Satellite data has become a fundamental tool for understanding and monitoring our planet from a unique perspective. This data, collected by satellites in orbit around the Earth, provides a global and detailed view of various terrestrial, maritime and atmospheric phenomena that have applications in multiple sectors, such as environmental care or driving innovation in the energy sector.

In this article we will focus on a new sector: the field of fisheries, where satellite data have revolutionised the way fisheries are monitored and managed worldwide. We will review which fisheries satellite data are most commonly used to monitor fishing activity and look at possible uses, highlighting their relevance in detecting illegal activities.

The most popular fisheries-related satellite data: positioning data

Among the satellite data, we find a large amount ofpublic and open data , which are free and available in reusable formats, such as those coming from the European Copernicus programme. This data can be complemented with other data which, although also public, may have costs and restrictions on use or access. This is because obtaining and processing this data involves significant costs and requires purchasing from specialised suppliers such as ORBCOMM, exactEarth, Spire Maritime or Inmarsat. To this second type belong the data from the two most popular systems for obtaining fisheries data, namely:

1. Automatic Identification System (AIS): transmits the location, speed and direction of vessels. It was created to improve maritime safety and prevent collisions between vessels, i.e. its aim was to prevent accidents by allowing vessels to communicate their position and obtain the location of other ships in real time. However, with the release of satellite data in the 2010s, academia and authorities realised that they could improve situational awareness by providing information about ships, including their identity, course, speed and other navigational data. AIS data went on to facilitate maritime traffic management, enabling coastal authorities and traffic centres to monitor and manage the movement of vessels in their waters. This technology has revolutionised maritime navigation, providing an additional layer of safety and efficiency in maritime operations. Data is available through websites such as MarineTraffic or VesselFinder, which offer basic tracking services for free, but require a subscription for advanced features..

2. Vessel Monitoring System (VMS): designed specifically for fisheries monitoring, it provides position and movement data. It was created specifically for the monitoring and management of the modern fishing industry. Its development emerged about two decades ago as a response to the need for improved monitoring, control and surveillance of fishing activities. Access to VMS data varies according to jurisdiction and international agreements. The data are mainly used by government agencies, regional fisheries management organisations and surveillance authorities, who have restricted access and must comply with strict security and confidentiality regulations.The data are used mainly by government agencies, regional fisheries management organisations and surveillance authorities, who have restricted access and must comply with strict security and confidentiality regulations.. On the other hand, fishing companies also use VMS systems to manage their fleets and comply with local and international regulations.

Analysis of fisheries satellite data

Satellite data has proven to be particularly useful for fisheries observation, as it can provide both an overview of a marine area or fishing fleet, as well as the possibility of knowing the operational life of a single vessel. The following steps are usually followed:

1. AIS and VMS data collection.
2. Integration with other open or private sources. For example: ship registers, oceanographic data, delimitations of special economic zones or territorial waters.
3. Application of machine learning algorithms to identify behavioural patterns and fishing manoeuvres.
4. Visualisation of data on interactive maps.
5. Generation of alerts on suspicious activity (for real-time monitoring).

Use cases of fisheries satellite data

Satellite fisheries data offer cost-effective options, especially for those with limited resources to patrol their waters to continuously monitor large expanses of ocean. Among other activities, these data make possible the development of systems that allow:

1. Monitoring of compliance with fishing regulations, as satellites can track the position and movements of fishing vessels. This monitoring can be done with historical data, in order to perform an analysis of fishing activity patterns and trends. This supports long-term research and strategic analysis of the fisheries sector.

2. The detection of illegal fishing, using both historical and real-time data. By analysing unusual movement patterns or the presence of vessels in restricted areas, possible illegal, unreported and unregulated (IUU) fishing activities can be identified. IUU fishing is worth up to US$23.5 billionper year in seafood products.

3. The assessment of the fishing volume, with data on the carrying capacity of each vessel and the fish transhipments that take place both at sea and in port.

4. The identification of areas of high fishing activity and the assessment of their impact on sensitive ecosystems.

 A concrete example is work by the Overseas Development Institute (ODI), entitled "Turbid Water Fishing", which reveals how satellite data can identify vessels, determine their location, course and speed, and train algorithms, providing unprecedented insight into global fishing activities. The report is based on two sources: interviews with the heads of various private and public platforms dedicated to monitoring IUU fishing, as well as free and open resources such as Global Fishing Watch (GFW) - an organisation that is a collaboration between Oceana, SkyTruth and Google - which provides open data.

Challenges, ethical considerations and constraints in monitoring fishing activity

While these data offer great opportunities, it is important to note that they also have limitations. The study "Fishing for data: The role of private data platforms in addressing illegal, unreported and unregulated fishing and overfishing", mentions the problems of working with satellite data to combat illegal fishing, challenges that can be applied to fisheries monitoring in general:

1. The lack of a unified universal fishing vessel register. There is a lack of a single database of fishing vessels, which makes it difficult to identify vessels and their owners or operators. Vessel information is scattered across multiple sources such as classification societies, national vessel registers and regional fisheries management organisations.
2. Deficient algorithms. Algorithms used to identify fishing behaviour are sometimes unable to accurately identify fishing activity, making it difficult to identify illegal activities. For example, inferring the type of fishing gear used, target species or quantity caught from satellite data can be complex.
3. Most of this data is not free and can be costly.  The most commonly used data in this field, i.e. data from AIS and VMS systems, are of considerable cost.
4. Incomplete satellite data. Automatic Identification Systems (AIS) are mandatory only for vessels over 300 gross tonnes, which leaves out many fishing vessels. In addition, vessels can turn off their AIS transmitters to avoid surveillance.
5. The use of these tools for surveillance, monitoring and law enforcement carries risks, such as false positives and spurious correlations. In addition, over-reliance on these tools can divert enforcement efforts away from undetectable behaviour.
6. Collaboration and coordination between various private initiatives, such as Global Fishing Watch, is not as smooth as it could be. If they joined forces, they could create a more powerful data platform, but it is difficult to incentivise such collaboration between competing organisations.

The future of satellite data in fisheries

The field of satellite data is in constant evolution, with new techniques for capture and analysis improving the accuracy and utility of the information obtained. Innovations in geospatial data capture include the use of drones, LiDAR (light detection and ranging) and high-resolution photogrammetry, which complement traditional satellite data. In the field of analytics, machine learning and artificial intelligence are playing a crucial role. For example, Global Fishing Watch uses machine learning algorithms to process millions of daily messages from more than 200,000 fishing vessels, allowing a global, real-time view of their activities.

The future of satellite data is promising, with technological advances offering improvements in the resolution, frequency, volume, quality and types of data that can be collected. The miniaturisation of satellites and the development of microsatellite constellations are improving access to space and the data that can be obtained from it.

In the context of fisheries, satellite data are expected to play an increasingly important role in the sustainable management of marine resources. Combining these data with other sources of information, such as in situ sensors and oceanographic models, will allow a more holistic understanding of marine ecosystems and the human activities that affect them.

Content prepared by Miren Gutiérrez, PhD and researcher at the University of Deusto, expert in data activism, data justice, data literacy and gender disinformation. The contents and views reflected in this publication are the sole responsibility of the author.

We are currently in a context of digital transformation in which all sectors are in a process of adaptation with the aim of responding to the needs for improvement, agility and efficiency that society demands. One of the fields in which this change is most evident is the rural environment.

In the specific case of Spain, the change of paradigm is more than necessary due to aspects such as climate change or the depopulation of rural areas. The digital transformation of primary activities such as agriculture or livestock farming can contribute to solving these challenges, by attracting new professional profiles to areas with lower population density, and contribute to more efficient and sustainable crops.

Open data play an important role in solving these challenges through digital transformation, as the raw material for technological solutions that help to make better, more sustainable decisions. For this reason, we would like to tell you about the main rural environment datasets that you can find in our catalogue and reuse to implement applications and services that promote improvements in this sector.

What types of data related to the rural environment can I find in datos.gob.es?

In datos.gob.es we have a wide catalogue of data related to different sectors such as Tourism, Environment, Culture and Leisure, Economy, Transport, Health or Industry. The Rural Environment category includes different data catalogues related to Agriculture, Livestock, Fisheries and Forestry.

Currently, this category has more than 1,000 outstanding datasets. Among these datasets we can find national, as well as local and regional information. In this article, we have already talked about the datasets that the Ministry of Agriculture, Fisheries and Food made available to citizens, but there are many more in this category. Along with the ministries, the institutions that most publish this type of dataset are the Autonomous Community of the Basque Country, the Government of Catalonia and the National Institute of Statistics (INE).

Of these datasets, the following are the most important, together with the format in which they are offered:

1. At state level

• CIS. Spanish rural youth. XML, CSV, Json.
• Official INSPIRE Data and Services Catalog. Beach guide. MDB, KMZ, SHP, ASCII, XHTML.
• INE. Distribution of certified organic farming area qualified and or in conversion period. CSV, XLSx, XLS, Html, Json, PC-axis.

2. At Autonomous Community level

• Government of Catalonia. Agro-food industries in Catalonia. CSV, JSON, XML-APP, RDF-XML.
• Castilla y León Government.  Agricultural statistics (Castilla y León). CSV.
•  Government of Aragon. Agricultural regions of Aragon. CSV, XML-APP, JSON.
• Basque Government. Rural women in the Basque Autonomous Community by professional situation according to age group (%). CSV, XLS.
• Autonomous Community of Castilla-La Mancha. Agricultural training courses. XLSX, PDF.

3. A the local level

• Island Council of La Palma. Zoning and uses of the island of La Palma. HTML, CSV, JSON, GeoJSON, KML, SHP.
• Barcelona Provincial Council. Decline of the forest mass of the Maresme forests. PDF, ZIP, HTML.
• Vitoria-Gasteiz City Council. Risk of forest fires.PDF, OCTET-STREAM.
• Zaragoza City Council. Zaragoza City Hall Clean Points. GeoRSS.

The re-use of data from the agri-food, forestry and rural sectors

The reusable power of all these data sets is very valuable. They can be used to create valuable tools and services. Take the example of the Agricultural Plot Geographic Information System, SIGPAC, which "makes it possible to identify geographically the plots declared by farmers and stockbreeders, in any aid scheme related to the area cultivated or used by the livestock". This viewer was created to make it easier for farmers to submit aid applications and to monitor them. However, it should be noted that SIGPAC has also been used to develop applications and services that improve crop efficiency, such as Campogest or Cropti. Many of these applications also incorporate the data from the Register of Fertiliser Products, such as cultivAPP, which allows farmers to control the phytosanitary treatments applied in an easier way, from their own mobile device.

We can also find applications related to the forestry field, such as förecast, a tool that provides real-time data on forest stocks and allows for spatial-temporal analysis based on remote sensors and artificial intelligence. Or with a marked social character such as Plan Repuebla, a project that seeks to reactivate the rural areas of Castile and Leon.

You can see more examples of the reuse of agricultural data in the finalists of the 2019 Challenge, in our applications section or in this report.

From datos.gob.es we invite you to visit our data catalogue and discover all the datasets we have collected in the different sections.

Now that the call for the third edition of the Aporta Challenge is open, in this occasion focused on the field of education, we have talked to the winner of the 2019 edition, Mariano Nieves, who won thanks to his Optimacis solution. Mariano explained his experience and gave us some advice for this year's participants.

Full interview:

1. What does Optimacis consist of?

Optimacis is a project for the optimisation of the fresh fish market, which seeks to balance prices against monopsony situations.

The success of the project lies in the delivery of value for the three main actors in these markets:

• the fishing companies as producers
• wholesalers and hospitality companies as mediators in the delivery to the market;
• and the fish markets themselves as primary distribution centres.

The values for each actor are specific: in the case of fishermen, by means of advance knowledge of the most advantageous prices for sale; in the case of wholesalers and restaurateurs, by means of knowledge of the supply points with the greatest capacity; and in the case of fish markets, by means of advance knowledge of the expected influx into their facilities, for the internal organisation of resources.

2. What prompted you to participate in the Aporta Challenge?

Without a doubt, the institutional support of datos.gob.es is a reference in the Public Administration, given that the project has a marked character of sustainability for a group that usually requires additional resources to the exploitation.

It was not a preconceived project that came to take advantage of the call. On the contrary, the project was developed after reading the call for proposals. In all honesty, I even asked a formal question at the Red.es website to make sure that fishing was an area covered by the 2019 Aporta Challenge.

I thought that having the recognition and dissemination of the Aporta Challenge would boost my professional career, as it has. This is a value that I want to highlight to encourage other participants in the new call: there are currently many professionals with an impressive career, who can make their CV shine with success in the Aporta Challenge.

3. How was your experience?

The challenge was impressive. For those who know the exciting world of data, I think it is important to stress the importance of handling more than 3,500 predictive models in real time (well, with a 24-hour regeneration cycle).

This is supported by various sources of ingestion, highlighting the information from Meteogalicia and the State Agency of Meteorology, the ingestion in real time from two radar systems (actually, they are called Automatic Identification Systems) located in As Pontes de García Rodríguez and Vigo, and the daily extraction of the price data published from the Galician fish markets.

Shuffling all these sources of information in record time (with seven machines working in continuous mode 24x7), ingesting and monitoring the predictive models was a major effort for me, to which I dedicated the entire summer of 2019. And the months of September and October was dedicated to geolocation and machine learning tasks.

The main advantage that the challenge has given me has been to know sources of large masses of data that are available for projects of all kinds, with the solvency of the sources of the Public Administration.

4. What is the current status of the development of the Optimacis System?

We are already in a phase of promoting the solution, in order to coordinate with public bodies that promote sustainable projects in the field of fisheries at a state, local and regional level. The balance of the market conditions is being a factor that awakens interest in local administrations.

5. What advice would you give to participants in the Aporta 2020 Challenge?

Well, only from my partition experience of course. I think that the dedication and effort were decisive in my case, because the rest of the participants had a very high level to which I could not aspire. Most of them were groups of people, while my participation was of a personal nature. However, the fact that I was able to build this whole block of predictive models and carefully review the results was decisive.

On the other hand, I think it also helped that I took meticulous care of the presentation. The fact that I carefully wrapped the content was well appreciated, as I had a fully functional model.

6. Closing and farewell.

I want to convey all the encouragement to the participants of this call, and not hesitate to include dedication and effort because it is worth it. Not every day you receive recognition from a government institution like datos.gob.es. May the best one win!