STV Precursor Coincident Datasets
Lidar, radar, and stereophotogrammetry provide ways to obtain the primary observable for STV. It is therefore important to establish information systems technologies to combine observations from multiple sensors. It is also important to note that even among the same family of observations (e.g., stereo imaging) observations using different platforms, and different geometries need to be reconciled.
Analyzing existing data, collecting new datasets, and sampling those new data sets in the way an STV sensor will observe provides a means of defining the needs for a new observational system. Sensitivity studies leveraging the science modeling will define what needs to be measured to understand the science or application physical process being addressed. Surrogate datasets, whether collected or simulated, will help drive technology and development and validate expected future observations for various system designs.
![Layered triangle diagram with data at the bottom, topped by a layer labelled information, which is in turn topped by knowledge, and wisdom at the top. Data is sub-labeled Multi-View Time series, information is sub-labeled systematic products, knowledge is sub-labeled process understanding, and wisdom is sub-labeled with action. Each of these in turn is filled with the variety of products that compose those elements.](https://science.nasa.gov/wp-content/uploads/2024/08/stv-triangle.png?w=4096&format=png)
Activities related to data analysis would include but not be limited to:
- Assessment and acquisition of existing data for analysis from commercial and government sources
- In situ data collection of higher resolution representative observations or data required for validation
- Suborbital flight demonstrations to create high-resolution observations for surrogate and validation data
- Simulated data for comparison with observed data
- Characterize error sources and uncertainties