Monitoring tidal areas from space using polarimetric radar


In this novel research, we want to improve the management and protection of salt marshes by using satellite and drone images and data.

Salt marshes and coastal grassland areas are ecologically and economically valuable ecosystems. They support a wide range of biodiversity including a rich invertebrate community and important wading birds and waterfowl. They also play an important role in carbon sequestration, act as nursery grounds for economically important fish and reduce the impact of storms on coastal defences. Yet, coastal wetlands are under threat from climate change and increasing human pressure [Gedan et al. 2009].

The main causes of salt marsh degradation are anthropogenic (e.g. pollution, agriculture, infrastructure) and related to climate change (e.g. the increase in storm frequency and magnitude). One way to make sure our marshes are properly protected and to monitor the rate of change is by carrying out periodic surveys as an early warning system. Ground surveys of coastal wetlands is very time demanding due to the uneven and often inaccessible terrain (presence of creeks, ponds and mud). Additionally, many features are more easily visible from above (e.g. drainage pattern). Low-cost methodologies able to provide periodic and inexpensive surveys of marshes would therefore benefit coastal scientists and land managers.

We want to demonstrate that satellite remote sensing could be the key. In this project we will use a combination of drone data and satellite Synthetic Aperture Radar (SAR). SAR uses microwaves to obtain images of the environment from space. It allows acquisition of images independent of weather condition and solar illumination which is very valuable in areas with frequent cloud cover. We will also use a cutting edge technology exploiting polarimetry (PolSAR). The advantage of PolSAR is that we can use the polarisation of the radar echo to obtain more images and therefore more information about objects in the scene [ESA-PolSAR].

A strong motivation for using satellite images is that we entered a new era of freely available satellite data (e.g. the ESA Sentinel constellation missions [ESA-Sentinel]). We are experiencing a rapid growth of activities in the Space industry and the Earth Observation sector. These opportunities do not just support commercial activities but also provide more efficient tools to the environmental management community.

The objective of this project is to use satellite images to extract biophysical information about the coastal habitats and evaluate how these changed in the last decade. The development work will be accompanied by large fieldwork and drone activities with monthly visits to field sites. One of the aims of this project is to understand the minimum number of drone surveys required to corroborate satellite data.

We will focus on two tidal areas in Scotland where salt marshes are present. The first is the Solway Firth, which hosts one of the biggest salt marshes in the UK and it has experienced large changes in the last decades. However, models predict a large loss of marsh by 2050 ( The second is Skinflats, which represents a much smaller marsh that is subject to an ongoing salt marsh restoration project. These two marshes will allow us to develop methodologies that could be applied to weekly monitor grasses and erosion of tidal areas in the UK.

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Image Captions

Figure 1: Analysing changes in Flookbourg (near Maracombe bay). The left image was acquired on the 1st of April 2007, the right image on the14th May 2007. The colours are related to the characteristics of the objects. Near the coast, we identified changes to the vegetation (crops growing), and the mud flat edge. ALOS-1 data 2007 (data provide by JAXA, id.1151).


Project objective: We want to use PolSAR combined with intermittent drone campaigns to monitor erosion, grass phenology and plant stress in marshes.

Deliverables: In this project, we will set up a series of methodologies that utilises images acquired from space and will be able to provide weekly update of coastal habitat conditions to local conservation authorities. We are also interested in monitoring the following events: erosion due to storms, biophysical parameters of grasses (e.g. biomass), phenology (e.g. length of the vegetative stage) and how all these varied in the last decade. An expected output of this activity will be the capability to derive accurate erosion maps.

Novelty: PolSAR is a cutting edge technology and is very useful to retrieve biophysical parameters of vegetation [ESA-PolSAR]. However, this technology has never being used for marshes and coastal grasslands. The research work carried out in this project has the potential to revolutionise the sector and allow surveying coastal areas with an unprecedented repetition time.

Data (satellite): Archive PolSAR data are already available. Future acquisitions will be carried out synchronised to fieldwork. The datasets used will include the following satellite missions: ALOS-1 and ALOS-2 (Japanese Space Agency); RADARSAT-2 (Canadian Space Agency); COSMO-SkyMED (Italian Space Agency); Sentinel-1 (European Space Agency).

Data (drone): Beside radar data we will collect drone aerial photography in the Solway Firth and Skinflats. Two drones will be available: DJI Phantom 4 and DJI Mavic. We will also collect camera pictures of the vegetated areas at ground level.

Algorithm development: In this project we will develop algorithms that exploit weekly available PolSAR images combined with sporadic very high resolution drone images to improve management practices of coastal areas.

1) We will monitor changes, such as erosion or plant phenology, by applying change detectors. One of the methodologies will be based on the use of optimisations of polarimetric data [Marino et al 2014]. Figure 1 shows an example of the algorithm output applied to ALOS-1 data over Flookbourg in 2007 (near Maracombe bay, UK). This activity will allow to derive accurate erosion maps.
2) We will use scattering models to retrieve biophysical parameters of marshes and grasslands. The model will probably be semi-empirical and it will use some background physical model to decompose the received radar echo into a ground and a vegetation components. We will start from some simpler vegetation model as in Attema at al (1979) and then proceed to design a better model especially tailored for grasslands in tidal areas. One output will be the biomass of grass. The expected output is the capability to derive grass information as biomass, height or density.
3) Analysis of time series. This will allow to evaluate trends in biophysical parameters of grasses and identifying erosion. This information will be used to assess the changes that the Solway Firth and the Skinflats suffered in the last decades and try to predict the future of coastal ecosystems. One output will be the identification of changes in phenological stages.

Fieldwork: The Solway Firth and Skinflats will be periodically surveyed. We expect on average one fieldwork a month. During these visits we will carry out drone surveys when these are not disturbing wildlife (e.g. arrival of barnacle geese in winter). Drone data will be used to have a qualitative overall evaluation of the plant phenology and a quantitative assessment of erosion. Additionally, we will use photographs to collect plant information and to identify and validate erosion.

End Users: this project has strong links with end users including the Solway Firth Partnership, Natural Scotland and RSPB Scotland. We will be in frequent contact with our partners. We will take advantage of their local experience to tailor methodologies in order to retrieve the most usefulness biophysical parameters for management and protection of marshes. We will freely distribute our methodologies to partner and the general public, with the aim of producing some tangible change in practices. We will be involved in outreach events in the Solway Firth

Project Timeline

Year 1

Preparing a literature review on the topics: SAR, marsh and grasses ecology. Fieldwork. Start working on classifying coastal areas with PolSAR and drones. Attending international training events. Expected submission of a journal paper on monitoring erosion with PolSAR and drone data.

Year 2

Develop a scattering model to retrieve biophysical parameters. Expected submission of a journal paper on retrieving biophysical parameters with PolSAR and drone data.

Year 3

Processing historical data. Use the model to evaluate trends in the occurrence of phenological stages (e.g. vegetative stage getting longer or shorter). Try to relate this to climate changes and/or oceanography. Starting writing the thesis chapters. Expected submission of journal paper on temporal trends and phenology. Conference attendance to present interim results.

Year 3.5

Complete thesis, submission and viva.

& Skills

This is a multi-disciplinary project including topics related to (a) satellite Earth Observation; (b) drone surveys; (c) physical models (electromagnetic scattering); (d) data analysis; (e) coastal areas, marshes and grassland; (f) programing.
The successful candidate will have the opportunity to gain valuable skills in the context of: (a) analysing and processing satellite images using Python; (b) planning and accomplishing drone campaigns; (c) developing analytical and empirical models to measure biophysical parameters or the environment; (d) using Geographical Information Systems (GIS) software.
The training will also include the attendance of a major international training events as the Training on polarimetric SAR data, provide by ESA in Frascati, Italy.
Development here will be supported through IAPETUS specific provision and external courses.

References & further reading

[Gedan et al. 2009]: Gedan KB, Silliman BR, Bertness MD (2009) Centuries of Human-Driven Change in Salt Marsh Ecosystems. Annual Review of Marine Science, 1, 117-141[ESA-PolSAR]:[ESA-Sentinel]:[Marino et al 2014]: Marino, Armando and Hajnsek, Irena (2014). A change detector based on an optimization with polarimetric SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 52(8) pp. 4781-4798.[Attema et al 1978]: Attema E. P., Fawwaz W. and Ulaby W. (1978) Vegetation modeled as a water cloud. Radio Science (AGU), 13 (2).

Further Information

For further information on the project please contact Dr. Armando Marino,

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