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The Ultimate Guide to Satellite Data 2020
Learn everything about Satellite Data. Understand data sources, popular use cases, and data quality.
Table of Contents
- What is Satellite Data and what to take care of when buying?
- Who uses Satellite Data and for what use cases?
- What are typical Satellite Data attributes?
- How is Satellite Data typically collected?
- How to assess the quality of Satellite Data?
- How is Satellite Data typically priced?
- What are the common challenges when buying Satellite Data?
- What to ask Satellite Data providers?
What is Satellite Data and what to take care of when buying?
Satellite data (also known as satellite imagery) provides information about Earth and other planets, gathered by spaceborne satellites in orbit around Earth. Its main use, from a business sense, is Earth Observation (EO), providing information about Earth, such as surface changes and weather changes on land, sea, and in the atmosphere. Satellite data can be used to map almost anything that occurs on Earth. Information is gathered through remote sensing technologies, such as Optical Imagery or Synthetic-Aperture Radar (SAR), which gather and transmit images and data about Earth. Earth Observation satellites have relatively low orbits to enable better image gathering.
Optical imagery gathers images of terrain and vegetation. The images produced by optical imagery are similar to how the human eye sees Earth. It also captures infrared, which is not visible to humans. But a major disadvantage of optical imagery is that it can only be utilised in sunlight. Optical imagery can be combined with laser data to give greater insights.
Radar imagery, which gathers images in radar wavelengths, can be used both day and night, in both sunny and cloudy conditions, and even in snow and rainfall. SAR systems are small instruments, which move over areas gathering information, rather than being a large, static instrument. They can cover large areas in a small amount of time. SAR uses the same pulse compression technique used in range direction.
The distance between the radar antenna and reflection points on Earth are measured and processed into images that can be read by humans and smart machines. SAR provides reliable images of both land and sea. SAR images provide satellite data which is utilised to monitor sea and land environments, and helps provide support during crises such as natural disasters.
One of the main features of satellite data is image resolution. The required resolution will depend on why the data is needed and the size of the ground area to be monitored. Image resolution is measured in pixels. One metre resolution means that overhead, looking down, each pixel on the image would represent 1m squared of the ground area.
Who uses Satellite Data and for what use cases?
Satellite Data provides opportunities for mapping and monitoring Earth’s resources, ecosystems and global events. This information can be used in many ways for scientific, administrative and business applications. Satellite data provides highly actionable data for governments, organisations and businesses and provides information, for example, on natural disasters and crime so governments and other organisations can take timely action on both large and small scales. Satellite data can be used to detect global events, changes and trends and how humans affect their environments, using both timely data and cumulative data for long-term evaluation. This has widespread applications in making decisions and implementing actions which will benefit people and their environments, including agriculture, forestry, urban development, insurance, energy, security and industry, as well as others.
The variety of uses to which satellite data can be put is huge and expanding all the time due to new and innovative technologies. It provides businesses with multiple opportunities to develop new and improved services both locally and globally. More and more businesses are employing satellite data as their next step in acquiring timely, reliable and actionable data. Radar-based satellite imagery especially is cost-effective for frequent coverage since it is not affected by cloud cover or weather conditions.
One of the big advantages of satellite data is its predictive value. A vast amount of data can be gathered and analysed and preventive measures taken based on this analysis, rather than having to rely on guesswork.
What are typical Satellite Data attributes?
Satellite Data has several typical attributes:
- Spatial resolution identifies the presence of separate objects and their properties. Similar to digital photography, higher resolution provides better image detail.
- Spectral resolution measures wavelength size and the number of intervals between wavelengths.
- Temporal resolution (the period of time in which the image was acquired) is important in satellite data since we depend on information on how events change and how these changes affect us as humans. The frequency in which satellite data is mapped is of great importance in events such as flooding, fires and other natural disasters such as earthquakes.
- Radiometric resolution records levels of brightness and contrast and is typically expressed in bits- 8-bit, 11-bit, 12-bit or 16-bit
- Geometric resolution measures how big of an area an image can record in a single pixel.
How is Satellite Data typically collected?
Satellite data is typically collected using two main imaging systems: passive or active remote sensing systems.
- Passive remote sensing uses optical and thermal sensors to collect information on the solar energy that Earth reflects and redirects into space. It can be used only during sunlit, cloudless conditions.
- Active remote sensing uses radar and lasers for microwave imaging. The satellite sends energy to Earth and measures the energy it receives back from the surface or atmosphere.
The two radar-based systems used to collect microwave imaging are:
- Real Aperture Radar (RAR)
- Synthetic-Aperture Radar (SAR)
Only active systems, especially SAR, are able to penetrate clouds and collect information even when there is no sunlight. This is important for collecting data in areas mostly covered by clouds, such as Northern Europe, South American rainforests and South-East Asia.
The methodology of collecting satellite data is as follows:
- Images are collected and downlinked to a ground station.
- The images are processed for analysis.
- The data is analysed, (combined with other data sources when required).
- Raw data images are processed and interpreted using remote sensing software into clear and reliable images. This may include lining up pixels, removing clouds and mist, polar reformatting and other processing, depending on what is required for the data’s end use. The satellite data is then compared with other data sources, such as spatial data for quality evaluation and verification. Machine Learning (ML) software analysing provides significant insights on changes in a fast and effective process that allows organisations and businesses to create models to format predictions on upcoming events.
- Some satellite data is freely available to the public. Satellite data providers also sell satellite images and data. Satellite data can be commissioned, for example, to provide a continuous stream of data about a particular area.
How to assess the quality of Satellite Data?
In assessing the quality of satellite data there are several things it is important to consider, such as:
Radiometric noise corrupts images. The quantity of radiometric noise should be measured, using a signal to noise ratio (SNR)
Resolution of images.
The requirements differ depending on whether the satellite data are radar images or optical
- For radar imagery, spatial resolution from 5-100 metres is classified as high, with anything less than 5 metres classified as very high.
- For optical imagery 10-80 is considered medium, less than 10 metres classed a s high and anything below 1 metre classed as very high.
It is important to ensure that image resolution is sufficiently clear and detailed for your requirements.
- Temporal resolution (the period when the image was acquired).
Timely images are important in many instances and businesses should check how often images are updated. This can be daily, and in some cases as often as every three hours. The temporal resolution required will depend on the end needs for your business.
How is Satellite Data typically priced?
Satellite data may be purchased in several ways, the three most typical being:
- Satellite data purchased directly as raw data and run through smart analytical systems to interpret the data.
- Satallite data purchased from data providers as a data list, without customization.
- Satallite data purchased as customized data, customized to your specific data needs.
Providers’ prices may vary depending on your business needs and the specific equipment and training involved.
What are the common challenges when buying Satellite Data?
There are several challenges to be considered when buying satellite data, such as:
- Spatial resolution — which is limited by diffraction, aberrations, imperfect focus and atmospheric distortion. These all have to allowed for when analysing satellite data. Many companies are working on improving spatial resolution.
- Data bandwidth — only a limited amount of data can be transmitted during a time period. This limits spectral capabilities to the four common visible and near-infrared bands (red, green, blue and near infrared).
- Satellite degradation — satellite images deteriorate over time
- Nadir angle — a satellite image from the wrong angle will affect the resolution and usefulness of the data. Some providers allow requests for images to be taken from a particular angle, although this may come with an additional cost.
Improved resolution, improved radio hardware and improved satellite lifetime are all challenges facing satellite data provision today. Many companies are working on resolutions to these challenges and rapid progress is expected in these areas.
What to ask Satellite Data providers?
There are several questions that businesses may want to ask satellite data providers, such as:
- How reliable is the data?
- What is the spatial resolution?
- How often are images updated?
- What areas on earth can be covered in the images?
- Will it integrate with my existing business systems?
- What training is required for my team to utilise it?
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