descarteslabs.comPlatform - Descartes Labs

Skip to content Get Started Platform Overview Data Refinery Data Sources Workbench Applications APIs Industries Agriculture Oil & Gas Mining & Metals Power & Renewables Shipping & Logistics Financial Services & Insurance Geospatial Environmental Impact Solutions Overview Solutions Team At A Glance End-to-end Solutions Development Company About Vision Leadership Careers Media Coverage Press Releases Contact Us Impact Science Program Resources Blog Resource Library Mobility Get Inspired Platform Industries Solutions Company Resources Back Platform Overview Data Refinery Data Sources Workbench Applications APIs Back Industries Agriculture Oil & Gas Mining & Metals Power & Renewables Shipping & Logistics Financial Services & Insurance Geospatial Environmental Impact Back Solutions Overview Solutions Team At A Glance End-to-end Solutions Development Back Company About Vision Leadership Careers Media Coverage Press Releases Contact Us Impact Science Program Back Resources Blog Resource Library Mobility Get Inspired Get Started Put science behind your decision-making With our geospatial platform, organizations can build predictive models to scientifically validate insights and decisions. Our Platform Use Cases Surface the power of geospatial data Unleash a powerful source of data to predict, adapt to and capitalize on the outside world. Our Platform Use Cases Rapidly define and experiment with new strategies Interrogate diverse datasets to test hypotheses and forecast outcomes. Our Platform Use Cases Improve decision-making to arrive at better, faster answers Ask higher-order questions that hinge on a better understanding of the planet. Our Platform Use Cases Create advantage through scientifically validated analytics Outperform in your market by operationalizing global insights and forecasts. Our Platform Use Cases Overview The Descartes Labs Platform is designed to answer some of the world’s most complex and pressing geospatial analytics questions. Our customers use the platform to build algorithms and models that transform their businesses quickly, efficiently, and cost-effectively. By giving data scientists and their line-of-business colleagues the best geospatial data and modeling tools in one package, we help turn AI into a core competency. Data science teams can use our scaling infrastructure to design models faster than ever, using our massive data archive or their own. The Descartes Labs Platform Data Refinery We provide petabytes of analysis-ready geospatial data and the ability to ingest, clean, calibrate, and benefit from any internal or third party data source. Workbench Our cloud-based data science environment combines the Descartes Labs Platform APIs, visualization tools, and sample models inside a hosted JupyterLab interface. Applications We enable enterprise teams to move faster than ever as they build applications that generate valuable insights and save money across multiple use cases. Customers rely on our cloud-based platform to quickly and securely scale computer vision, statistical, and machine learning models to inform business decisions with powerful raster-based analytics. Key features and sample applications Our extensive API documentation, tutorials, guides and demos provide a deep knowledge base for users allowing them to quickly deploy high-value applications across diverse industries including Agriculture , Oil & Gas , Mining & Metals , Power & Renewables , Shipping & Logistics , Financial Services & Insurance , and more. Data Sources Multiband Optical High-Res Optical Atmospheric Geostationary SAR Elevation Hydrological Meteorological Geolocation and AIS Land Use Internal Data Derivative Data Learn more about our data sources Copernicus Sentinel data 2020 Overview Geospatial data can add invaluable information to modern data science workflows, but it can be challenging to incorporate. Complications arise for data scientists when they’re confronted with legacy coordinate systems, band combinations, differing resolutions, cloud cover, or seemingly endless post-processing steps. Beyond imagery issues, further challenges stem from the massive, billion-record vector datasets generated by AIS shipping transponders, mobile devices, ground cameras, and sensors. When fusing such datasets together into a time series analysis, these difficulties can become insurmountable. In short, we’re living through a sensor revolution and the world needs better tools to prepare and manage all of the data being produced. The Descartes Labs Platform is such a tool, equipping customers with 15+ petabytes of analysis-ready data from some of the world’s leading satellite constellations and ground-based sensors. Customers use this data to power continental-scale models without the hassle of downloading, data preparation, storage, or compute. Our data ingestion pipelines perform continuous loading and automatic pre-processing at speeds up to 20 gigabytes per second. The processing stages we go through for a typical image may include: Retrieving it from cloud storage Uncompressing it Parsing the metadata Identifying the bounding rectangle that contains valid data Cleaning the edges of the image Converting the raw pixel information into meaningful units Calibrating top of atmosphere reflectance using the appropriate constants for each satellite Accounting for solar distance and zenith angle Tiling to standard sizes Performing any necessary coordinate transformations Compressing the data back into a standard format Storing the result back into the cloud. Datasets Multiband Optical Landsat 4, 5, 7, 8: A joint NASA/USGS program providing the longest continuous space-based record of Earth’s land in existence Sentinel-2, Sentinel-3: An ESA Copernicus program providing multi-spectral imaging instruments for land, ocean and atmospheric monitoring MODIS: A sensor aboard NASA’s Terra and Aqua satellites that views the entire Earth’s surface every 1 to 2 days and acquires data in 36 spectral bands ASTER: A sensor aboard the NASA Terra satellite providing high-resolution images of Earth in 14 different bands of the electromagnetic spectrum, ranging from visible to thermal infrared light High-Res Optical Airbus SPOT 6 and SPOT 7: A set of wide-swath high-resolution (1.5 m) optical imagery satellites owned and operated by Airbus Defense and Space Airbus Pleiades A and Pleiades B: A set of very high-resolution (0.5 m) optical imagery satellites owned and operated by Airbus Defense and Space NAIP: National Agricultural Imagery Program’s orthoimagery collected during the peak growing season Texas Orthoimagery Program: 50cm orthoimagery collected during leaf-off conditions Any taskable satellite or aerial imagery from third party providers Atmospheric Sentinel-5P: An ESA Copernicus program providing radar and multi-spectral imaging instruments for land, ocean and atmospheric monitoring More planned for 2020 and beyond Geostationary NOAA GOES-16, GOES-17: A pair of geostationary satellites positioned over the Western Hemisphere with a five minute refresh. Useful for detecting and monitoring storm systems, fog, wildfires, and other weather phenomena DMSP night lights: The Defense Meteorological Satellite Program’s cloud-free composites of average light percent from nighttime-visible bands Meteorological NCEP CFSR: The National Centers for Environmental Precition’s Climate Forecast System Reanalysis: The most extensive gridded weather product with daily global coverage NOAA GSOD: The National Oceanic and Atmospheric Administration’s Global Surface Summary of the Day: A higher resolution daily weather dataset interpolated into a grid NOAA GFS: The National Oceanic and Atmospheric Administration’s Global Forecast system: A numerical weather prediction system published multiple times a day SAR Sentinel-1: An ESA Copernicus program providing radar imaging instruments for land, ocean and atmospheric monitoring Elevation N...