REMOTE SENSING

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Every picture has a story to tell

More data from more sources, coupled with intelligent processing, unlocks limitless opportunities enabled by IoT.

Satellite and drone data as a source of information, whether it is combined with other source of information or not, can be of inestimable value. Satellites measure the entire planet and can provide insights into changes over time. 

Drones allow people to photograph, video, map, survey and inspect a limited sized area e.g. a farm or a forest. 

Drone and satellite imagery can all provide useful information, however the value of the information is highly dependent on the quality of the imagery. Drones support a higher resolution than satellite images.

USGS/NASA Landsat-7 (2013)

SATELLITE AND DRONE REMOTE SENSING

How it works and what to expect.

The absolute basics:

Earth observation satellites are designed for applications such as monitoring and predicting climatic patterns, estimating crop yields, assessing damage during natural disasters, availability of water sources, and surface geology mapping. It works at a high altitude using remote-sensing techniques to collect data on the earth system’s chemical, physical, and biological aspects. This method also helps to manage the earth’s natural resources in a resourceful manner.

Basically it’s all about “Spectral Imaging Systems”. In Mangosat’s specific cases about drones and satellites in space tracking change on the Earth’s surface over time. Its fundamentals maybe a bit overwhelming but not that difficult to understand. The technology (indeed a kind of rocket science) behind it is of a different kind. We are just – and only – users, hence we leave the true complexity up to the experts.

At Mangosat our job is first channelizing information and discovering trends. Next is simplifying the models and creating ready to implement, easy to understand solutions which are affordable and accessible to potential users in the field. Users who are in their own bubble, not necessarily technical, and only interested in how we possibly can fix THEIR problems. 

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If you are interested in a little more detail and background than please click Landsat Satellites – a short but comprehensive tutorial on the Landsat series. Or go here: Fundamentals of Remote Sensing – tons of really good information from the Canada Centre for Mapping and Earth Observation.

What to expect from remote sensing satellites:

Remote sensing satellites orbit the earth year-round, snapping “photos” or better “images” as regularly as every week. Most commercial imagery falls between 1 and 5 meter resolution, with high resolution sensors capturing 70, 50 and 30 cm resolution. 

What about resolution

Public satellite image services may be limited to a maximum spatial resolution of 26 cm to 30 cm, which is plenty for personal use. Commercial services go beyond that, with some offering 15 cm and up for the highest resolution sensors. The update frequency for these satellite images can vary depending on their original source. Public and commercial services update their imagery database once every few days, but it differs from company to company.

Since centimeters provide the best quality and details for satellite imagery, why don’t we use the highest resolution for every situation possible?

One technicality holds us back. Equipping and deploying each satellite with robust high-resolution sensors is expensive. Aside from that, the higher the resolution, the overall file size of the images increases. Maintaining and updating large satellite image files would be a monumental task, but it wouldn’t be impossible. As this technology advances, we will likely see even higher-resolution images from public and commercial satellite image services.

Good to know is that our planet have been mapped many times over the past decades which means that you can often find historical satellite images which provide a high-level assessment.

Illustrating example: Chernobyl, Ukraine 1986-2013
A nuclear accident devastated the region near Chernobyl, Ukraine, on April 26, 1986. Farm fields are the bright green and tan shapes in the 1986 image. Those farms have converted to natural vegetation, the flat gray-green in the 2013 image.

(1) Chernobyl - April, 1986 - Landsat 5
(2) Chernobyl - July,1992 - Landsat 4
(3) Chernobyl - June, 2011 - Landsat 5
(4) Chernobyl - Aug 11, 2018 - Landsat 8
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The USGS/NASA Landsat 5 image from April 29, 1986, was the first civilian satellite image of the accident. The data from Landsat were used to help confirm that an explosion had happened at Chernobyl and that the plant had been shut down. Click here for the source.

Why satellite images have “unnatural” colours:

While humans can perceive only a small portion of the electro magnetic spectrum (visible light), satellite sensors can use other types, like infrared light, ultraviolet light, or even microwaves. When satellite and drone images are made, these invisible types of light are assigned a visible colour. That is why satellite images often have “unnatural” colours.

Note: Many types of spectroscopy can be used for spectral imaging. Remote sensing of the Earth operates in the visible and short-wave near infrared regions, whilst applications for precision agriculture are within the NIR region (780–2500 nm).

Landsat imagery courtesy of NASA/USGS

How useful are satellite images:

Satellite images are useful because different surfaces and objects can be identified by the way they react to radiation. For instance, smooth surfaces, such as roads, reflect almost all of the energy which comes at them in a single direction. This is called specular reflection. Meanwhile, rough surfaces, such as trees, reflect energy in all directions. This is called diffuse reflection. Also, objects react differently to different wavelengths of radiation. For instance, there is a frequency of infrared light which can be used to determine plant health. Healthy leaves reflect this frequency well while unhealthy ones do not.

More about spectral imaging

Spectral imaging is the detection of light reflected by an object or e.g. a crop with the use of specialized sensors. It is measured in spectral bands. The higher the number of bands the higher the accuracy, the flexibility and information content.

Currently satellites and drone fitted cameras are using multispectral imaging technology. Multispectral technology (5–7 bands) can offer a good general overview,  but fails to do so if more detail or a higher level of accuracy is required. Hyperspectral technology with its higher number of spectral bands (40+) can provide solutions for almost every problem encountered in the field.

More spectral bands result in a significantly higher information content of the data acquired. High spectral resolution of data allows for detection and identification of for example inferring biological and chemical processes in crops, which opens up a full range of applications in precision agriculture.

Technology is fascinating!

Free sources for raw satellite images:

All the free options below offer different spatial resolutions for satellite or aerial imagery, depending on its use case. So if you want to discover satellite imageries from all over the world. you’ll love this list. And also all are downloadable!

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All the paid options below offer at least a 1-meter spatial resolution for satellite or aerial imagery.

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What is the market opportunity and what are the cost for using satellite imagery:

Due to this growing demand for the availability of information, there is a global market for satellite applications that both governments and commercial parties are interested in. At the same time, both governments and a growing number of commercial parties are the suppliers of satellite data, and the quantity and quality of the available satellite data is rapidly increasing. This creates opportunities for developers and suppliers of services, but also for governments and markets to make use of the services. 

more to come

What about drones.

Drone data, be it RGB, multispectral or hyper spectral, have a higher spatial and temporal resolution than satellite data and is cheaper than manned-aircraft flights for the same data.

Drone data output depends on the sensor and processing software. Select a sensor based on your data requirements. Your sensor choice will determine the drone you need to carry this payload. 

Drone technology has revolutionized agricultural management for farmers and agronomists. Tasks such as crop mapping and spraying have undergone significant transformations with drone solutions, offering enhanced efficiency, improved worker safety, and reduced production costs. Explore three crucial steps, along with powerful drone solutions, to advance your farming missions.

The first step in an efficient agricultural operation is to have a deep understanding of what is happening in the field. That’s where drone solutions come into play. They can help guide land preparation before planting as well as precise spraying and fertilization.

After thoroughly surveying and mapping your farmland, you will have access to advanced data to guide your future operations. By using drones, you can import images captured from multiple angles and auto-generate realistic 2D and 3D models, enabling you to get detailed measurement results for all your critical projects.

After acquiring in-depth knowledge of your farmland, you can choose the correct course of action for your missions. Drones can help you ful fill your spraying and spreading needs through an incredible spray load of e.g. 40 kg and a spread load of 50 kg (70 L)/1.5 tonner of fertilizer per hour.

 

Satellites and drones compared:

Satellites are recommended to cover large amounts of spatial temporal data to identify trends but do not offer the same level of precision as other tools such as drones or sensors on the ground.

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“Instead of just seeing a plant, hyperspectral imaging can go deeper and see the chlorophyll content of the plant, or the composition of the soil.

Mangosat service offerings

Mangosat offers a total concept solution, which is the combination of image processing and on the ground IoT solutions for overall farm, tree, and on-tree fruit monitoring. The system is flexible and expandable and basically every sensor can be included. Our concept has low economic investment and is not subject to geographical restriction. Moreover, your farm can be efficiently managed from anywhere in the world.

If required we take care of electrical power, connectivity, implementation, and maintenance.

Collecting and combining data

Analysing the moment or looking backward

Detecting change and prediciting future development

Collecting and processing

Satellite data knows no boundaries. drones have a higher resolution, ground sensors are very precise. Together with our partners, we collect and combine all available data in one point for further processing.

The moment or the past

We have both near real-time and historical data available, allowing greater accuracy in monitoring. Powerful AI algorithm generate alarms, do predictions and facilitate decision making processes.

Useful and understandable

Raw data is not what we want to present to our customers and users. Our data is converted into handy dashboards or individual maps so that everyone can implement the data in his own preferred way.

What to expect?

Data package

We provide you with our data in all possible formats. CSV and TIFF files to get started right away.

Documentation

You will receive a report with explanation of our findings. Including maps and graphs for the right insights.

Accessible dashboard

Access your data anytime, anywhere. Your own online dashboard, with your own data.

Page last modified: Feb 26, 2024 @ 9:27 am