358 citations · 408 across the 5 of their papers we have counts for
5 papers
Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar
Jamie Tolan, Hung-I Yang, Ben Nosarzewski +13
Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurement…
A global method to identify trees outside of closed-canopy forests with medium-resolution satellite imagery
John Brandt, Fred Stolle
Scattered trees outside of dense, closed-canopy forests are very important for carbon sequestration, supporting livelihoods, maintaining ecosystem integrity, and climate change ada…
Text mining policy: Classifying forest and landscape restoration policy agenda with neural information retrieval
John Brandt
Dozens of countries have committed to restoring the ecological functionality of 350 million hectares of land by 2030. In order to achieve such wide-scale implementation of restorat…
Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attention
John Brandt
Land use classification of low resolution spatial imagery is one of the most extensively researched fields in remote sensing. Despite significant advancements in satellite technolo…
Imbalanced multi-label classification using multi-task learning with extractive summarization
John Brandt
Extractive summarization and imbalanced multi-label classification often require vast amounts of training data to avoid overfitting. In situations where training data is expensive…