Remote sensing#
Data levels#
Firstly, it is important to understand the different levels of data which we can work with. A full description can be found here: https://www.earthdata.nasa.gov/engage/open-data-services-and-software/data-information-policy/data-levels, but as a summary:
Level 0: This is the most basic data from the spacecraft, at full resolution. It is unprocessed from the spacecraft.
Level 1: Processing is included to label the data.
Level 2: Geophysical variables are derived at the same resolution as the L1 data.
Level 3: Variables are included on maps and can be averaged out over time periods.
Level 4: Variables are derived from multiple data streams including other L1 data.
Satellites#
Landsat#
Landsat satellites have been providing detailed images of the Earth’s surface since the 1970s. Their long-term data archive is highly valuable for studying temporal patterns of algal blooms. Landsat data typically has a spatial resolution ranging from 15 to 100 metres, depending on the sensor. This makes it ideal for studying larger water bodies but less suitable for small-scale features. Landsat 8 offers the highest resolution imagery, with data going back to 2013.
Sentinel-2#
The Sentinel-2 mission provides high-resolution optical imagery with a spatial resolution as fine as 10 metres. It has 13 spectral bands, including those sensitive to chlorophyll concentrations, which is essential for algae monitoring. The relatively short revisit time (5 days with two satellites in operation) allows for more frequent monitoring, enabling researchers to capture short-term variations in algal blooms.
MODIS#
MODIS (Moderate Resolution Imaging Spectroradiometer) provides a unique blend of high temporal resolution and broad spatial coverage, with resolutions ranging from 250 metres to 1 kilometer. It captures data in 36 spectral bands, including those suitable for studying sea surface temperature and chlorophyll concentrations. This makes MODIS ideal for large-scale, long-term studies of algae distribution patterns and their correlation with environmental factors.