1k citations · 1.7k across the 31 of their papers we have counts for
5 papers · 1 filter
Annual field-scale maps of tall and short crops at the global scale using GEDI and Sentinel-2
Stefania Di Tommaso, Sherrie Wang, Vivek Vajipey +3
Crop type maps are critical for tracking agricultural land use and estimating crop production. Remote sensing has proven an efficient and reliable tool for creating these maps in r…
With big data come big problems: pitfalls in measuring basis risk for crop index insurance
Matthieu Stigler, Apratim Dey, Andrew Hobbs +1
New satellite sensors will soon make it possible to estimate field-level crop yields, showing a great potential for agricultural index insurance. This paper identifies an important…
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery
Yezhen Cong, Samar Khanna, Chenlin Meng +6
Unsupervised pre-training methods for large vision models have shown to enhance performance on downstream supervised tasks. Developing similar techniques for satellite imagery pres…
Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution
Yutong He, William Zhang, Chenlin Meng +3
Automated tracking of urban development in areas where construction information is not available became possible with recent advancements in machine learning and remote sensing. Un…
Unlocking large-scale crop field delineation in smallholder farming systems with transfer learning and weak supervision
Sherrie Wang, Francois Waldner, David B. Lobell
Crop field boundaries aid in mapping crop types, predicting yields, and delivering field-scale analytics to farmers. Recent years have seen the successful application of deep learn…