Application of support vector machines for landuse classification using high-resolution rapideye images: A sensitivity analysis
The classification accuracy of remotely sensed data and its sensitivity to classification
algorithms have a critical importance for the geospatial community, as classified images …
algorithms have a critical importance for the geospatial community, as classified images …
Towards automated large-scale 3D phenoty** of vineyards under field conditions
In viticulture, phenotypic data are traditionally collected directly in the field via visual and
manual means by an experienced person. This approach is time consuming, subjective and …
manual means by an experienced person. This approach is time consuming, subjective and …
[PDF][PDF] Data-centric machine learning for geospatial remote sensing data
Subpixel land-cover classification for improved urban area estimates using Landsat
Urban areas are Earth's fastest growing land use that impact hydrological and ecological
systems and the surface energy balance. The identification and extraction of accurate spatial …
systems and the surface energy balance. The identification and extraction of accurate spatial …
Urban growth dynamics in Perth, Western Australia: using applied remote sensing for sustainable future planning
Earth observation data can provide valuable assessments for monitoring the spatial extent of
(un) sustainable urban growth of the world's cities to better inform planning policy in …
(un) sustainable urban growth of the world's cities to better inform planning policy in …
Adaptive stop** criterion for top-down segmentation of ALS point clouds in temperate coniferous forests
The development of new approaches to individual tree crown delineation for forest inventory
and management is an important area of ongoing research. The increasing availability of …
and management is an important area of ongoing research. The increasing availability of …