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Inspire Helsinki 2019 HELCOM Data Challenge, Team DeepSpace
- 1. Find the best seaside vacation spot Web-based Baltic Seaside Recommendation Puzhao Zhang, Xikun Hu, Hui Zhang puzhao@kth.se; xikun@kth.se
- 3. HELCOM Data Stage1 Variables Data Source Warni ng Area Marine Litter (plastic pieces/100m， 2011-2016) Beach litter (macrolitter, large litter objects) in monitored sites Chlorophyll (ug/l) & Phosphate (umol/l) 2017 Higher chlorophyll/ Phosphate, more algae in water Contamination 2018 integrated assessment of hazardous substances Pharmaceuticals 2003 to 2014 Medicine leaching in biota/ Sediment /water Stage 2 Variables Description Fishing Herring herring relative abundance Perch Species distribution Pikeperch Species distribution Recreational Fishing the capture or attempted capture of living aquatic resources mainly for leisure and/or personal consumption Swimming Accessibility (2015) land-based travel time to the nearest densely- populated area for all areas Bathing Sites (2014) Contains information on the location and water quality of bathing sites 2014 Boating Shipping Traffic Density high-intensity shipping (lanes and fairways) and areas of low shipping activity Recreational Boating the geographical distribution of the fuel used by small boats Diving Benthic Habitat Integrated biodiversity status assessment Marine Protected Areas (MPAs) areas of high natural value Secchi Visibility of Water Zostera Marina many species and can be considered as interesting spot
- 4. Framework: Stage 1: Warning Areas consist of these contaminated area by marine litter, algae, pollution, and medicines. Warning areas will be applied as the high-level exclusion for next processing. Stage 2 is made up of four activities. • Swimming area mainly focus on the accessibility to reach the swimming spots based on the bathing sites. • Fishing points are sorted out based on the herring spatial distribution, perch and pikeperch distribution and also the recreational fishing consumption data. • Boating areas are from the recreational boating to avoid the busy shipping traffic. • Diving areas should be situated around MPAs with good benthic habitat and high visibility of water with zostera marine species.
- 5. Stage 1: Warning Areas Pharmaceuticals Eutrophication The Baltic Sea still suffers from eutrophication with excessive input of nutrients.
- 6. Stage 1: Warning Areas Contamination Marine Litter Man-made chemicals and heavy metals enter the Baltic Sea via numerous sources, including waste water treatment plants, leaching from household materials, leaching from waste deposits, and atmospheric deposition from industrial plant emissions
- 7. Stage 1: Warning Areas
- 10. Fishing Herring Abundance(2011-2016) Perch Recruitment 2011-2016 Pikeperch Recruitment 2011-2016 Recreational Fishing 2011-2016
- 11. Good Fishing
- 12. Boating Recreational Boating-2018 Shipping Traffic Density-2016
- 13. Good Boating
- 14. Diving Benthic Habitat (2018) Zostera Marina (2018) Secchi (2018) Visibility of Water Marine Protected Areas (2018)
- 15. Good Diving
- 16. Deliverable Products: WebApp https://omegazhan gpzh.users.earthen gine.app/view/web srbestseaside
- 17. Deliverable Products: WebApp https://omegazhangpzh. users.earthengine.app/v iew/websrbestseaside Good Swimming Points in Aurinkolahti, Helsinki, Finland
- 18. Find the best seaside for multiple activites
- 19. Find the best seaside with multiple activites
- 20. Deliverable Products: Recommendation Map https://www.google.com/maps/d/ u/0/viewer?mid=1YQrp5- tgAyO3oVQFUaQaHzIQeuzyO71R &ll=60.10642026702774%2C23.8 9784808363879&z=5
- 21. Deliverable Products: Recommendation Map https://www.google.com/maps/d/ u/0/viewer?mid=1YQrp5- tgAyO3oVQFUaQaHzIQeuzyO71R &ll=60.10642026702774%2C23.8 9784808363879&z=5
- 22. Discussion 1. Data sources have different geospatial formats, including Geotiff, shapfile, Geometry (Line, Point, Polygon et al). How to realize the mathematical computation based on these data is a challenge. The method we used is to upload into Google earth Engine and then convert all features into Geotiff in Stage 1. 2. Deployment methods we used here are Google Earth Engine App and Google Maps. The former can realize the internal computation framework in the Google Server. The latter is a good way to show the feature points with characteristics and embed into website. 3. The high resolution satellite images should be further involved into the beautiful seaside which can help users to target the destinations in time. For instance, EU Copernicus Sentinel-2 has a weekly temporal resolution. Based on the recommendation points, we could upgrade the information based on satellite images. Daily updated Sentinel-3 data also provides a new solution to get near-real time results around Baltic sea.
- 23. Acknowledgement 1. Great thank to HELCOM for provision of huge data sources of Baltic sea. 2. Thank National Land Survey of Finland, Ministry of Agriculture and Forestry and Joint Research Center of European Commission for technical and financial support. Special thanks to Hanna for smooth administrative communication. 3. Thanks Google Maps, Google Studio, Google Earth Engine, Airbus and Maxar for data sets and base map.
Editor's Notes
- People have flocked to the seaside for different activities and relaxation for hundreds of years. Whether you like to fish, swim, dive, sail, the seaside has been a popular place for people to spend their vacations. The Baltic Sea is a very special place with varying conditions from beach weather in the summer to ice roads in the winter. The area also contains interesting geography like the Archipelago Sea between Åland and Finland which is the largest archipelago of the world by the number of islands. With such a variety of conditions, it can be difficult to find the best location for a summer house or vacation.
- HELCOM, collects and curates a wide number of datasets describing the nature, conditions, and activities on the Baltic Sea. So now, we have many datasets. It’s a challenge that vacationers want different things: some might want clear waters to dive while others want conditions suitable for fishing. In contrast, nobody wants to be around poplution or dangerous things.
- Marine litter may affect human activities and health, reduce the value of tourism and recreation, or result in direct costs for removal. It can also damage fishing gear, contaminate catches or be a risk to navigational safety. Marine life is impacted both directly and indirectly. Litter may cause harm to animals when they ingest it
- 1) This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometer or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. 2) Contains information on the location and water quality of bathing sites 2011-2014.
- The map of herring relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016 (ICES WGBIFS reports), reported as millions of herring / ICES rectangle. Also herring landings data were used to complement the data. 2) The distribution area or perch recruitment is delineated by selecting areas where depth < 4 m (For Danish waters < 3 m), logged exposure < 5 (exposure model described in Isæus 2004), and salinity < 10 PSU 3) The pikeperch recruitment area presented on the map is mainly delineated by selecting areas where depth < 5 m, logged exposure < 5, salinity < 7 PSU, Secchi depth < 2 m and distance to deep (10m) water < 4km. The threshold values have been obtained from literature 4) Recreational fishing yearly catches of cod 2011-2016 based on the reports of ICES Working Group on Recreational Fisheries Surveys (WGRFS). Recreational fishing is the capture or attempted capture of living aquatic resources mainly for leisure and/or personal consumption. This covers active fishing methods including line, spear, and hand–gathering and passive fishing methods including nets, traps, pots, and set–lines (considered recreational in some countries).
- This dataset contains modelled small vessel fuel consumption. This describes the geographical distribution of the fuel used by small boats. The total fuel consumption was modelled in SHEBA project to study emissions from pleasure boats. The model is based on locations and berths in marinas and leisure harbours, AIS information, statistics on fuel sale and extensive survey. For 2018 version the layer is weighted with depth, log-transformed and normalised (please see below). This dataset represents the density of IMO ships operating in the Baltic Sea under the ship type "fisheries". It does not reflect the fishing effort but it shows the traffic of these ships. Density is defined as the number of ships crossing a 1 x 1km grid cell.
- This dataset represents the Integrated biodiversity status assessment for benthic habitats using the BEAT tool. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological Quality Ratios (BQR) above 0.6 correspond to good status. 2) Zostera Data quality: Mapping is not exhaustive and sampling density varies between the countries. Attribute information: Raster value representing presence (1) or absence (0) of Zostera marina. Spatial resolution: 1 km x 1 km grid (originally 5 x 5 km). 3) Marine protected areas represent areas of high natural value, it includes managed MPAs as officially reported to HELCOM by the respective Contracting State until in November 2018. 4) This indicator evaluates the eutrophication status of the Baltic Sea area based on water clarity measured by secchi depth during summer. The measured average secchi depth (in meters) is based on in-situ measurements from oceanographic monitoring data for 2011-2016 summer months (June-September).