SeaDAS (SeaWiFS Data Analysis System) is a comprehensive image analysis package developed by NASA’s Ocean Biology Processing Group (OBPG) for the processing, display, analysis, and quality control of all SeaWiFS data products. It is freely available for download.
ESA’s Sentinel Application Platform (SNAP) and the Sentinel Toolboxes – SNAP and the individual Sentinel Toolboxes also support numerous sensors other than Sentinel. For example, the Sentinel-3 Toolbox consists of a rich set of visualisation, analysis and processing tools for the exploitation of OLCI and SLSTR data from the upcoming Sentinel-3 mission. As a multi-mission remote sensing toolbox, it also supports the ESA missions Envisat (MERIS & AATSR), ERS (ATSR), SMOS as well as third party data from MODIS (Aqua and Terra), Landsat (TM), ALOS (AVNIR & PRISM) and others.
ODESA provides users with a complete Level 2 processing environment for the MERIS instrument: It includes MEGS_8.1 and associated Auxiliary Data Files (ADF) used for the MERIS 3rd reprocessing in line with the current version of the IPF (6.0).
Giovanni – Interactive Visualization and Analysis. Giovanni is a Web-based application developed by NASA GES DISC that provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Giovanni is an acronym for the GES-DISC (Goddard Earth Sciences Data and Information Services Center) Interactive Online Visualization ANd aNalysis Infrastructure.
NOAA’s Ocean Colour Viewer – The Ocean Color Viewer (OCView for short) is designed for an interactive display of various ocean color data products generated by NOAA/NESDIS/STAR Ocean Color Team from the data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite.
HYDROPT is an open-source Python framework for forward and inverse modelling of multi- and hyperspectral observations from oceans, coastal and inland waters. The remote sensing reflectance, Rrs , is calculated by specifying the inherent optical properties (IOP) of the water column, the sensor viewing geometry and solar zenith angle. Our framework is based on radiative transfer principles and is sensor agnostic allowing for Rrs to be calculated for any wavelength in the 400 – 710 nm range. Inversion of Rrs spectra is achieved by minimizing the difference between the HYDROPT forward calculations and the reflectance measured by the sensor. Different optimization routines can be selected to minimize the cost function. An extensive description of the theoretical basis of the framework as well as applications are provided in Holtrop, T., & Van Der Woerd, H. J. (2021) and Van Der Woerd, H.J. & Pasterkamp, R. (2008). Link to the software: https://github.com/tadz-io/hydropt
NASA’s Worldview – To visually explore the past and the present of this dynamic planet from a satellite’s perspective.
European Space Agency’s Ocean Colour-Climate Change Initiative – satellite observations of ocean colour, focusing on the Ocean Colour Climate Change Initiative project.
BEAM Software: The Basic ERS & Envisat (A)ATSR and Meris Toolbox (BEAM) is a collection of executable tools and an application programming interface (API) which has been developed to facilitate the utilisation, viewing and processing of ESA MERIS, (A)ATSR and ASAR data. It can be downloaded fee of charge.
WASI (Water Colour Simulator) (Version 5) is a tool for the simulation of optical properties and light field parameters of deep and shallow waters, and for data analysis of instruments disposed above the water surface and submerged in the water. You can download the installation file directly here. Examples of supported measurements are downwelling irradiance, upwelling radiance, irradiance reflectance, remote sensing reflectance, attenuation, and absorption. Data analysis is done by inverse modeling. The provided database, which covers the spectral range from 350 to 1000 nm in 1 nm intervals, can be exchanged easily to represent the studied area. The module WASI-2D extends the functionality towards image processing of atmospherically corrected data from airborne sensors and satellite instruments. WASI is free of charge. It has been developed for Windows, but can be operated also under Linux, BSD, Solaris and Mac OS X using the wine emulator (www.winehq.org). For further information contact Peter Gege at email@example.com.
SeaBatch – If you work with ocean colour data and utilize SeaDAS (see above), you likely need a way to batch process multiple files. SeaBatch can help. SeaBatch is a group of Unix shell scripts that batch process ocean colour data derived from NASA’s MODIS (Aqua and Terra) and SeaWiFS sensors. With SeaBatch you can:
- Process MODIS Level-0 files (utilize high-resolution bands)
- Process Level-1 files to Level-2
- Spatially bin Level-2 files (.5, 1, 2, 4, 9, and 36 km)
- Temporally bin Level-2 files (day, 7day, 8day, and month)
- Output Level-3 files as ascii, flat, hdf, png, etc.
SeaBatch is a powerful tool that will greatly assist you with your research. It is free, as are SeaDAS and Unix. If using runtime SeaDAS, an IDL license is not required.
ArcGIS & satellite data – Importing satellite data into ArcGIS just got easier! There is now an ArcGIS extension that allows users to browse THREDDS catalogs and connect directly to OPeNDAP servers to access large amounts of scientific data and ingest the data into ArcGIS desktop 9.3. This extension, called the Environmental Data Connector (EDC), uses a Java-based browser and leverages existing components from Unidata and NOAA/PMEL libraries so that users can filter large amounts of data in space and time. The user has a choice of importing the data into ArcGIS in either raster or feature format. The time stamped data can then be animated using a TimeSlider extension which is built into the EDC. A stand-alone version is also available, which provides a GUI to browse THREDDS catalogs or OPeNDAP directories, to subset the selected data in space and time, and to download the data as a netcdf file. The EDC was developed for NOAA Fisheries by Applied Science Associates, Inc. with funding from NOAA’s Satellite Research and Operation (R&O) project, and is freely available at www.pfeg.noaa.gov/products/EDC/. A patch that affects the handling of files within ArcGIS (not necessary for use with the standalone version of EDC) is available from the same website. For further information contact Cara Wilson at firstname.lastname@example.org.
UNESCO-Bilko: Virtual global faculty for remote sensing for learning and teaching remote sensing image analysis skills.
WIM (Windows Image Manager) is a general-purpose image display and analysis programme for various satellite images, including those from ocean colour sensors (see http://wimsoft.com). This is commercial software, but it is available for free evaluation. A major addition to the tools is the WIM Automation Module (WAM), which allows automating repetitive tasks by writing simple programs using WIM functions e.g. calculating primary production according to Behrenfeld-Falkowski model.
Software Carpentry – a volunteer project dedicated to teaching basic computing skills to researchers.
The software for the various algorithms discussed in IOCCG Report 5 can be found below. Please remember to check the relevant weblinks, or contact the authors for algorithm updates.
- Inversion of IOP based on Rrs and Remotely Retrieved Kd (Chapter 5: Inversion of IOP based on Rrs and Remotely Retrieved Kd by Hubert Loisel and Antoine Poteau). The Fortran program for the IOP inversion algorithm, as well as three look-up tables can be downloaded below.Fortran Program: IOP_inversion.f [Posted 26 February 2007]
Look-up tables: LUT_AW, LUT_KD and LUT_RRS [Posted 26 February 2007]
- Over Constrained Linear Matrix Inversion (Chapter 8: Over Constrained Linear Matrix Inversion with Statistical Selection by Emmanuel Boss and Collin Roesler). The updated code files can be found on the University of Maine, In-situ Sound & Color Lab website, or they can be downloaded below:
In situ data inversion [Posted 31 October 2006]
Synthetic data inversion [Posted 31 October 2006]
- Quasi-Analytical Algorithm (Chapter 10: Quasi-Analytical Algorithm by ZhongPing Lee, Kendall Carder and Robert Arnone)
This IOP algorithm was updated in March 2009 and November 2014. See QAA_v6_202011.pdf for a full description.
Quasi-Analytical Algorithm (QAA) Excel file [Version 6: updated November 2020].
- Garver, Siegel, Maritorena Model (GSM-01) (Chapter 11: The GSM Semi-Analytical Bio-Optical Model by Stéphane Maritorena and Dave Siegel). The updated IDL code files for this model can be downloaded at GSM 01 IDL code files [Posted 25 October 2006]
- PML algorithm by Smyth, Moore, Hirata and Aiken (2006).The PML algorithm is an IOP algorithm developed by Smyth et al. (2006) at the Plymouth Marine Laboratory, which was not available for evaluation when the IOCCG working group was convened. PML algorithm software . [Posted 23 February 2007]
The PML IOP model is an analytical approach for determining the spectral inherent optical properties of the ocean which uses spectral slopes, derived from field measurements, at the central wavelengths of 490 and 510 nm (or 531 for MODIS). Once the absorption and backscatter are known at these wavelengths, based on the assertion of Morel (1980), then the absorption and backscatter across the spectrum can be determined if you assume a spectral shape for backscatter. Once the primary inherent optical properties of total absorption and backscatter have been determined the bio-geochemical parameters can be determined using standard relationships and slopes for CDOM and phytoplankton. The reference for the model, together with its validation using the NOMAD dataset can be found in:
Smyth T. J., G. F. Moore, T. Hirata and J. Aiken (2006) Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment. Applied Optics, 45, 8116-8131.
This synthesized dataset contains both inherent optical properties (IOPs) and apparent optical properties (AOPs) for testing and comparing ocean colour algorithms. See PDF file for details of the dataset and IOCCG Report 5 for further information about the algorithms.
Please cite IOCCG Report 5 as follows if you use this dataset:
IOCCG (2006). Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications. Lee, Z.-P. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 5, IOCCG, Dartmouth, Canada.