Map of the Month for July from Teagasc presents an interim output from a remote sensing study looking to see how often fields are bare of vegetation, due to harvesting or re-seeding. Using the Teagasc archive of satellite imagery going back to the 1980’s we can use vegetation indices to give an indication the number of times a every field in the country has been bare. This will be a useful baseline dataset in many applications like GHG accounting, biodiversity, and landuse studies.
We’ve had a few days of summer storms and lightning strikes leading to blackouts and animal deaths. If you want see where lightning is happening here and now, then real-time lightning detection has the answer. The detectors measure Very Low Frequency radio waves and triangulate bursts to locate lightning strikes. Met Eireann feeds data (from the valentia island observatory) into a system run by UK met office and shows the results on its landing page map every 15 mins. My favorite site is lightningmaps.org which is a service run by volunteers and hobbyists across the world. You can follow lightning storms as they happen and it has audio to mimic strikes in the area you are looking at.
The current Teagasc Map of the month creates a Normalized Difference Moisture Index for May form MODIS data and compares it with a decadal May average to show which parts of the country are plants under stress due to drought.
FG IV – Scientific Project Officer – Land and Soil
The Soil Unit in the JRC in Italy is looking for a a project offcier (3 year contract) From the PANAGOS newsletter:
The position will support the implementation of the European Land and Soil Observatory through the development of an EU-wide land degradation and restoration assessment, reflecting the global approach adopted by the IPBES. This should include a detailed European Land Degradation map, an underpinning database and a detailed analysis of the land restoration potential in the EU. Candidates must possess an undergraduate degree in soil science, earth sciences, environmental sciences or agricultural sciences, together with at least 5 years Job-Related experience on modelling or geostatistical analysis of soil condition or land degradation processes. A post-graduate qualification in a related field, contributions to national-continental-global land or soil degradation assessments, experience of working with large spatial datasets (including EO data) or in the implementation of land or soil restoration techniques, would be an advantage. Deadline: 25.5.2020 Apply: https://recruitment.jrc.ec.europa.eu/ (code 2020-IPR-D3-FGIV-014171)
Great Idea from Copernicus, a competition for new ideas looking at the impacts that COVID crisis has had on certain sectors:
European Space Agency (ESA), in coordination with the European Commission, is launching a special edition of the Custom Script Contest, focused on the support of space assets during the COVID-19 crisis, managed by Euro Data Cube group. Following a similar format, but further to looking for new algorithms, we are in the quest for ideas on how satellite data could help monitor and mitigate the situation for the upcoming months, while the world will organize to get back to business and will need to adapt from this crisis.
This is not just “make work”- the impact of COVID is so severe and rapid that governments ability to understand what is happening can’t keep up. Remote Sensing approaches could give vital information about the performance of certain sectors in society before conventional statistical gathering (hampered themselves by the impact of Covid-19) can provide the needed information.
I’m the guest in the latest episode of the Teagasc Podcast series – the Research Field presented by Sean Duke.
In Teagasc we use Earth Observation technology to help us understand the status of Irish agriculture and develop tools to allow farmers to better manage their farms. Earth Observation is a branch of remote sensing, using technology like satellites and drones to measure see what’s going on in Ireland.
The satellites we use are optical (like orbiting digital cameras) and radar (which broadcast microwaves and measure how they bounce back). We can use these satellites to characterise the landscape, telling us what type of land-cover we have. They are particularly good at mapping habitats and nature. Radar and a similar technology, lidar (which uses lasers), allow us to understand the 3D world we live in, measuring the shape of the earth and objects like hedgerows.
The optical satellites work very well in helping understand the current status of field or farm and seeing how it changes or compares to the past. For grassland production, which is so important in Ireland, regular, in some cases daily observations by satellites mean we can see the grass grow. Using these images with artificial intelligence means we very reliably measure, from space the amount of grass growing in a field and the whole farm. Satellites are also very useful in seeing variation across the country at anyone time to understand the carried impacts of droughts or floods.
Across a wider landscape we can use the historical record of satellite images (going back to the 1970’s) to see how current conditions compare to normal or we can see how some land-use, like forestry, have changed over time.
One problem with using Earth Observation in Ireland is that it’s so often cloudy. Radar satellites overcome this because they can “see” through clouds but the information they relay can be difficult to interpret and be a little limited. For Ireland and Irish agriculture drones offer the solution. Modern drone are easy to fly, easy to program and can carry many different types of sensors. Drones are used to map farms to help farm planning and design, monitor crop and grass growth (especially to detect disease within a field) and they can even see underground, using thermal cameras.
The Video shows how NO2 levels have decreased this year over Italy due to the Corona Lock down.
The data was collected by the European Sentinel 5P satellite which directly measures atmospheric gases. AS well as NO2 it collects information on the concentration of gases such as SO2 and Methane.
Maynooth University are seeking an enthusiastic Data Scientist to join an exciting new research project, SOil MOisture estimates from SATellite based Earth observations (SoMoSAT), for a period of 28 months. The research, which is funded by the Environmental Protection Agency, is seeking to develop a novel data platform to ingest, analyse and fuse multi-thematic and multi-temporal earth observation data streams, including in situ data, using advanced machine learning techniques to derive high spatial resolution soil moisture estimates for Ireland. The successful candidate will be working as part of a project team, alongside Dr. Tim McCarthy and Dr. Rowan Fealy. Details HERE
23:30hrs (local Irish time) on Friday, 6th March 2020.
Please note all applications must be made via our Online Recruitment Portal at the following link:
Post Ref: 005721
Someone was asking the other day about MODIS time series. A quick way to get a ready to go time series to play with is the Fixed Site Subset tool. Its an archive of sires around the world (maybe a dozen in Ireland) with ready cut (say 10 by 10km) subsets of All Modis products in time series, usually around flux towers and so on. If you need a time series to test an algorithm or process on and are not that concerned about location – this is dead quick: