9 papers
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…
TEMPO: Global Temporal Building Density and Height Estimation from Satellite Imagery
Tammy Glazer, Gilles Q. Hacheme, Akram Zaytar +9
We present TEMPO, a global, temporally resolved dataset of building density and height derived from high-resolution satellite imagery using deep learning models. We pair building f…
Machine Learning for Sustainable Rice Production: Region-Scale Monitoring of Water-Saving Practices in Punjab, India
Ando Shah, Rajveer Singh, Akram Zaytar +6
Rice cultivation supplies half the world's population with staple food, while also being a major driver of freshwater depletion--consuming roughly a quarter of global freshwater--a…
Optimizing Cloud-to-GPU Throughput for Deep Learning With Earth Observation Data
Akram Zaytar, Caleb Robinson, Girmaw Abebe Tadesse +5
Training deep learning models on petabyte-scale Earth observation (EO) data requires separating compute resources from data storage. However, standard PyTorch data loaders cannot k…
GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language Models
Gilles Quentin Hacheme, Girmaw Abebe Tadesse, Caleb Robinson +3
Classifying geospatial imagery remains a major bottleneck for applications such as disaster response and land-use monitoring-particularly in regions where annotated data is scarce…
Core-Set Selection for Data-efficient Land Cover Segmentation
Keiller Nogueira, Akram Zaytar, Wanli Ma +9
The increasing accessibility of remotely sensed data and their potential to support large-scale decision-making have driven the development of deep learning models for many Earth O…
Analyzing Decades-Long Environmental Changes in Namibia Using Archival Aerial Photography and Deep Learning
Girmaw Abebe Tadesse, Caleb Robinson, Gilles Quentin Hacheme +5
This study explores object detection in historical aerial photographs of Namibia to identify long-term environmental changes. Specifically, we aim to identify key objects -- Waterh…
Bootstrapping Rare Object Detection in High-Resolution Satellite Imagery
Akram Zaytar, Caleb Robinson, Gilles Q. Hacheme +6
Rare object detection is a fundamental task in applied geospatial machine learning, however is often challenging due to large amounts of high-resolution satellite or aerial imagery…
Weak Labeling for Cropland Mapping in Africa
Gilles Quentin Hacheme, Akram Zaytar, Girmaw Abebe Tadesse +4
Cropland mapping can play a vital role in addressing environmental, agricultural, and food security challenges. However, in the context of Africa, practical applications are often…