as a powerful tool
to understand and quantify spatial relationships between landscape dynamics, biophysical …

An extensive artificial water diversion project aimed at alleviating the shortage of ecological
water in lakes can change the original hydrological and physicochemical states and further …

Forest covers about a third of terrestrial land surface, with tropical and subtropical zones
being a major part. Remote sensing applications constitute a significant approach to …

The seasonal occurrence of plant communities in rivers' reaches has a direct impact on the
flow resistance and sediment dynamics. Monitoring the occurrence of plant communities and …

Measuring and monitoring tree diversity is a prerequisite for altering biodiversity loss and the
sustainable management of forest ecosystems. High temporal satellite remote sensing …

Anthropogenically-driven climate change, land-use changes, and related biodiversity losses
are threatening the capability of forests to provide a variety of valuable ecosystem services …

Forests contribute significantly to terrestrial biodiversity conservation. Monitoring of tree
species diversity is vital due to climate change factors. Remote sensing imagery is a means …

Abstract Machine learning image classification algorithms offer a potential for effective and
efficient classification of remotely sensed images covering glaciated areas. The Columbia …

Forest ecosystems depend on species of tree variety. Remote sensing for obtaining large-
scale spatial distribution information of tree species diversity is a geoscience research …