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“How QuantCube Technology uses alternative data to create macroeconomic, financial and extra-fiancial indexes? Specific focus on the use of satellite images.” by Alice Froidevaux - Lead Data Scientist @QuantCube Technology

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QuantCube Technology uses artificial intelligence and big data analytics to deliver real-time macro-economic insights. The firm operates one of the largest alternative data lakes in the world, processing more than 14 billion data end points. Sources encompass news, social media, satellite data, professional networks and consumer reviews, as well as international trade, shipping, real-estate, hospitality and telecoms data.
During this session we will see how QuantCube Technology uses satellite data to create standardized indicators of economic activity.

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“How QuantCube Technology uses alternative data to create macroeconomic, financial and extra-fiancial indexes? Specific focus on the use of satellite images.” by Alice Froidevaux - Lead Data Scientist @QuantCube Technology

  1. 1. Titre QuantCube Technology ©2021 All rights reserved. QuantCube Big Data Analytics for Economic & Financial Intelligence
  2. 2. 2 QUANTCUBE DATALAKE Leveraging on the asymmetry of information to create competitive edges Big Data and AI • One of the most sophisticated AI technology and Big Data processing expertise • Fully transparent methodology • Specifically tailored for Financial Markets Real-time Macroeconomic • Leading indicator by construction with high correlation • Supported by a team of 50+ data scientists • Based on more than 14 billion datapoints Our partners
  3. 3. 3 QUANTCUBE DATALAKE QUANTCUBE ARTIFICIAL INTELLIGENCE QUANTCUBE ECONOMIC INTELLIGENCE FACTORY Smart Data Catalog GLOBAL MACRO NOWCAST SMART DATA REAL-TIME SECTOR TRACKERS Economic Growth (G7 & China) Inflation Index by components Sector Employment Index Business Cycle Index Credit Cycle Index Crude Oil Sentiment Index Iron Ore Trade Index Automotive Exports Index Outbound Chinese Tourist Index Prediction of BDI Index USE CASES EXAMPLES FOREIGN EXCHANGE ARBITRAGE MACROECONOMIC RESEARCH TACTICAL ASSET ALLOCATION CORPORATE INVESTMENTS EQUITY OPPORTUNITIES S&P500 INDEX, ETFs FIXED INCOME RESEARCH PROJECT FINANCING TRACKERS REAL ESTATE INVESTMENTS OUR PRODUCT: ECONOMIC INTELLIGENCE PLATFORM NLP for Text Analytics Deep Learning for Pictures Analytics Graph Theory for Network Modeling Machine Learning on Structured data Social Media Professional Networks Satellite Imagery Blogs Transportatio n Data Real Estate Hospitality Consumer Reviews
  4. 4. 4 See what Wall Street does not see (feedback) May 7, 2020 Provides unique real-time macro data USA, Eurozone, China Investment Strategies Unique Proprietary Datalake GDP Nowcast – US, Eurozone, China International Trade, Employment, Industrial Production, Consumer Spendings, … Maritime, Air & Road Traffic Multi-lingual Social Media Many other data sources… Use cases BIG DATA ANALYTICS FOR MACROECONOMICS
  5. 5. QUANTCUBE SATELLITE DATA ANALYTICS Use Case: Urban Growth proxy
  6. 6. 6 The spatial resolution of a satellite image is the size of the area covered by a pixel. Each pixel of the image corresponds to part of the surface of Earth. QUANTCUBE SATELLITE DATA ANALYTICS Introduction: Spatial Resolution
  7. 7. 7 Mining Agriculture Manufacturing Oil&Gas Industry etc… q Earth Observation satellites : Sentinel 2 & Landsat 7&8 q High Resolution satellites : Pléiades (50cm de résolution) q Atmospheric satellites : Sentinel5P & OCO-2 q Radar satellites : Sentinel 1 q Thermal images : Landsat 8 & Sentinel 3 MACRO ECONOMIC LEVEL SECTOR ANALYTICS Urban Growth Air Pollution Water Stress QUANTCUBE SATELLITE DATA ANALYTICS Access to any satellite data through our partnership with European Space Agency
  8. 8. 8 8 Pleiades satellite image Deep neural network Number of vehicles in each region of interest Commercial sites Industrial sites Vehicle assembly sites Construction sites Streets 50 cm resolution Is car detection possible at this resolution ? USE CASE: Car detection in satellite images Technical specification of the solution
  9. 9. 9 9 ● Images from satellites Pleiades 1A & 1B ● 50cm spatial resolution ● 4 bandes : RGB and NIR ● Geographic area : region of Paris, France ● Heterogeneous environments : rural, forest, residential and industrial areas USE CASE: Car detection in satellite images Pleiades images description
  10. 10. 10 Three different strategies : 1. Semi-supervised labeling using a network trained on a public aerial image dataset adapted to the resolution of Pleiades sensor; 2. Constitution of training data by integrating synthesized images; 3. Semi-automatic annotation of Pleiades images. Aerial images of 5 cm spatial resolution downscaled at 50 cm : ● colorful vehicles ● sharp outlines Pleiades images : ● white or black vehicles ● irregular outlines ● indistinguishable shadows and cars USE CASE: Car detection in satellite images Semi-automatic annotation process - Creation of our training data set
  11. 11. 11 11 ● An interactive labeling tool was developed ● Enables the labeling of 60% of vehicles with one click using flood-fill methods adapted for this application. ● The mask color is automatically changed in order to distinguish two touching cars. Next, all bounding boxes are extracted. 87 000 labelled vehicles internally USE CASE: Car detection in satellite images Semi-automatic annotation process - Creation of our training data set
  12. 12. 12 12 We investigated a segmentation algorithm Tiramisu [1] with post-processing and we adapted a direct detection network YOLOv3 [2]. Vehicle detection from satellite images is a particular case of object detection as : ● Objects do not overlap ● Objects are uniform ● Objects are very small (around 5*8 pixels/vehicles in Pleiades images) [1] Tiramisu: “The One Hundred Layers Tiramisu : Fully Convolutional DenseNets for semantic segmentation”, S. Jégou, M. Drozdzal, D. Vazquez, A. Romero et Y. Bengio (2017) [2] YOLOv3: “An Incremental Improvement”, J. Redmon et A. Farhadi (2018) USE CASE: Car detection in satellite images Modelling - Deep learning models for vehicle detection and counting
  13. 13. 13 13 Data Augmentation added at the predicting phase with padding and geometric operations. Post-processing to count vehicles based on the size and shape of the predictions within the segmentation mask 20 predictions per pixel that are processed by a voting system. The number of pixels associated with a block of multiple cars is divided by the mean number of pixels observed either in lined cars or in side by side cars. USE CASE: Car detection in satellite images Modelling – Tiramisu – Segmentation Model
  14. 14. 14 14 ● Removing two detection levels related to large objects (with a sub-sampling factor called stride of 32 and 16) ● Replacing them with two new prediction levels with strides of 4 and 2. State of the art detection neural network that was adapted to very small objects detection USE CASE: Car detection in satellite images Modelling – YOLOv3 – Detection Model
  15. 15. 15 15 Conclusion : Pleiades satellite images are exploitable for vehicle detection and counting applications. Detection results from a validation set including 2673 vehicles. Results using Tiramisu (middle) and YOLO model (right). Color codes: green for good detection, blue for missed detection and red for false alarms USE CASE: Car detection in satellite images Results – Qualitative and Quantitative evaluations
  16. 16. 16 16 There are vehicles detected by YOLO but not by Tiramisu and vice versa. ➔ A mixed model based on both predictions may increase the number of detected vehicles. Mixed model : - Recall = 80.3% - Precision = 81.8% Tiramisu YOLO Mixed model USE CASE: Car detection in satellite images Results – Qualitative and Quantitative evaluations
  17. 17. 17 32 8 47 4 170 17 6 5 14 12 13 20 → Get the number of vehicles per ROI → Aggregation per sector (Macro Smart Data) or company (Equity Smart Data) Hospitality Commercial Logistics Number of vehicles 60 USE CASE: Car detection in satellite images Tracking activity level by tracking vehicles
  18. 18. New York (USA) 60 Broad Street, Suite 3502 New York, NY 10004, USA Paris (France) 15 Boulevard Poissonnière 75002 Paris, FRANCE For general enquiry: info@quant-cube.com www.quant-cube.com THANK YOU FOR YOUR ATTENTION !

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