2 citations · 7 across the 24 of their papers we have counts for
11 papers · 1 filter
Fields of the Planet: Field Boundary Mapping Beyond 10m
Isaac Corley, Caleb Robinson, Jennifer Marcus +1
Field-boundary maps support crop monitoring, irrigation planning, and yield estimation, but many smallholder parcels span only a few 10 m Sentinel-2 pixels. We introduce Fields of…
No One Knows the State of the Art in Geospatial Foundation Models
Isaac Corley, Nils Lehmann, Caleb Robinson +6
Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, and other high-stakes Earth-o…
Overhead Wildlife Locator (OWL): Benchmarking Weakly Supervised Learning for Aerial Wildlife Surveys
Isai Daniel Chacón, Zhongqi Miao, Bruno Demuro +9
Automated aerial wildlife surveys increasingly rely on deep learning, yet standard object detectors require bounding-box annotations, reported to be up to seven times slower and th…
The first global agricultural field boundary map at 10m resolution
Caleb Robinson, Gedeon Muhawenayo, Subash Khanal +9
The agricultural field is the natural unit at which crops are planted, managed, regulated, and reported, yet most global remote-sensing products for agriculture are only available…
WATCH: Wide-Area Archaeological Site Tracking for Change Detection
Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7
Monitoring archaeological sites at scale is vital for protecting cultural heritage, yet pinpointing when disturbances occur remains difficult because visual cues are subtle and gro…
GeoAI Agency Primitives
Akram Zaytar, Rohan Sawahn, Caleb Robinson +5
We present ongoing research on agency primitives for GeoAI assistants -- core capabilities that connect Foundation models to the artifact-centric, human-in-the-loop workflows where…
PRUE: A Practical Recipe for Field Boundary Segmentation at Scale
Gedeon Muhawenayo, Caleb Robinson, Subash Khanal +10
Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field mapping are sensitive to illuminat…
XMENTOR: A Rank-Aware Aggregation Approach for Human-Centered Explainable AI in Just-in-Time Software Defect Prediction
Saumendu Roy, Banani Roy, Chanchal Roy +1
Machine learning (ML)-based defect prediction models can improve software quality. However, their opaque reasoning creates an HCI challenge because developers struggle to trust mod…
Advancing Earth Observation Through Machine Learning: A TorchGeo Tutorial
Caleb Robinson, Nils Lehmann, Adam J. Stewart +4
Earth observation machine learning pipelines differ fundamentally from standard computer vision workflows. Imagery is typically delivered as large, georeferenced scenes, labels may…
Satellite-Based Detection of Looted Archaeological Sites Using Machine Learning
Girmaw Abebe Tadesse, Titien Bartette, Andrew Hassanali +7
Looting at archaeological sites poses a severe risk to cultural heritage, yet monitoring thousands of remote locations remains operationally difficult. We present a scalable and sa…
Fields of The World: A Field Guide for Extracting Agricultural Field Boundaries
Isaac Corley, Hannah Kerner, Caleb Robinson +1
Field boundary maps are a building block for agricultural data products and support crop monitoring, yield estimation, and disease estimation. This tutorial presents the Fields of…