Location Intelligence contents
This page contains demonstration version of Location Intelligence contents.
It is just a sample of the content that a location-specific report contains.
Full report is usually between 50 to 90 pages long depending on the location type.
Here below you can see the Location Intelligence sample for Isla Canea, Spain:
Location Intelligence report is delivered through our atSEA platform in a convenient and professionally formatted PDF. The cover page contains information about who the report was generated for and the target location. See Data Coverage page for more details.
Location Intelligence Report Contents
- Units and Conventions
- Geo-administrative Overview
- Satellite Time Laps
- Elevation Maps
- Major Seismic Faults
- Climate Characteristics
(Temperature, Precipitation, Wind, Cloud & Solar)
- Sea and Ocean Characteristics (for marine and shore locations)
- Sea Ice Properties
- Sea State (Wave characteristics)
- Vessel Density (includes major inland waterways)
- Protected Areas
The report is generated for a specific geographic location (unique combination of longitude and latitude). Here, for demonstration purposes, samples of typical visualisations included in reports are presented. Several different locations are used to better highlight the breath of information available.
There is an exponential growth of available data thanks to orchestrated efforts across the world to collect and publish climate, environmental and administrative information. However, the access and transformation of such vast volumes of heterogeneous data plus extraction of actionable insights require considerable investment of time and money bringing it often beyond the rich of smaller developments and bloating the costs of bigger projects.
At Analytics Pika, we are passionate about democratization of data – meaning driving the availability of data in a form and at a price that makes it widely accessible and doesn’t require specialized expertise. We invest in finding and validating best data sources, deploy advanced data science techniques to extract actionable insights and develop visualizations agnostic to user’s educational background or digital literacy. We hope that access to quality information will help the users to make the best decisions in the fields of their expertise promoting responsible resources management.
This report has been created to enable investors, project managers and local planners to make well informed decisions maximizing the return on investment and minimizing project risk exposure. Evidence based planning ensures best possible utilization of resources, minimization of environmental impact and seamless integration within natural or built environments.
The understanding of the local climate promotes integration of renewable power generation from small local prosumers to large national level developments. It allows better choices of materials and technologies, benefiting sustainable architecture based on sound understanding of climate and environmental factors instead of reliance on subjective believes. There is a wealth of applications where fast and reliable environmental awareness for a specific geographic location brings tangible financial rewards in project planning, tendering and execution.
To cater for a broad range of applications, we designed a standardized site report, which offers commonly requested information in form of clear graphics avoiding overwhelmingly textual descriptions. If, in some unique cases higher resolution data or different representation might be required, Analytics Pika is offering custom services utilizing hundreds of data repositories worldwide. Our experienced analysts equipped with broad range of professional tools can respond fast to your unique data and analytics needs.
Dr Ilona Söchting, CEO
Analytics Pika Oy
Units and Conventions
Units are expressed using the SI convention if not stated otherwise:
- length or distance (wave height, surface elevation, water depth) in meters [m],
- time (wave periods) in seconds [s],
- speed in meters per second [m/s],
- power in Watt [W]
- energy in Joule [J]
- direction in degrees clockwise from North.
Wind, wave, sea current and sea ice directions are defined as “coming from” relative to true north positive clockwise.
Unless explicitly stated otherwise, coordinates are expressed as latitude and longitude in WGS84 coordinate reference system.
The information presented in this report is a human readable version of datasets acquired from multiple sources. The best effort is made to update all data sources regularly, but a small lag behind the releases/updates of original sources cannot be avoided. The sources of original data are always clearly stated including the release version of original data where relevant.
Analytics Pika Oy does not share, endorse, or express any opinion over the legal state or sovereignty of any country, state, entity, or territory as well as over its land borders or maritime boundaries. Analytics Pika Oy does not endorse or express any opinion about the legal state, designation, or specific boundary of any special, designated or protected area or habitat. All responsibility for the quality and accuracy of data rests with the primary sources.
The presented environmental and climate data is well suited to provide local awareness for project planning and execution, however, it has spatial and temporal resolution and quality restrictions making it unsuitable for detailed engineering design, static evaluations, navigation, or any other purpose that can compromise safety on land or at sea.
For all material included in this report and any associated digital assets package (if such is part of the sold product), Analytics Pika Oy provides no warranties of any kind whether express, implied, statutory, or otherwise. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable.
Analytics Pika Oy will not be liable to you on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of the use of the material in this report or associated digital assets package (if such is part of the sold product).
The purpose of the atSEA – Site Environmental Awareness Report is to provide fast, actionable insights covering all environmental, climate and logistical aspects at depth and quality required at the onset of investment or project planning. Such timely situational awareness is usually used for the first go/no-go and/or to design a well-informed strategy for further surveys or studies that might be required to make such decisions. The atSEA Report is also perfectly suited to accelerate and improve submission of tenders by allowing to predict probable weather losses, logistical constraints and optimize asset requirements for local climate and environment.
The type of sections contained in the atSEA Report depends on the data availability for a given location. For example, locations within EU, USA and Australia are benefitting from additional logistical information regarding protected areas. The information for some of the sections of the atSEA Report is gathered based on data processed within geographical grids which follow international standards. The grids are fixed and not centered around the selected location. The selected geographical location is associated with a given grid cell if its falls within its boundaries independent of the placement within the cell, in some cases it might be even at its very edge . Different sections of the reports are based on different data sources and consequently different grid cell sizes (as detailed in the Data Coverage & Limitations on the atSEA website), and depending on the type of environment covered by the grid cell, viable data for a given report section might not be available. In such case the section is excluded from the report. For example, some locations may have wave data available, but not ocean physics, or vice versa. In the case of locations which are shallow, where the depth is less than 5 meters, the data on waves would be highly inaccurate, and consequently is excluded from the report. Similarly, a near-shore marine location benefits from satellite time laps data which are not added for purely offshore locations. The vessel traffic density sampled from the Automated Identification System (AIS) is added for all locations because it covers inland water ways too.
The statistical distributions of conditions are represented through various types of plots, selected to best match typical use cases and properties of the data itself. Besides self-explanatory scatter and line plots, the report contains numerous boxplots, violin-plots and rose-diagrams which statistical features are explained in the examples below.
The summary of geo-administrative indicators is tabulated below. The jurisdiction or sovereignty of the area may be disputed, thus, we attempt to add the main disputing parties wherever available. To preserve best possible objectivity, the global boundaries provided by the World Bank Group and Marine Regions have been used instead of relying on any national compilation.
The area from coastal state’s baseline to 200 nm (nautical miles) adjacent to its territorial sea is its Exclusive Economic Zone (EEZ) where it has jurisdiction over exploration and exploitation of economic activities as adopted by the United Nations Conference on the Law of the Sea (1982). The area from baseline to a limit of 12 nm is its territorial sea where the state has full jurisdiction over the air space, sea waters and the seabed. The contiguous Zone of a state is the area up to 24 nm from its baseline where the state is entitled to prevent and control traffic. Further, some countries have claims to a Continental Shelf zone, extending their interest beyond the 200nm EEZ.
Major Seismic Faults
The presence of major active seismic faults nearby, indicates increased probability of medium to strong earthquakes to occur. The information shall be used to assess the need for further seismic assessment.
Satellite Time Series
The site-specific satellite imagery is presented for four points in time, distributed throughout one year to visualize site changes due to changing seasons. For each season, a set of image scales is presented (4km, 2km, 1km) capturing different geographical aspects of the location’s surroundings. The four most resent completed and processed seasons are used. The images were acquired by the Sentinel-2 satellites with 10m/pixel using a multispectral imaging camera. The different image bands are combined into true colour images presented in this report. Since clouds present an impenetrable obstruction, only images with low cloud cover (<5% of tile area contains clouds) are used. In rare circumstances when the whole season didn’t yield such image for a given location, such season will be missing from this report. The Universal Transverse Mercator (UTM) projection is used in all the visuals below, which means that the images show UTM coordinates in meters for the given utm-zone.
Elevation Models map spatial elevation data of the earth’s surface in grids. Elevation models are termed as Digital Surface Models if they represent elevation data of earth’s surface above sea levels, whereas for depths below sea level, elevation model is termed as Bathymetric model. Analytics Pika has merged elevation models from land and ocean to bring out the best attributes of each while keeping the deficiencies at bay.
The climate parameters aggregated and visualized in this report originate from hourly averaged data on covering the period from 1993 to 2021 and gridded with a horizontal resolution of 0.25o x 0.25o on a regular latitude-longitude grid. The climate parameters have been produced using 4D-Var data assimilation and model forecasts in CY41R2 of the ECMWF Integrated Forecast Systems (IFS) and further improved in reanalysis mode by combining these values with new observation values. The latency is 5 days ensuring assimilation of all relevant in-situ measurements on global scales.
Air temperature at 2m is the temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is independent of the type of the surface, thus more reliable as climate parameter. This parameter has typically units of kelvin [K] which has been shifted to Celsius [°C] scale for convenience (0°C = 273K). The diagram shows the monthly distribution of the 2m air temperature.
The 5-year average of weekly means of the air temperature represents the long-term trend, free of seasonal or year on year variations.
Summer days are days when the daily maximum temperature is above 25°C. The diagram shows the monthly distribution of the number of summer days.
Tropical nights are days when the daily minimum temperature is above 20°C. The diagram shows the monthly distribution of the number of tropical nights.
Frost days are days when the daily minimum temperature falls below 0°C. The diagram shows the number of frost days as monthly distribution.
Ice days are days where the daily maximum temperature is below 0°C. The diagram shows the number of ice days as monthly distribution.
Biologically effective degree days is the sum of daily mean temperatures above 10°C and less than 30°C calculated over a given period, in this case 1-month aggregations are shown. This index is expressed in [°C] and helps to compare the biological effectiveness between different locations or times of the year.
Dewpoint Temperature at 2m is the temperature to which the air, 2 meters above the surface of the Earth, would have to be cooled for saturation to occur. It is a measure of the humidity of the air. Combined with temperature and pressure, it is used to calculate the relative humidity.
Specific Humidity is the mount of moisture in the air divided by amount of air plus moisture at that location. The units are dimensionless but, in most cases, expressed as [kg/kg] or [g/kg].
Precipitation for the Tokyo city area, Japan.
Daily total precipitation is the sum of all hourly means of the precipitation for every given day. The diagramm shows the monthly distribution of the daily total precipitation. This is very important characteristic both for building sites and in terms of renewable energy.
The 5-year average of weekly means of the weekly total precipitation represents the long-term trend, largely free of seasonal or year on year variations.
Heavy precipitation days are days where daily total precipitation is more than 10mm. The monthly distribution of heavy precipitation days is shown in the diagram.
Very heavy precipitation days are days where daily total precipitation is more than 20mm. The monthly distribution of the number of heavy precipitation days is shown in the diagram.
Surface pressure is the atmospheric pressure on Earth’s surface (terrain and oceans). It is usually expressed in Pascal [Pa] or more conveniently [hPa].
The average value of surface pressure on Earth is 985 hPa. This contrasts with mean sea-level pressure, which involves the extrapolation of pressure to sea-level. The average pressure at mean sea-level is 1013.25 hPa.
Surface pressure for the Tokyo city area, Japan.
Wind is classified by its speed, direction, and the height from the surface of earth. The heights of 10m and 100m are used internationally as a standard to report wind speed and direction. Hourly reanalysis data have been chosen for its high temporal and spatial resolution (1hr within ca 30km grid) and highest accuracy compared to other global sources. Nevertheless, its resolution might be too low to account for extremely local wind phenomena due to steep and highly variable local elevation model.
The monthly probability of various wind speed ranges at 10 meters above ground in m/s.
Wind speed at 10m represents wind at 10m above the ground and is usually expressed in meters per second [m/s]. It is relevant to housing planning and design, plantations, and forestry. It is also the type of wind speed deciding the output of small wind turbines used in private or residential green electricity production.
The cut-in wind speed is the lowest speed limit at which most conventional wind turbines become operational and start yielding some electric output. Our research has shown that cut-in wind speed for commercially available turbines is between 2.0-4.5 m/s. The hours with wind speed below the cut-in speed should be considered as unproductive for wind energy generation. The diagram illustrates the monthly distribution of such unproductive hours assuming cut-in speed of 3 m/s.
Instantaneous wind gust at 10m is the maximum wind gust within one-hour intervals, at a height of ten metres above the surface of the Earth. The World Meteorological Organization defines a wind gust as the maximum of the wind averaged over 3 second intervals.
The wind rose for Tokyo City area is shown on the plot.
Wind speed at 100m represents wind at 100m above the ground and is usually expressed in meters per second [m/s]. It is relevant for aviation and most importantly industrial scale green electricity production using large wind turbines.
The wind rose, cut-in speed and rated wind speed plots are also available for 100m height above the ground.
The understanding of the intensity and annual distribution of solar radiation in a specific area is a prerequisite for climate-aware, sustainable architecture and integration of solar electricity and heat generation in residential and industrial developments.
The insights presented in this section are based on three decades of hourly data which is a fusion of ground and satellite measurements using physical models and have been shown in scientific literature to be the most accurate globally available data.
The data reported in global data sources are the total and direct radiation at the horizontal surface, which is considerably different to the radiation arriving on a tilted or rotated module. In this report, besides the visualisation of the horizontal values, the available solar irradiation for different tilts and orientations of modules is simulated based on available data, solar angles and well documented laws of physics. The presented values are long-term averages and represent the available insolation. They are not the output of any devices which is product specific and shall be calculated using the available insolation and manufactures guidelines.
Surface Net Solar Radiation Downward [W/m2] is the amount of solar radiation that reaches a horizontal plane at the surface of the Earth. This parameter comprises both direct and diffuse solar radiation. To a reasonably good approximation, this parameter is the model equivalent of what would be measured by a pyranometer (an instrument used for measuring solar radiation) at the surface.
Surface Solar Irradiance Downward in [W/sqm] as average hourly values for different months of the year. It represents the total horizontal irradiance (surface power density). It is the sum of the direct and diffuse radiation.
In real life applications, the collecting surfaces will be rarely mounted at the horizontal angle. To meet this challenge, Analytics Pika Oy conducted a simulation of the available solar insolation (also called irradiation) in [kWh/sqm] available for different module angles and orientations at each specific location. It is based on historic hourly data and includes location typical weather patterns. To limit the near-ground effects, it has been assumed that direct (beam) radiation can only be collected for sun’s altitude of 5 degrees or greater. The results need to be considered as average across about 30km wide grid.
The resulting on module insolation as function of the module tilt and orientation (fixed mount modules):
Sea and Ocean Characteristics
Sea and ocean characteristic refers to properties of sea such as water temperature, sea surface height, salinity and ocean currents. In this report the Global Ocean Physics Reanalysis is utilized.
Global Ocean Physics Reanalysis, GLORYS12V1 product from CMEMS, provides daily mean data gridded with a spatial resolution of 0.083o x 0.083o (ca. 9km grid sizes). Global Ocean Physics Reanalysis is based on current real-time global forecasting CMEMS system and is generated using NEMO platform coupled with ERA5 reanalysis data (fusion of in-situ and satellite measurements through physical modelling).
The diagram of the 5-year average of weekly means of the Sea Surface Height above geoid in [mm]. It is a representation of the local elevation of the ocean relative to its resting level (called the geoid), largely free of seasonal or year on year variations. Local variations in sea surface height generally reflect dynamic phenomena and structures in the ocean, such as eddies or large currents.
Sea Water Temperature at the surface is the temperature of water at about 0.4 meters depth to avoid skin effects. It is usually quoted in kelvin [K] and in this report shifted to Celsius scale [C] for convenience. The diagram illustrates the monthly distribution of the temperature.
Sea Water Temperature at the sea floor is the temperature of water at bathymetric depth. It is usually quoted in kelvin [K] and in this report shifted to Celsius scale [C] for convenience. The diagram illustrates the monthly distribution of the temperature. In addition, there is an extra plot with differential between the water temperature at the surface and sea floor.
Sea Water Temperature Differential between surface and bottom layers.
The long-term average of the water temperature. All weekly means are averaged over a 5-year period to show main climate trend.
Sea water temperature differential is shown here for Vaasa, Vasklot location in Finland.
The diagram of the 5-year average of weekly means of the salinity represents the long-term trend, largely free of seasonal or year on year variations.
Sea Water Temperature at the surface in tabulated form of monthly averages from last three decades.
Sea Water Temperature at the sea floor in tabulated form of monthly averages from last three decades.
Example of the Surface Sea Water Temperature table for location on Hawaii
Sea state refers to the condition of sea surface such as wave height, wave periods and direction including the differentiation between swell and locally wind-induced waves. To provide the best accuracy and spatial resolution, this report utilizes the Global Ocean Waves Reanalysis, Waverys product from CMEMS which provides 3 hourly data gridded with a spatial resolution of 0.2o x 0.2o . The Global Ocean Waves Reanalysis is based on MFWAM model coupled with GLORY12 physical ocean reanalysis which assimilates historic observational data.
Significant Wave Height (Hm0) is defined as four times the square root of the zeroth-order moment (area) of the wave spectrum. It is equivalent to four times the standard deviation of the surface elevation. Hm0 is very close in value (few percent difference) to significant wave height (SWH) which is defined as the mean wave height (trough to crest) of the highest third of the waves (H1/3). The significant wave height is measured in metres [m].
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell. The units are degrees defined as “coming from” relative to true north positive clockwise. Wave principal direction is the wave direction at spectral peak and was found to be a more reliable parameter than the mean wave direction, which might be strongly impacted by different wave components arriving from different directions. In terms of the direction of transport of marine debris, the Stokes drift direction is more relevant and can be systematically different to the wave direction.
Wave principal direction is the wave direction at spectral peak.
Wave Peak Period is the wave period associated with the most energetic waves in the total wave spectrum. Wind waves dominated regimes tend to have smaller peak wave periods, and regimes that are dominated by swell tend to have larger peak wave periods. It is measured in seconds (s). The density distribution of data points showing the significant wave height versus wave peak period relation.
Wind Wave Component represents the waves generated by the local wind. This parameter takes account of wind-sea waves only and is measured in metres.
Significant Wave Height of Primary Swell is a measure for the wave height for the dominant non-locally generated wave system (Swell). It is measured in metres (m). Mean direction shows from where the swells are coming from.
The monthly probability of different wave height brackets as percentage
Sea Ice Properties
This section shows site specific sea ice properties such as sea ice thickness, concentration and speed and direction of its motion. The sea ice concentration is the area of ice relative to the total area of the sea waters in the local grid cell. The sea ice thickness is modelled based on the local sea water properties and ice concentration giving an average value for the area. Consequently, localized anomalies remain unaccounted for. Multi-decade Distribution and Sea Ice Movement seed and direction plots are included in the report (where applicable).
Multi-decade distribution of sea ice concentration
Multi-decade distribution of sea ice thickness
Sea ice movement with direction it is arriving from for different velocity bins in meters per second [m/s]
Vessel Traffic Density
Shipping traffic density represents distribution of marine traffic per unit area which is based on positional data gathered from vessels’ AIS transponders. Marine traffic density offers a measure of extent of human activities in oceans and their corresponding density.
The source dataset employs AIS traffic data is from IMO-registered vessels covering mainly commercial markets such as dry and wet bulk vessels, containers, gas carriers etc. Small boats such as tugs, barges and services that don’t carry IMO registration are not the part of this dataset.
Additional plots in the report are separated by type of ships: Commercial, Fishing, Passenger or Leisure Vessels. The selected location is Vaasa in Finland.
As per IUCN, International Union for Conservation of Nature – A protected area is a clearly defined geographical space, recognised, dedicated, and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values. (IUCN Definition 2008)
Protected areas is a wide variety of conserved areas can be very sensitive to human activity. Before planning to work in these zones, the permission must be obtained from local authorities.
Protected areas is currently offered only for selected countries: United States, Australia and Europe (Albania, Austria, Bosnia and Herzegovina, Belgium, Bulgaria, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Estonia, Greece, Spain, Finland, France, Croatia, Hungary, Ireland, Iceland, Italy, Liechtenstein, Lithuania, Luxembourg, Latvia, Montenegro, North Macedonia, Malta, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Sweden, Slovenia, Slovakia, Kosovo)
Critical habitat is defined as specific areas within the geographical area occupied by the species that contain features essential to conservation of the species and, thus, may require special management considerations or protection. Also, specific areas outside the geographical area occupied by the species can be included if the area itself is essential for conservation of the given species.
The generalised product is aimed at addressing concerns regarding the release of detailed locations of species sensitive to illegal collection and disturbance while still providing public access to the distributions of threatened species. The data are not suitable for either local scale analysis or area-based calculations.
Habitat and species data is currently offered only for selected countries: United States, Australia and Europe (United Kingdom, Norway, Russian Federation, Ukraine, Belarus, Georgia, Armenia, Andorra, Albania, Bosnia and Herzegovina, Azerbaijan, Switzerland, Montenegro, Iceland, Moldova, North Macedonia, Serbia, Liechtenstein, Latvia, Austria, Germany, Lithuania, Poland, Hungary, Estonia, Slovakia, Portugal, Denmark, Slovenia, Romania, Sweden, Croatia, Cyprus, Finland, Bulgaria, Czechia, Spain, France, Greece, Italy, Luxembourg, Netherlands, Belgium, Ireland, Malta)
The content and amount of chapters in the report can vary depending on the selected location and availability of the corresponding content. Check Data Coverage page for more details.
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