The global availability of high spatial resolution images makes mapping tree species
distribution possible for better management of forest resources. Previous research mainly …

Many studies have investigated the effects of spectral and spatial features of remotely
sensed data and topographic characteristics on land-cover and forest classification results …

Although many advances have been made in past decades, land cover classification of fine-
resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral …

Recognition of tree species and geospatial information on tree species composition is
essential for forest management. In this study, tree species recognition was examined using …

Urban tree species mapping is an important prerequisite to understanding the value of
urban vegetation in ecological services. In this study, we explored the potential of bi …

The spatial distribution of forest stands is one of the fundamental properties of forests. Timely
and accurately obtained stand distribution can help people better understand, manage, and …

Tree species characterise biodiversity, health, economic potential, and resilience of an
ecosystem, for example. Tree species classification based on remote sensing data …

Individual tree species identification is important for urban forest inventory and ecology
management. Recent advances in remote sensing technologies facilitate more detailed …

Land cover mapping (LCM) in complex surface-mined and agricultural landscapes could
contribute greatly to regulating mine exploitation and protecting mine geo-environments …

Spatially explicit information on tree species composition is important for both the forest
management and conservation sectors. In combination with machine learning algorithms …