Space-based Machine Automated Recognition Technique (SMART)
The goal of the SMART program is to automate the quantitative analysis of space-based imagery to perform broad-area search for natural and anthropogenic events and characterize their extent and progression in time and space. The SMART program aims to develop capabilities in the spectral and temporal domains, enabling seamless integration and fusion (i.e., absolute calibration) of data from multiple sensors to deliver a comprehensive representation of seven natural or anthropogenic evolving events. Examples of such events include: heavy construction, urban development, crop disease propagation, forest fire, insect or battle damage, human migration, mining, logging, farming, and other natural events such as flooding, mudslides, or earthquakes. The SMART program will require innovations in new computing approaches and calibration techniques in order to rapidly and reliably compare thousands of images from multiple sensors registered in space and time. The SMART program will also leverage algorithmic approaches to:
- Search for specific activities
- Detect and monitor activities throughout time and over broad areas
- Characterize the progression of events and activities temporally and categorically
Related Program(s)
Research Area(s)
- Remote sensing
- Image processing
- Atmospheric correction
- Machine learning
- Radiometric calibration
- Multi-spectral
- Multi-temporal
- Datacube
- Data fusion
- Automation
- Spaceborne
- Geo-registration
- Change detection
- Classification
- Pixel-based
Related Article(s)
