Author: merriebethneely

Register today for UNESCO Frontiers in Global Water Science Webinar Series January 30th!

Join UNESCO for the first webinar in this series: “Water Quality and the Global Goals for Sustainability” by Dr. Joseph Alcamo, University of Sussex (UK)

UNESCO is pleased to announce the launch of our Monthly Webinar Series commemorating the UNESCO Intergovernmental Hydrological Programme’s 50th anniversary and 60 years of water sciences at UNESCO.

This comprehensive series, “Frontiers of Global Water Science,” brings together distinguished experts from the UNESCO Water Family and their international partners for in-depth discussions on critical water challenges and innovations.

Join the webinar on 30 January, 2025 from 13:00 to 14:00 (CET) featuring Dr. Joseph Alcamo (University of Sussex) on “Water Quality and the Global Goals for Sustainability.” Using the WorldQual model, Prof. Alcamo will present findings on river pollution across three continents, showing how bacterial contamination affects one-third of river-kilometers and impacts public health. He will also explore ecological solutions and management approaches for developing countries, highlighting science’s role in addressing these challenges.

Joseph Alcamo is Professor of Environmental Systems Science at the University of Sussex and Director of the Sussex Sustainability Research Programme (SSRP). His extensive experience in environmental systems science and dedication to sustainable development make him an ideal speaker to kick off our series. The presentation will be followed by a 15-minute Q&A session where participants can engage directly with Prof. Alcamo.

Throughout 2025, these monthly webinars will promote knowledge exchange and strengthen collaborations within our global water science community.

Register for the first webinar here:https://unesco-org.zoom.us/webinar/register/WN_1puvdSGVTo6L3JJIBaJfTA

The complete programme schedule will be available shortly on the UNESCO IHP website.  Join UNESCO in advancing water science for sustainable development.

RAdCor is here! adjacency effects atmospheric correction….

RAdCor, a new atmospheric correction module that accounts for adjacency is now available in ACOLITE

Ghent, Belgium, January 21, 2025
Content provided by the RAdCor consortium.

The latest release of the free and open-source ACOLITE software, 20250114.0, includes a new atmospheric correction processor that accounts for atmospheric blurring, i.e. the adjacency effect. The new processor, RAdCor, was developed by Alexandre Castagna and Quinten Vanhellemont in a two year STEREO project funded by the Belgian Science Policy Office (BELSPO), and is described in an upcoming paper. This new processor further expands the capabilities of ACOLITE, which includes several processors for optical and thermal satellite imagery.

Figure 1 – Overview of the new processor available in ACOLITE.

 

RAdCor is a generalisation of the standard ACOLITE processor for optical imagery, and is applicable for heterogeneous surfaces under turbid atmospheres, conditions where atmospheric blurring can become problematic. The standard processor estimates the aerosol properties with the Dark Spectrum Fitting (DSF) method, and calculates the surface reflectance with the measurement equation for the sensor signal over homogeneous surfaces that was first described by Van de Hulst in the 1940s. The DSF generalises the NIR or SWIR dark pixel approach to estimate aerosol properties, and requires no assumption on the spectral signature of surface targets nor the presence of specific sensor wavebands.

Figure 2 – Example application of TSDSF+RAdCor to a MSI/Sentinel-2B image over the Spuikom lagoon in Ostend, Belgium. The RGB colour composite shows a 5 km x 5 km image centred on an in situ reference station (red cross). The spectral plot shows the in situ measurement, the reflectance at the sensor (ρt), and the reflectances at the surface (ρs) estimated with DSF and with TSDSF+RAdCor. More information about this example can be found here.

 

Over heterogeneous surfaces overlaid by a turbid atmosphere, the Van de Hulst equation is not an appropriate descriptor of the observed signal. It cannot account for the blurring caused by (1) the downward diffuse reflection, or the spherical albedo of the atmosphere, and (2) the upward diffuse transmittance of the atmosphere. These processes introduce a signal from surrounding areas to the signal observed over a given location. RAdCor restates the measurement equation for the observed signal over heterogeneous surfaces, providing a mathematically flexible and computationally efficient solution for the surface reflectance, regardless of atmospheric blurring.

Figure 3 – The cumulative distribution function (CDF) of the (nadir) atmospheric diffuse Point Spread Function (PSF) and Spatially-resolved Spherical Albedo (SAF) as a function of radial distance from a pixel position. The burring arises from the fractional contribution from surrounding areas described by these functions.

 

As a physics-based approach, RAdCor must be provided with the appropriate transmittance and reflectance quantities that ultimately depend on the aerosol properties. Despite the flexibility of DSF, it was developed with the homogeneous surface framework and its core assumptions are not valid under significant atmospheric blurring: (1) the darkest pixel at the top of the atmosphere for a given waveband might not be the darkest pixel at the surface; and (2) a part of the signal over the darkest pixel arises from diffuse transmittance from surrounding areas, not only from the atmospheric path reflectance. We generalised the DSF, as the TOA-surface Dark Spectrum Fitting (TSDSF) method, keeping its sensor-generic properties, but removing these two limitations that occur under atmospheric blurring. This estimation requires no image iteration, resulting in a computational efficient module.

Figure 4 – Example application of TSDSF+RAdCor to a OLI/Landsat 8 image over the Donkmeer lake in Berlare, Belgium. The RGB composite shows a 5 km x 5 km image centred on an in situ reference station (red cross). The spectral plot shows the in situ measurement, the reflectance at the sensor (ρt), and the reflectances at the surface (ρs) estimated with DSF and with TSDSF+RAdCor. Note that the panchromatic waveband (centred at around 592 nm) is included in ACOLITE processing.

 

RAdCor can be run using aerosol properties estimates from TSDSF, directly derived from the imagery, or from external sources. RAdCor can also be used in optimisation mode, if a reference spectrum for a target in the scene is available. In this case, an image iteration is performed to find the aerosol properties that minimise the difference between the sensor estimate and the reference spectrum. While this approach is less computationally efficient than TSDSF+RAdCor, it provides a robust correction option, with optimal aerosol properties.

Figure 5 – Example application of TSDSF+RAdCor to MSI/Sentinel-2 imagery over an area with banana plantations in Costa Rica. Both images show the ratio of the surface reflectances retrieved in the homogeneous (hom) and heterogeneous (het) surface framework. The ratios indicate the over or underestimation when using the homogenous framework. The left image shows the ratio for the red waveband (665 nm) and the right image shows the ratio for a NIR waveband (864 nm). More information about this example can be found here.

 

The current version supports multispectral nadir-viewing sensors from the Landsat, Sentinel-2, and PlanetScope constellations. Check out the ACOLITE user manual for installation and use instructions, and the ACOLITE user forum for support, questions and feedback. The RAdCor website contains further demonstrations and analysis in blog posts.

Ocean Color Remote Sensing Specialist Opportunity – USA (US citizens only)


IBSS is hiring an Ocean Color Remote Sensing Specialist (#25-00280) to work with a team of NOAA and NASA scientists to develop an accurate coastal chlorophyll product. The position will be stationed at the Northeast Fisheries Science Center in the Ecosystem Dynamics and Assessment Branch, but will require working with all NOAA Fisheries Science Centers. The remote sensing specialist will compile and collect in situ optical and pigment measurements and help develop operational ocean color products relevant for fisheries science and ecosystem based management.

We would appreciate you sharing this posting with potential candidates who have expertise in ocean color remotesensing, data management, and algorithm development. A strong candidate will also have good coding and communication skills, and be expected to work closely with the development team to complete the project on time.

If you have any questions, please contact Lacey Bluemel ( lacey.bluemel@ibsscorp.com).