Geospatial-Temporal Sensemaking of Remote Sensing Activity Detections with Multimodal Large Language Model
We introduce SMART-HC-VQA, a Sentinel-2-based visual question answering dataset derived from the IARPA SMART Heavy Construction dataset, designed for spatiotemporal analysis of human activity. The dataset transforms construction-site annotations, construction-type labels, temporal-phase labels, geographic metadata, and observation relationships into natural language question-answer triplets. This approach redefines the existing dataset as a temporally extended automatic target recognition and visual question answering (VQA) challenge, considering a fixed geospatial site as a target whose attributes and activity states evolve across sparse satellite observations. Currently, SMART-HC-VQA co...
| Authors | David F. Ramirez, Tim Overman, Kristen Jaskie et al. |
|---|---|
| Primary category | eess.IV |
| Published | 11 May 2026 |
| Last updated at source | 11 May 2026 |
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