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Machine Learning – ML

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Machine Learning (ML) and Remote Sensing Technology

Machine Learning (ML) and remote sensing technology aids in many applications requiring large amounts of spectral and spatial data needed for pattern recognition. ML uses algorithms through computer systems, computer vision, and deep learning methods to collect and identify features in an environment with precise accuracy and speed. ML a subdivision of Artificial Intelligence (AI) and Computer Vision (CV) can help the end-user to understand the data collected in order to find resolutions for remote sensing data and improve the overall accuracy of the data classification and can enhance the reliability and assessment of the features of data collected. ML algorithms through neural networks can improve the analysis of large areas to classify objects, identify temporal change, data fusion, cloud removal, and spectral analysis from satellite or aerial imagery that will overcome challenges of remote sensing data.

WorldView-3 Satellite Image of Caribou Herd Migration – North Slope of Alaska (30cm)

Click image to view animation

Copyright © MAXAR/processed by Satellite Imaging Corporation. All Rights Reserved.

Images collected by satellites or unmanned aerial vehicles (UAV) by applying ML techniques, these models can provide near real-time reports for areas with complex feature distribution such as in the applications of environmental monitoring and management, mineral mapping, agriculture, disaster management, climate change, and wildlife conservation.

ML for Environmental Monitoring

Using standard VNIR/SWIR and Hyperspectral Satellite sensors, SIC can provide data with advanced spectral resolution and capabilities to detect carbon (CO2) and methane (CH4) emissions and monitor  changes over time. Machine learning (ML) algorithms have proven to be a powerful tool to acquire remote sensing data at high processing speeds for applications involving environmental studies, land change detection, land use, agriculture, energy, climate change, and forestry.

ML for Habitat Mapping & Monitoring

Remote sensing, ML, and GIS, have greatly expanded opportunities for data collection, integration, analysis, and modeling for wildlife monitoring and assessment. High-resolution satellite images give scientists and researchers increasingly up-to-date geospatial and spectral data at high processing speeds through neural networks. Reliable statistics are obtained for monitoring wildlife migrations, habitat mapping, and tracking endangered species in remote areas of the world in order to assist with habitat mapping, wildlife monitoring, and wildlife conservation activities.

Spectral and spatial data are collected for wildlife monitoring and management by utilizing neural networks algorithms by acquiring data and statistics to obtain accurate and precise data for conservation projects. Remote sensing data and ML can provide data and features in support of habitat mapping, migrations, illegal activities, and monitoring changes in forest cover. This method allows scientists, researchers, and conservationists to collect and analyze data in a time-sensitive series that can allow estimated rates and patterns of remote wildlife areas.

Consultancy

Ongoing remote sensing and GIS mapping consultancy services are provided to our clients, including the set-up of reliable source coordinate databases in support of computerized mapping, exploration, and development of projects around the world and to clients implementing AI, CV and GIS management systems, utilizing a variety of source data. For more information or for a consultation, please contact us.

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TESTIMONIALS

Stories & Experiences

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FAQ’S

Frequently Asked Questions

How to find Geographic Coordinates in Google maps?

To find geographic coordinates in Google Maps, you can follow these steps:

  1. Open Google Maps in your web browser or on your mobile device.

  2. Search for the location you want to find the geographic coordinates for by entering the address, landmark, or name of the place in the search bar at the top of the page.

  3. Once the location is displayed on the map, right-click (or long-press on mobile) the exact point on the map where you want to find the coordinates. This will open a small menu.

  4. In the menu that appears, click on “What’s here?” or “What’s here? – Coordinates” option. On mobile devices, you may need to tap on the location marker first to reveal the menu options.

  5. A small information box will appear at the bottom of the screen, displaying the latitude and longitude coordinates of the selected point. The coordinates will be shown in decimal degrees format.

  6. You can click on the coordinates in the information box to expand it and see the coordinates in different formats, such as degrees, minutes, and seconds (DMS) or Universal Transverse Mercator (UTM) format.

To create a KML (Keyhole Markup Language) file in Google Earth, you can follow these steps:

  1. Download Google Earth Pro and Open on your computer.

  2. Navigate to the location or area you want to create a KML file for by using the search bar, zooming in/out, and panning on the map.

  3. Customize the view and layers in Google Earth Pro to include the specific data or elements you want to include in your KML file. This can include placemarks, paths, polygons, overlays, images, and more.

  4. Once you have set up the desired view and layers, go to the “Add” menu at the top of the screen and select the type of element you want to add (e.g., placemark, path, polygon, image overlay).

  5. Follow the prompts to add the specific element and provide the necessary information, such as location coordinates, name, description, and any additional properties or styling options.

  6. Repeat the previous step if you want to add more elements to your KML file.

  7. After adding all the desired elements, go to the “File” menu and select “Save Place As.”

  8. In the “Save Place As” dialog box, choose a location on your computer where you want to save the KML file.

  9. Specify the name of the KML file, ensuring it has the .kml extension (e.g., myfile.kmL), you may need to select KML as GoogleEarth defaults to KMZ formats.

  10.  Click the “Save” button to save the KMZ file to the specified location on your computer.

Ordering commercial high-resolution and medium-resolution satellite maps process:

  1. Identify your requirements: Determine the specific needs for the satellite maps, including the desired resolution, geographic coverage, acquisition date, and any additional specifications such as spectral bands or cloud cover constraints.

  2. Contact Us: Reach out to us to inquire about our imaging product and services. Provide us with the details of your requirements, including the area of interest, resolution, and any other specifications.

  3. If there is high urgency for imagery, please let us know that this is a time sensitive project. Any project deadlines should be included with your initial contact.

  4. Request a quote: Ask for a formal quote for the satellite maps you need. The quote should include information such as the cost, delivery timeline, licensing terms, and any additional services like data processing or analysis.

  5. Review the quote: Evaluate the quote provided by us and if needed, we can negotiate the terms, pricing, or any specific requirements that may not be fully covered.

  6. Confirm the order: Once you are satisfied with the quote and have reached an agreement, confirm your order. We will guide you through the necessary steps for payment and delivery.

  7. Receive the satellite maps: After the order is confirmed and payment is processed, you will receive the satellite map data in the specified format. This may include downloading the data from a secure portal or receiving physical media, depending on delivery method.

  8. Utilize the satellite maps: With the satellite maps that you receive, you can utilize it for your intended purposes, such as GIS data, 3D terrain maps, disaster, geospatial data, and other applications as needed.

Satellite map raw files refer to the unprocessed and unedited data captured by satellite sensors. These files contain the raw data received by the satellite sensors, including the reflected or emitted electromagnetic radiation from the Earth’s surface.

Satellite map raw files typically come in specialized formats specific to each satellite sensor or provider. These formats may include formats like GeoTIFF (georeferenced Tagged Image File Format) or ENVI (Environment for Visualizing Images). The raw files preserve the original sensor readings, which can include various spectral bands, radiometric information, and geometric parameters.

Raw files require processing to convert them into usable formats, such as georeferenced images or digital elevation model(DEM). Processing steps may involve radiometric and geometric corrections, atmospheric compensation, calibration, orthorectification, and mosaicking, among others.

Once processed, raw files can provide valuable information for various GIS data applications, including 3D terrain maps, agriculture production maps, vegetation maps, and disaster maps.

To download satellite maps from an FTP (File Transfer Protocol) server, you can follow these general steps:

  1. Obtain the FTP server information: Get the FTP server details from the satellite maps provider or the source you are accessing. This includes the FTP server address, username, password, and potentially the directory path to the imagery files.

  2. Choose an FTP client: Select an FTP client software or application that allows you to connect to the FTP server and perform file transfers. Some popular options include FileZilla, WinSCP, Cyberduck, or the built-in FTP functionality of certain web browsers.

  3. If you are unable to download an FTP client due to software locks, Windows has a built in FTP Protocol that can be accessed by copying the URL of the FTP server in your Windows File Explorer.

  4. Depending on the method to connect to the FTP, you will need credentials including a Username and Password to access these file.

  5. Most FTP clients will allow you to Copy and Paste or Drag and Drop the files from the client window to your local files.

Remember to comply with any terms and conditions associated with the satellite map data, including usage restrictions, licensing agreements, and any attribution requirements specified by the provider.

For any other questions or for a consultation, please contact us.

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