TY  - JOUR 
AU  - Gui, Baoling
AU  - Sam, Lydia
AU  - Bhardwaj, Anshuman
AU  - Soto Gómez, Diego
AU  - González Peñaloza, Félix
AU  - Buchroithner, Manfred F.
AU  - Green, David R.
PY  - 2025
SN  - 0924-2716
UR  - https://hdl.handle.net/10259/11723
AB  - Growing global population, changing climate, and shrinking land resources demand for quicker, efficient, and
more accurate methods of mapping and monitoring vegetation cover in remote sensing datasets. Many deep
learning-based methods have been...
LA  - eng
PB  - Elsevier
KW  - Object-based classification
KW  - Graph convolutional
KW  - Vegetation mapping
KW  - Deep learning
KW  - Remote sensing
KW  - Aprendizaje automático
KW  - Machine learning
KW  - Cartografía de la vegetación
KW  - Vegetation mapping
TI  - SAGRNet: A novel object-based graph convolutional neural network for diverse vegetation cover classification in remotely-sensed imagery
DO  - 10.1016/j.isprsjprs.2025.06.004
T2  - ISPRS Journal of Photogrammetry and Remote Sensing
VL  - 227
M2  - 99
ER  -