40 citations · 69 across the 4 of their papers we have counts for
6 papers
Annual Earth-observation embeddings encode wildfire disturbance and support simplified burned area mapping
Jovana Knezevic, Clement Atzberger, Zhengpeng Feng +3
Medium-resolution (10-30 m) burned area mapping is vital for monitoring wildfires and their impacts, but remains difficult to scale. Existing methods require either curated fire-sp…
TESSERA v2: Scaling Pixel-wise Earth Foundation Models
Zhengpeng Feng, Sadiq Jaffer, Ira Shokar +12
Pixel-wise Earth-observation (EO) foundation models are now achieving state-of-the-art performance via generated spatial embeddings. However, how these models scale and how best to…
Scaling Up Forest Vision with Synthetic Data
Yihang She, Andrew Blake, David Coomes +1
Accurate tree segmentation is a key step in extracting individual tree metrics from forest laser scans, and is essential to understanding ecosystem functions in carbon cycling and…
Steps towards an Ecology for the Internet
Anil Madhavapeddy, Sam Reynolds, Alec P. Christie +10
The Internet has grown from a humble set of protocols for end-to-end connectivity into a critical global system with no builtin "immune system". In the next decade the Internet wil…
TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis
Zhengpeng Feng, Clement Atzberger, Sadiq Jaffer +11
Satellite Earth-observation (EO) time series in the optical and microwave ranges of the electromagnetic spectrum are often irregular due to orbital patterns and cloud obstruction.…
Tree species classification from hyperspectral data using graph-regularized neural networks
Debmita Bandyopadhyay, Subhadip Mukherjee, James Ball +3
We propose a novel graph-regularized neural network (GRNN) algorithm for tree species classification. The proposed algorithm encompasses superpixel-based segmentation for graph con…