1. Satellite observations enable global and up-to-date actionable insights;
2. Mapping and monitoring marine and coastal areas are ideal for satellite image data as big areas can be easily covered;
3. They can capture nearly any spot, including remote or hard-to-reach destinations;
4. The power lies in its ability to monitor large areas consistently and regularly;
5. They can visualize what the human eyes are not able see.

Let’s start with the basics first: we deal with Earth Observation (EO) satellites, which are distinct from other types of satellites like GPS, internet, or telescopes. EO satellites gather data while orbiting the Earth. Some of these are public satellites, where the data is made publicly available. These include satellites operated by NASA and the European Space Agency. Others are owned by commercial companies who sell access to that data.

EO satellites allow us to look back in time using archived data — meaning that we can see how ground conditions or land cover have changed over time. Many public EO satellites were launched several decades ago, so there is a long archive of historic data to explore. Those launched more recently are often able to capture higher resolution data, as well as other novel and useful information about our planet.

We weigh three main satellite data characteristics: (1) temporal; (2) spatial; and (3) spectral resolution. First, some quick definitions:

(1) Temporal resolution is the time it takes for a satellite to orbit and revisit a specific area, which determines the frequency of data captured. This could be daily, weekly or monthly, for example.

(2) Spatial resolution is the level of detail captured, like pixels on a camera, and is measured in meters. Some public satellites capture data at 10-meter resolution, while private satellites can capture sub-meter resolution (down to 30 cm for example). Imagine gradually descending from a hot air balloon. As you descend, your human eyes start recognizing features because everything is sharper. For any type of sensor, this means the spatial resolution is becoming finer.

Spatial resolution is the detail in pixels of an image. High spatial resolution means more detail and a smaller grid cell size. Whereas, lower spatial resolution means less detail and larger pixel size.

(3) Spectral resolution is the wavelengths captured by the satellite, or the range of the electromagnetic spectrum that the sensor(s) can capture. Spectral resolution describes the amount of spectral detail in a band. High spectral resolution means its bands are more narrow. Whereas low spectral resolution has broader bands covering more of the spectrum. Electromagnetic energy is observed and recorded by satellites

For example, a multispectral image breaks light into 4 to 36 bands. Then, it assigns those bands names such as red, green, blue, and near-infrared. Each band may span 50 nano-meter in the electromagnetic spectrum.

Similarly, hyperspectral imaging captures a spectrum of light. But it divides the light into hundreds of narrow spectral bands. For hyperspectral images, spectral resolution is very high.

1. Geographical distribution: Identify where each pond, cage or line is to coordinate efforts and improvements;
2. Operation type and intensity: Identify the specific aquaculture operation type and intensity level;
3. Production activity: Monitor aquaculture operations activity and track production cycles;
4. Production interruption: Tracking of aquaculture operations which had their production cycles interrupted;
5. Production forecast: Estimate production volume by using historical data and up-to-date insights;
6. Price forecast: Monitor price fluctuations based on efficiency and market insights;
7. Water environment: Monitor water environment and usage across different operations;
8. Marine pollution accidents: Identify marine pollution accidents and disasters;
9. Technology adoption: Identify the technology trends that matter, either feeders, aerators or other.

Get in touch with us to discuss more!

Through satellite observations we are able to monitor several aquatic species, both animals and plants, as: shrimp, tilapia, salmon and seaweed. Let us know your needs!

We process data from satellites with radar and optical sensors that generate value-added services. However, our users are not necessarily experts in remote sensing, so we have to be able to provide information that is as simple, integrated, and direct as possible to make the data user-friendly and helpful in decision-making processes.

Dynaspace therefore acts as a link between the volume of data that we have and our users, extracting the best information and presenting it in an immediately accessible way through our cloud-based platform, insightSPHERE. This is achieved using modern artificial intelligence-based data processing techniques developed and perfected by Dynaspace. Get in touch with us to request a demo meeting!

We offer you flexibility to choose the most optimal solution for your needs. The cost drivers are based on:

1. Subscription package (basic, standard or advanced).
2. Update frequency (weekly, monthly, quarterly or annually).
3. Size of area (farm, region, country or global).
4. Data type (historical, present or forecast).
5. Project duration.

The insightSPHERE cloud-based platform works on all computers (PCs and Macs), and on mobile on all Android and Apple smartphones and tablets.

Our team is continuously working on improvements driven by customer feedback and requests. You can expect regular releases with new, improved or updated features along with clear communications so you know exactly what is changing.

At Dynaspace, we hire people who are committed to our mission and are the best at what they do. Visit our careers page to learn more about open positions.