arXiv:2609.12533v1 Announce Type: cross Abstract: Real-world Earth observation (EO) agents must translate high-level scientific questions into executable workflows to acquire observations, prepare da...
arXiv:2606. 13148v1 Announce Type: new Abstract: Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite imagery, geospatial context, and simulator outputs.
arXiv:2608. 10494v1 Announce Type: new Abstract: Earth observation (EO) agents construct scientifically valid tool workflows and ground their conclusions in current geospatial evidence.
Geographic Information System (GIS) professionals rely on multi-step spatial analysis workflows to support decision-making in urban planning, disaster response, and environmental monitoring. The process is tedious, time-consuming, and error-prone.
arXiv:2606. 12821v1 Announce Type: new Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis, and AI agents that automate geospatial workflows remain unvalidated: no benchmark evaluates agents operating through structured tool calling against real APIs.
GeoFitBench-LLM is a benchmark designed to evaluate large language models (LLMs) on their ability to elicit geospatial data requirements for geo‑analytic tasks. It focuses on two reasoning dimensions—spatio‑temporal relational and semantic grounding—and uses a provider‑independent schema to encode ground‑truth requirements. Experiments on seven models show that while many can identify necessary resources, accurately specifying fitness‑for‑use remains challenging, with GPT‑5.4 Thinking recovering all resources in 66.67% of cases.
arXiv:2607. 12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models.
arXiv:2609.13667v1 Announce Type: new Abstract: Geospatial agents are increasingly expected to support recurring and evolving analytical tasks rather than execute isolated workflows. In such settings...
arXiv:2607. 24772v1 Announce Type: new Abstract: Geoscience research requires complex analysis and domain expertise, with remote sensing (RS) observations as a key foundation.
Beyond perception, reasoning is essential in remote sensing for advanced interpretation, inference, and decision-making. Recent advances in large language models (LLMs) have enabled tool-augmented agents that leverage external tools to perform complex analytical tasks.
arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in "deep research" by iteratively navigating the open web to synthesize information, real-world p...
arXiv:2607. 02387v1 Announce Type: cross Abstract: NASA and its data centers hold thousands of geoscience datasets and tools like Worldview, Giovanni, the Science Discovery Engine, and Harmony.