Satellite Imagery For

Architecture,
Engineering &
Construction

aec

Insights to build better cities

Enhance Site Selection

Utilise cutting edge data to ensure optimal infrastructure building sites

manage assets


Remotely monitor heavy equipment, supplies and building progress

Monitor Compliance

Use unhindered satellite access to keep track of every detail of construction

As the construction industry faces challenges regarding new infrastructure demands and green building initiatives, Very High Resolution (VHR) satellite imagery becomes an essential tool. Satellite imagery not only compliments and enhances traditional in situ data, but opens the door for innovative techniques in large scale project planning, monitoring and impact evaluation applications.

EU climate initiatives push construction firms to use satellite imagery for infrastructure site selection

Read about this and more satellite imagery applications in the AEC INCITE industry report, The 123 Of AEC: Renewing the Architecture, Engineering and Construction Industry with Satellite Imagery

DETAILED ANALYSIS

European Space Imaging provides the highest resolution satellite imagery commercially available. Imagery with this level of clarity allows analysts to see vehicle types, personnel activities, individual plants and building/infrastructure construction details. It’s perfect for:

  • Equipment inventory
  • Monitoring Projects
  • Small Feature Identification
  • Studying Traffic Patterns
  • Verifying Property Lines
  • Optimising on-site inspections

SITE MONITORING

Satellites have no boundaries, no boarders and no restrictions like on-site or aerial inspections. Satellites can have a permanent and programmed focus on a single location over the course of months or even years. Coupled with high enough resolution to idenitify small objects, project managers can monitor and collect data on multiple sites around the globe from a desktop.

From a compliance perspective, having detailed daily or weekly images of ground activities can be used to prove what happened and when in the case of any legal disputes.

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DIGITAL ELEVATION MODELS

The measurement and visualisation of topography and existing structures is key in the pre-construction planning phase. The ability to accurately lay out temporary facilities and heavy equipment access in tight urban as well sprawling countryside project sites can greatly reduce unknown factors and prevent delays during the construction process.

Remotely sensed Digital Elevation models and 3D renderings can achieve usable levels of accuracy for many applications and cut costs as much as 30% when compared to ground surveys.

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Download the Latest Edition of INCITE

The 123 Of AEC: Renewing the Architecture, Engineering and Construction Industry with Satellite Imagery

The definitive guide to acquiring and using satellite imagery in the AEC industry.

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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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