TerraQ: Spatiotemporal Question-Answering on Satellite Image Archives
Not on the map. Why?
Abstract (arXiv)
TerraQ is a spatiotemporal question-answering engine for satellite image archives. It is a natural language processing system that is built to process requests for satellite images satisfying certain criteria. The requests can refer to image metadata and entities from a specialized knowledge base (e.g., the Emilia-Romagna region). With it, users can make requests like "Give me a hundred images of rivers near ports in France, with less than 20% snow coverage and more than 10% cloud coverage", thus making Earth Observation data more easily accessible, in-line with the current landscape of digital assistants.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 19 references that are in the map. First posted on arXiv 6 Feb 2025.
Builds on
7 of 19 references.
References · 7
- 2023GPT-4 Technical Reportcited by 18,132
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2023Mistral 7Bcited by 3,065
- 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
- 2022Translating Place-Related Questions to GeoSPARQL Queriescited by 3
- 2022Three-dimensional Geospatial Interlinking with JedAI-spatialcited by 2
Built on by
Citing papers per year: 2025: 1.
1 paper.