Multi-Sensor Multi-platform Surface Topography and Vegetation Structure Data Fusion Information System (STV-FIS)

We propose to develop a multi-sensor, multi-platform surface topography and vegetation structure (STV) data fusion information system (STV-FIS) to characterize future STV performance. Our STV-FIS will address all four major gaps and gap-filling activities identified in the STV incubation study white paper (STVWP, p. vii): 1) Knowledge Gaps by providing a large number of simulated data products, 2) Methodology Gaps by developing and implementing a multi-sensor data fusion information system, and 3) Algorithm Gaps by integrating physically based models with AI for STV change detection, and 4) Measurement Gaps by developing trade study for simulating multi-sensor and multi-platform architecture and smart-tasking. Our goal is to leverage existing models and data in active sensing of STV geophysical parameters to build a multi-sensor, multi-platform STV Data Fusion Information System (STV-FIS) to address the STV identified gaps by focusing on the following objectives: Obj-1. Develop a multi-sensor (Radar and Lidar) fusion formulation and testing platform based on a dedicated EM model of vegetation 3D structure and surface condition (topography, dry, wet, snow, etc.). Obj-2. Develop Artificial Intelligence (AI) model-data analytics for sensitivity analysis, STV parameter retrieval, change detection, and uncertainty assessment. Obj-3. Simulate a dedicated data fusion observing system for multi-sensor and multi-platform trade study, and on-board processing and smart-tasking. Obj-4. Integrate model and data fusion within a visualization system and on-line analytical toolbox for enabling simulations of STV observations, AI algorithms, and implementation future OSSEs. The proposed STV-FIS include a user-friendly platform along with visualization and algorithmic tool boxes to meet the needs of all STV disciplines for data analysis, trade studies and OSSEs. STV-FIS components will start at average TRL of 2 and exit at the average TRL of 5.

Maturation of observing systems, instrument technology, and measurement concepts for Planetary Boundary Layer and Surface Topography and Vegetation

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