Microservices
Optimized for processing Earth imagery on the cloud
Contact Sales - CATALYST Microservices
Move Processing, not data
Eliminate unnecessary data transfer costs and waste by moving your processing workflow next to your data
Move the process, not the data
CATALYST Microservices do not require installation and can be deployed on any of our cloud partner servers in seconds. This reduces costly waste in your processing pipeline by eliminating the time and fees associated with transferring and storing disk heavy earth imagery to your servers.
Limitless Scalability
Complete batch processes in a fraction of the time without incurring additional costs
Limitless scalabilitY At No Extra CosT
CATALYST Microservices leverage the nearly limitless processing resources available in public clouds to scale processing without hardware constraints. By combining this with our consumption pricing model, you can process every image in a batch at once for the same cost of processing each image sequentially. Completing your project in a fraction of the time at no extra cost.
Cost Predictability
Processing costs are predictable and directly attributable to the work being performed
Cost Predictability at Any SCale
CATALYST Microservices use a consumption model that prices your work based on the amount of data that is being processed and includes all hardware, infrastructure and data access costs. This allows you to directly associate your costs to the work being performed, simplifying your cost attribution, while reducing risks by eliminating cost uncertainty.
CATALYST Microservices is our library of workflows and algorithms that are implemented on major cloud providers to automate and simplify the user experience and data acquisition, eliminate costly waste, and automatically scale to minimize project duration.
The smarter way to process earth imagery on the cloud
CATALYST Microservices solves one of the biggest barriers to the commercialization of information derived from Earth imagery… How to cost-effectively process the many petabytes of Earth imagery at scale.
Explore Our Rich Set of Capabilities
| Capability | Description | Sensor Support | Cloud Support |
|---|---|---|---|
| Displacement Mapping (millimeter precision) | Reliably detect millimeter precision ground movement using a sophisticated Small Baseline Subset Synthetic Aperture Interferometry (SBAS-InSAR) technique on a stack of InSAR compatible images | SAR |
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| Displacement Mapping (centimeter precision) | Calculate ground movement with centimeter precision from as few as 2 InSAR compatible image | SAR |
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| Analysis Ready Data (ARD) | Analysis Ready Data (ARD) is the result of converting satellite image pixels into highly-accurate interoperable scientific measurements. This allows for immediate analysis with minimal additional processing. The CATALST ARD workflow consists of a rigorous geometric correction, radiometric normalization, quality assessment and product packaging based on the CARD4L specifications | Satellite |
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| Automatic Orthorectification | Designed to maximize automation, accuracy, and precision, our orthorectification workflows for satellite, SAR, and aerial imagery are packed with the top image matching, self-camera calibration, bundle adjustments, and model refinement algorithms of today. | Satellite, Aerial, SAR |
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| Automatic Mosaicking | Our mosaicking workflow consists of sophisticated automation to balance colors, and create seamless edges from gigabytes to petabytes of satellite, aerial and SAR ortho imagery | Satellite, Aerial, SAR |
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| Super Registration | A common problem with Ortho-images from different archives and projects is that they do not align with one another, which impedes analysis. Super registration can align satellite with aerial and or UAV archives so that they align with geometric accuracies as high as 1/10th of a pixel | Satellite, Aerial, SAR |
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| True Orthorectification | Automatically remove building lean and create a nadir (top-down) ortho image from overlapping aerial imagery and a DSM | Aerial |
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| DEM (DSM) Extraction | We use a semi-global matching technique to calculate elevation measurements from multiple viewing angles and compares the measurements against one another using a sophisticated algorithm to determine the most accurate measurement for each pixel in your DEM. | Satellite, Aerial, SAR |
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| DTM Filtering | Automatically remove surface features such as buildings and trees, while preserving terrain features, such as slopes | Satellite, Aerial, SAR |
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| Image Tiling | Tile very large images to more reasonable sizes for improved data storage and streaming | Satellite, Aerial, SAR |
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| Autmospheric Correction | Uses ATCOR to remove atmospheric, terrain and BRDF effects in imagery | Satellite |
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| Haze Removal | Minimize the impact of haze in pixels with an empirical approach | Satellite |
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| Cloud Masking | Automatically and accurately identify and cloud masks for improved analysis, mosaicking and image compositing | Satellite |
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| Pansharpening | Create a multispectral with the detail and resolution of the associated panchromatic image pair | Satellite, Aerial |
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| Scientific Image Fusion | MRA fusion creates a stunning pansharpened image, that preserves the spectral integrity of the image bands making it perfect for image compositing, spectral analysis and time-series analysi | Satellite |
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| Data Transformation | Reproject, resample, convert file formats and enhance imagery | Satellite, Aerial, SAR |
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| Capability | Description | Support |
|---|---|---|
| GCP Collection | Automatically collect and refine ground control points against a reference image | Satellite, Aerial, UAV |
| Bundle Adjustment | Automatically collect tie points to align adjacent images in a project | Satellite, Aerial, UAV |
| Satellite Orthorectification | Orthorectify satellite imagery using the most accurate supporting model | Satellite |
| Airphoto Orthorectification | Orthorectify digital, UAV, analog or pushbroom airphotos | Aerial, UAV |
| True Orthorectification | Create True Orthorectified images from multiple overlapping images of Aerial and UAV images | Aerial, UAV |
| SAR Orthorectification | Orthorectify SAR imagery | Radar |
| DEM Extraction | Extract 3D digital elevation models (DEM) and digital surface models (DSM) using semi global matching | Satellite, Aerial, UAV |
| Digital Terrain Model Filtering | Create digital terrain models (DTM) by filtering out surface features from DSMs or DEMs | DEM |
| Super Registration | Align any image to 1/10th of a pixel accuracy | Satellite, Aerial, UAV |
| SAR DEM Extraction (Stereo) | Extract 3D DEMs from SAR stereo imagery | Radar |
| Mosaic Seamline Generation | Automatically calculate the best path for seamlines to eliminate visible seams | Satellite, Aerial, UAV |
| Mosaic Colour Balancing | Automatically balance the color of all images in a mosaicking project | Satellite, Aerial, UAV |
| Mosaic Tiling | Automatically tile a mosaic for easier storage | Satellite, Aerial, UAV |
| Mosaic Preview | Generate a low resolution mosaic preview for quality assurance | Satellite, Aerial, UAV |
| Capability | Description | Support |
|---|---|---|
| Principle Component Analysis | Reduce dimensionality and improve classification with eigen decomposition | Satellite, Aerial, UAV |
| Texture Measurement | Analyse the texture of features in images | Satellite, Aerial, UAV, Radar, DEM |
| Atmospheric Correction | Convert satellite DN values to ground reflectance using a physical model | Satellite |
| Haze Removal | reduce the visual and scientific impact of haze in satellite images | Satellite |
| Cloud Masking | Automatically mask clouds | Satellite |
| Spectral Pre Classification | Preclassify pixels using Modis data for improved modelling | Satellite |
| Pansharpeing | Panchromatic sharpening to increase the resolution of multispectral images | Satellite |
| Image Fusion | Scientific method to increase multispectral resolution using a panchromatic pair that maintains the radiometric integrity of the multispectral image | Satellite |
| Masking | Create custom masks for inclusion or exclusion in modeling, analysis and mosaicking | Satellite, Aerial, UAV, Radar, DEM |
| Filtering | Low and high pass filtering | Satellite, Aerial, UAV, Radar, DEM |
| Reprojecting | Change the geographic coordinate systems and projections of imagery and vectors | Satellite, Aerial, UAV, Radar, DEM |
| Image Enhancing | Enhance the histogram of images | Satellite, Aerial, UAV, Radar, DEM |
| Morpholocical Operations | Dissolve and erode pixel mask boundaries (bitmaps) | Satellite, Aerial, UAV, Radar, DEM |
| Resampling | Resample imagery/rasters to higher or lower resolutions | Satellite, Aerial, UAV, Radar, DEM |
| Capability | Description | Support |
|---|---|---|
| Object-based classification | Object-based image classification using advanced machine learning algorithms | Satellite, Aerial, UAV, Radar, DEM |
| Feature extraction | Object and pixel feature extraction using machine learning and heuristics | Satellite, Aerial, UAV, Radar, DEM |
| Change Detection | Object and pixel-based image change detection | Satellite, Aerial, UAV, Radar, DEM |
| Vegetation Analysis | Over 30 different vegetation indices for RGB and MS imagery | Satellite, Aerial, UAV |
| Image statistics | Collect and chart statistics from imagery, such as histograms | Satellite, Aerial, UAV, Radar, DEM |
| Pixel-based classification | Classify and cluster image pixels using supervised and unsupervised machine learning techniques | Satellite, Aerial, UAV |
| Lineament Extraction | Extract linear features from an image | Satellite, Aerial, UAV, Radar, DEM |
| Vector Analysis | Intersection, overlay, neighborhood | Vector |
| Capability | Description | Support |
|---|---|---|
| Deformation Analysis | Measure up to millimeter precision ground deformation (ground movement) from SAR pairs using InSAR | Radar |
| SAR Orthorectification | Orthorectify SAR imagery | Radar |
| SAR DEM Extraction (InSAR) | Extract 3D DEMs from SAR imagery using InSAR | Radar |
| SAR DEM Extraction (Stereo) | Extract 3D DEMs from SAR stereo imagery | Radar |
| SAR Change Detection | Change detection using phase, amplitude and or coherence from single, dual, full and compact Polarimetric SAR imagery | Radar |
| Compact Polarimetry | Support for compact polarimetry workflows | Radar |
| SAR filters | A variety of specialized filters for SAR imagery | Radar |
SAR Object Based Classification | Object-based image classification using advanced machine learning algorithms | Radar |
| Capability | Description | Support |
|---|---|---|
| Geometric Correction | Fully automated geometric correction based on CARD4L specifications | Satellite |
| Radiometric Correction | Fully automated radiometric correction based on CARD4L specifications | Satellite |
| Image Fusion | Multi-resolution Analysis for scientific pansharpening. This technique retains the spectral fidelity of the MS image during the pansharpening process | Satellite |
CARD4L Product Packaging | Metadata, report and file format creation basd on CARD4L specifications | Satellite |
| Capability | Description | Support |
|---|---|---|
| File Conversion | Convert imagery between popular file formats | Satellite, Aerial, UAV, Radar, DEM |
| Data Conversion | Convert bit-depth, interleaving and more | Satellite, Aerial, UAV, Radar, DEM |
| Bitmap and Vector Conversions | Convert between bitmaps, points, lines and polygons | Vector |
| Data Merge | Combines multiple bands from several files into a singe file by using the georeferencing of the source files | Satellite, Aerial, UAV, Radar, DEM |
| Reprojecting | Change the geographic coordinate systems and projections of imagery and vectors | Satellite, Aerial, UAV, Radar, DEM |
Get started today
Speak with one of our expert solution consultants to learn more about CATALYST Microservices.
