The training date is in the past. However, videos and resources of the training can be accessed here.
At night, satellite images of Earth capture a uniquely human signal - artificial lighting. Remotely-sensed lights at night provide a new data source for improving our understanding of interactions between human systems and the environment. NASA has developed the Black Marble, a daily calibrated, corrected, and validated product suite, so night light data can be used effectively for scientific observations. Black Marble is playing a vital role in research on light pollution, illegal fishing, fires, disaster impacts and recovery, and human settlements and associated energy infrastructures. The data (originally retrieved from the VIIRS day night band sensor) has been corrected by multiple novel algorithms, providing high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected nighttime radiances.
This webinar will focus on building the skills needed to choose the appropriate night lights product, acquire and understand Black Marble data, and how to use the data in analyses for tracking urbanization, electrification, and disaster monitoring. Participants are encouraged to take the NASA ARSET online training "Fundamentals of Remote Sensing - Session 1" before this online training. In order to be able to follow along with the demonstration associated with this online training, participants should also install QGIS on their computers.
- Understand the new capabilities of NASA’s Black Marble product and which nighttime lights product to use for different science applications
- Learn the basics of how to acquire and interpret information in Black Marble data
- Manipulate Black Marble data and create time-series analyses
- Recognize distortions that need to be corrected in Black Marble images
- Basic application of Black Marble data for topics relevant to the SDGs: tracking urbanization, disaster monitoring, and electrification
Local, regional, state, federal, and international organizations interested in global Earth system science and applications to topics relevant to the SDGs: tracking urbanization, disaster monitoring, and electrification.