SBIR/STTR Research Award

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

Award identifier 4124668e3de4f58b99913f8fac90a9c5fcd3b5e951bceadde1578500a02dc2d9Awarding agency Department of Defense · National Geospatial-Intelligence Agency

Award amount

$1,999,836

Program and phase

SBIR · Phase II

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
National Geospatial-Intelligence Agency
Recipient company
INTELLIGENT MODELS PLUS INC.
Proposal award date
2024-09-30
Contract end date
2026-09-29
UEI
LFLDNXWR95D5
Solicitation number
21.3
Topic code
NGA213-001

Research abstract

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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

6 SBIR/STTR records share this UEI (2019–2024). Reported award amounts total $4,395,572. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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