VHR

Satellite Imagery

Since the launch of the first commercial VHR optical satellite, we have been a leader in providing the highest quality satellite imagery in the world. Whether your project requires historical imagery from the archive, a fresh collection over your area of interest or massive amounts of data ingestion, we can guide you to the perfect solution.

Discover a new perspective

True 30cm Resolution

When you need to clearest imagery in the world

Multi- & Hyperspectral

When you need insights beyond the naked eye

Multiple Daily Revisits

When you need constant monitoring

Find all of our imagery specifications here.

Image Library

Get instant access to the most comprehensive archive of VHR satellite imagery in the world. This powerful tool lets you search and filter billions of square kilometers of imagery, create AOI shapefiles and obtain all the info you need to order imagery seamlessly.

The intuitive interface features:

  • Global imagery coverage
  • Historical imagery dating to 1999
  • millions of sq. km added daily
  • Search and filters
  • Polygon tools
  • “Quick Look” preview images*

* Images in the library are not viewed at full resolution. For full resolution image streaming, please see SecureWatch

Satellite Tasking

Put the control in your own hands. When pre-existing imagery won’t work for your project, then you can take advantage tasking a satellite to take the image you need, when you need. 

With access to dozens of orbiting satellites from both Maxar and Satellogic, our users get several opportunities every day to collect the perfect image.

Work personally with our team of experts for feasibilities studies and to specify:

  • Cloud cover thresholds
  • Off-nadir Angle
  • Priority levels
  • Collection time windows
Cone Map

Want To Try Before You Buy?

Download free samples to see the quality for yourself and how it fits into your workflow.

15 cm HD

When your organisation’s business decisions require you to identify small features on the ground, an improved visual experience is key. True 30 cm resolution imagery has long been the industry leader in clarity. Now with innovative proprietary technology from Maxar applied to native 30 cm data, 15 cm HD imagery provides the next level of detail – enhancing manual and automated feature extraction efforts from satellite imagery.

 

SecureWatch

A SecureWatch subscription gives you instant access to the best satellite imagery and geospatial data via web browser or API integration; And you don’t have to be an imagery expert or have in-house tools. SecureWatch is designed to make both fresh and archive imagery accessible to anyone who needs it, whether you’re concerned with a specific area or the entire globe.

SecureWatch Screenshot-crunched

API Data Ingestion

For our high volume users we offer flexible API ordering and data ingestion framework. The European Space Imaging ordering API is a REST based interface enabling searching and ordering of the entire European Space Imaging and Maxar imagery archive. The system allows for the production of ortho-ready standard and orthorectified imagery, according to the specifications in the product guide.

API screenshot

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Architecture of ResNet34-UNet model

UNet architecture for semantic segmentation with ResNet34 as encoder or feature extraction part. ResNet34 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of VGG16-UNet model

UNet architecture for semantic segmentation with VGG16 as the encoder or feature extractor. VGG16 is used as an encoder or feature extractor in the contracting path and the corresponding symmetric expanding path predicts the dense segmentation output.

Architecture of ResNet34-FCN model

In this model, ResNet34 is used for feature extraction and the FCN operation remains as is. The feature of ResNet architecture is exploited where just like VGG, as the number of filters double, the feature map size gets halved. This gives a similarity to VGG and ResNet architecture while supporting deeper architecture and addressing the issue of vanishing gradients while also being faster. The fully connected layer at the output of ResNet34 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

Architecture of VGG16-FCN model

In this model, VGG16 is used for feature extraction which also performs the function of an encoder. The fully connected layer of the VGG16 is not used and instead converted to fully convolutional layer by means of 1×1 convolution.

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