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LUCID (Land Use Classification Intelligence Discovery) -- Phase 2B

Awarded
208682SBIR / STTR

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

General Info

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N/A

Place of Performance

Not specified

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NONE

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Organization & Contact Information

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AgencyDepartment of Defense → National Geospatial-Intelligence Agency
ContactsNo contacts available
OfficeN/A
Office AddressN/A
ContactsNo contact information available

Full Description

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LUCID (Land Use Classification Intelligence Discovery) is a new state-of-the-art Geospatial AI system that autonomously gathers and analyzes a broad spectrum of internet-based data to classify fine-grained land use and land cover (LULC) features. It detects unconventional, illegal, unsafe, and hostile land uses, like hidden military installations or biochemical laboratories, through a joint analysis of satellite imagery and all-source multimodal data.The Core Capabilities of LUCID include:Interoperating Multimodal Geospatial Data: LUCID integrates diverse data sources—including satellite images, street views, text, social media interactions, and mobile data—ensuring a comprehensive analysis of geographical areas and contexts to discern land use patterns and concealed activities.Unified Embeddings for GeoAI Pre-training: LUCID embeds the maps with geography-aware codes to align the core modalities—from imagery and text to trajectories—into a unified GeoAI Foundation Model, pre-trained to tackle diverse geospatial tasks.Spatiotemporal Semantic Graphs: It performs alignment and real-time fusion of multimodal data to create knowledge graphs composed in a Lego®-like fashion, offering a unified view of intelligence built from complementary data sources and modalities.Interactive Dynamic Maps: LUCID achieves the new state-of-the-art in interactive cartography via animated maps that display the evolving “Information Layers” rich in semantic content, which LUCID discovers, ingests, and analyzes on-the-fly to produce in-depth regional insights, visualized to inform the analysts of the high-value intelligence.Emergent Self-supervised GeoAI: It enables the autonomous AI self-play, enriched by synergistic human-AI dialog, to harvest and analyze diverse semantic contexts gathered from the web, linking the multimodal data to the collected labels to circumvent the manual data-labeling bottleneck.Deep GeoAI Sense-making: Through neuro-symbolic reasoning over multimodal semantic graphs, supported by zero-shot learning capabilities, LUCID learns the spatiotemporal pattern signatures of rare, covert, obscure, novel, never-before-seen, and other elusive land uses.Performance Metrics Dashboard: It embeds the maps with a comprehensive metrics dashboard for evaluating model performance and tracing multimodal evidence trails of specific classifications, helping the analysts understand and corroborate the AI-derived insights.LUCID combines the cutting-edge AI models with innovative mapping and data fusion techniques to offer unparalleled geospatial analytics capabilities to the analysts, while empowering the analysts to make more informed and nuanced decisions with accuracy and speed, even in the most complex and obscured environments. It introduces a new level of precision and depth to the field of geospatial analytics, offering an innovative approach to data integration, analysis, and visualization to advance geospatial intelligence capabilities and platforms.

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Miguel
Hillary
Keith Deutsch
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