Urban tree canopy maps are essential for providing urban ecosystem services. The
relationship between urban trees and urban climate change, air pollution, urban noise …

The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the
Institute of Advanced Research in Artificial Intelligence are presented here. The objective of …

Accurate and automatic identification of tree species information at the individual tree scale
is of great significance for fine-scale investigation and management of forest resources and …

Plantation forests provide critical ecosystem services and have experienced worldwide
expansion during the past few decades. Accurate map** of tree species through remote …

Positive-unlabeled learning (PU learning) in hyperspectral remote sensing imagery (HSI) is
aimed at learning a binary classifier from positive and unlabeled data, which has broad …

Pine wilt disease (PWD) poses a serious threat to the worldwide pine forest resources.
Unmanned aerial vehicle (UAV) remote sensing has been widely used for PWD control, due …

Earth vision research typically focuses on extracting geospatial object locations and
categories but neglects the exploration of relations between objects and comprehensive …

Rapid and accurate agricultural parcel map** from high-resolution remote sensing
imagery is fundamental to precision agriculture for smallholder farming systems. However …

Anomaly segmentation in high spatial resolution (HSR) remote sensing imagery is aimed at
segmenting anomaly patterns of the earth deviating from normal patterns, which plays an …

Tree species identification is a critical component of forest resource monitoring, and timely
and accurate acquisition of tree species information is the basis for sustainable forest …