Satellite - Ocean Colour - MODIS - 1 day - Picoplankton fraction (OC3 model and Brewin et al 2012 algorithm)
InfoOpen data
|
Deployed on AWS
The Aqua satellite platform carries a MODIS sensor that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. An empirical relationship is then used to compute an estimate of the relative abundance of three phytoplankton size classes (micro, nano and picoplankton).
The methods used to decompose chl_oc3 are described by Brewin et al in two papers in 2010 and 2012. The two methods, denoted Brewin2010at and Brewin2012in, used calibration data from the Atlantic and Indian Oceans respectively. Users should note that these are unvalidated experimental products and they should familiarise themselves with the underlying algorithms and methodologies described in the published literature before making use of them.
The data are produced from the same data stream as the MODIS Chla_oci data set (https:/[...]
Overview
The Aqua satellite platform carries a MODIS sensor that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. An empirical relationship is then used to compute an estimate of the relative abundance of three phytoplankton size classes (micro, nano and picoplankton).
The methods used to decompose chl_oc3 are described by Brewin et al in two papers in 2010 and 2012. The two methods, denoted Brewin2010at and Brewin2012in, used calibration data from the Atlantic and Indian Oceans respectively. Users should note that these are unvalidated experimental products and they should familiarise themselves with the underlying algorithms and methodologies described in the published literature before making use of them.
The data are produced from the same data stream as the MODIS Chla_oci data set (https://catalogue-imos.aodn.org.au:443/geonetwork/srv/api/records/d7a14921-8f3f-4522-9a54-e7d1df969c8a ).
Data are provided as two files per day, one with the percentage of nanoplankton, and one for picoplankton. The percentage of microplankton is computed as the balance to 100%, that is %micro = 100 - %nano - %pico.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Cloud Optimised AODN dataset of IMOS - SRS - MODIS - 01 day - Picoplankton fraction (OC3 model and Brewin et al 2012 algorithm)
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::aodn-cloud-optimised/satellite_picoplankton_fraction_oc3_1day_aqua.zarr
- AWS region
- ap-southeast-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://aodn-cloud-optimised/satellite_picoplankton_fraction_oc3_1day_aqua.zarr/
Resources
Vendor resources
Support
Contact
FILL UP MANUALLY - CHECK DOCUMENTATION
Managed By
FILL UP MANUALLY - CHECK DOCUMENTATION
How to cite
Satellite - Ocean Colour - MODIS - 1 day - Picoplankton fraction (OC3 model and Brewin et al 2012 algorithm) was accessed on DATE from https://registry.opendata.aws/aodn_satellite_picoplankton_fraction_oc3_1day_aqua .
Similar products
Blink AMI is the ideal choice for satellite operators interested in using the AWS Ground Station virtualized ground segment. Operators can command, control and upload/download payload from own satellites in real time. Blink's support for TT&C, narrow- and wideband payload uplink and downlink (including CCSDS and DVB-S2(X) standards), as well as rich reports indispensable in AIT/AIV and operational troubleshooting make this multi-mission, versatile and flexible software modem the modem of choice for next generation of ground station operations.
Propensity model that determines the probability that a consumer watches Satellite TV the Most.
Telescope® is Affine's next-gen AI Satellite Image Segmentation solution which utilizes Computer Vision models to segment structures like buildings, land, water, and other geographical structures efficiently and with good accuracy.
G7 Bridge is a companion product for G7x IoT safety wearables. G7 Bridge connects up to five G7x IoT wearables to the Blackline Cloud through Iridium satellite and 4G communications. G7 Bridge supports both G7x lone worker and G7x personal gas detection use cases.
Leveraging advanced AI to analyze satellite data, LiveEO's Treeline solution delivers timely and actionable intelligence to protect linear infrastructures like electrical grids or rail networks against vegetation-related risks. Our solution ensures safer and more reliable operations by effectively mitigating threats, ultimately enhancing overall efficiency for our clients.