List of machine learning competitions for satellite imagery and remote sensing. Download PDF Abstract: This paper describes our approach to the DSTL Satellite Imagery Feature Detection challenge run by Kaggle. Standing water 9. I ended up with a intersection of NDWI and CCCI masks (with boundary contact checking to filter out standing water / building artifacts) rather than using deep learning approaches, thus freeing up training resources for other classes. This scheme was applied also on test images, so results are pipelined as you can see from the flowchart. Large vehicles 10. Having more systems helps in terms of creating experiments and ensemble permutations, but it’s not absolutely necessary if you have a strong flow or network. Optimization wise I used the Jaccard loss directly with Adam as optimizer (I did not get much improvement from NAdam). Thanks for subscribing! The Worldview tool from NASA's Earth Observing System Data and Information System provides the capability to interactively browse over 900 global, full-resolution satellite imagery layers and then download the underlying data.Many of the imagery layers are updated daily and are available within three hours of observation - essentially showing the entire Earth as it looks "right now". The staff at EROS has been processing satellite imagery since 1972, but the facility has never been able to control a satellite’s movements – until now. For this competition, the number of true positives and false positives are aggregated over all of the test imagery and the F1 score is computed from the aggregated counts. The primary goal of this challenge is accurate semantic segmentation of different classes in satellite imagery. Crops 7. Take a look at our Sentinel Hub brochure for more information. You can use images from both outlets to study geography and survey land. I used three desktops for this contest. Credit: Capella Space. One swarm measured 60 x 40 kilometres wide in the country’s northeast area, Intergovernmental Authority on Development (IGAD) said in a press release. Various widths (256x256, 288x288, etc.) Moreover, data science is an ever evolving field. This was after completing various online machine learning courses — Andrew Ng’s Machine Learning course, Geoffrey Hinton’s course on Neural Networks, to name a few. The competition task was to create a 50 drone New Year animation with a maximum length of 5 minutes using Blender animation software. Crops — The image was first scaled to 1024x1024 (lowered resolution), then split into 256x256 overlapping sliding windows. The other important classes which I spent a chunk of time on were the two vehicle classes. Top Tier Worldwide Data European Space Agency Registration Required. Jul 26, 2018 Lava from Hawaii's Kilauea Volcano flowing to the Pacific Ocean, imaged July 25 by NASA's Advanced Spaceborne Thermal Emission and Reflection (ASTER) instrument. ExecutiveGov, published by Executive Mosaic, is a site dedicated to the news and headlines in the federal government. Overall, I generated 40+ models of various scales/widths/depths, training data subsamples, and band selections. Secondly, many vehicles were very hard to distinguish between large and small classes both in terms of visibility (blurred) and mask areas. In June, we concluded the second SpaceNet competition, a satellite imagery object detection competition hosted by CosmiQ Works, DigitalGlobe, and NVIDIA. Live imagery is updated every 10 minutes from NOAA GOES and JMA Himawari-8 geostationary satellites. The public and private LB score for this class seemed competitive relative to other teams who may have used deep learning methods. To understand the structure of Commercial Satellite Imagery market by identifying its various sub segments. No pretrained models were used in the final solution, although I did give fine-tuned (VGG16) classifier-coupling for merged vehicle networks a shot — to no avail. Most importantly, have fun during the competitions — it won’t even feel like work when you are having fun (!) In fact, this field wasn’t even on the radar a decade ago — so be sure to keep to date on the architectural improvements year-by-year. Focuses on the key global Commercial Satellite Imagery manufacturers, to define, describe and analyze the sales volume, value, market share, market competition landscape, SWOT analysis and development plans in next few years. I’d like information about a particular satellite mission! In this interview, first place winner Kyle Lee gives a detailed overview of his approach in this image segmentation competition. Capella Space released radar satellite images with a resolution of 50 centimeters by 50 centimeters, which the San Francisco startup says is the highest resolution available from a … EXAMPLES OF SMALL VEHICLES RELATIVE TO ROADS AND BUILDINGS. Surprisingly, waterways could well be generated using simple and fast index methods. Satellite imagery is new to me, where can I start learning about it? Query and order satellite images, aerial photographs, and cartographic products through the U.S. Geological Survey Roads 4. "NGA mission success is contingent on a world-class workforce with a wide diversity of opinions and expertise,” NGA deputy director and 2020 Wash100 Award recipient Dr. Stacey Dixon. For reference, their mask areas from training data are shown in the histogram below, and there is a large area overlap between large and small vehicles from around 50–150 pixels². Ultimately, I ended up using rasterio/shapely to perform polygon to WKT conversion. Satellite imagery and aerial photography can both give you a clear image of the planet Earth, from above. satellite mission database; I’d like to search for and download free satellite imagery for an area of interest! I would have added some ensembling to crops, added heat-map based averaging (and increase the test overlap windows at some expense of runtime), dilated structures training mask (which helped structure scoring for some competitors), and removed most of the expensive rare scale (320x320, for example) ensembling on tracks. In addition, I also oversampled some of the rare classes in some of the ensemble models. satellite mission database; I’d like to search for and download free satellite imagery for an area of interest! The team is on its way to the 2018 NASA Robotic Mining Competition at the Kennedy Space Center. Many features (such as histogram of oriented gradient, local binary pattern, scale-invariant feature transform, etc.) Lillian Kay Petersen, 17, has won the Regeneron Science Talent Search, a top science and math competition for high school seniors. Index methods for waterways — namely a combination of Non-Differential Water Index (NDWI) and Canopy Chlorophyl Content Index (CCCI). It’s always interesting to see what neural networks can accomplish with segmentation — first medical imaging, now multi-spectral satellite imagery! Oversampling on rare classes — oversampling was performed by sliding in smaller steps over positive frames and sliding in larger steps over negative frames than default window size. This post-processing resolved class confusion between standing water and waterways, cleaned up artifacts on the roads, and gave some additional points to the large vehicle score. My understanding is that most competitors had either weak public or private scores with standing water and vehicles, which I spent extra effort to deal with in terms of pre- and post-processing. As I mentioned earlier I participated in one of the earliest segmentation challenges on Kaggle — the “Ultrasonic Nerve Segmentation”. The first two were used for all the training/inferencing of all classes, while the last one (#3) was only run on crops. The sliding window steps are shown below: Oversampling standing water and waterway together was a good idea since it helped to reduce the amount of class confusion between the two, with reduced artifacts (particularly for standing water predictions). High School Senior's Tool To End Food Insecurity Wins National Competition Lillian Kay Petersen, 17, has won the Regeneron Science Talent Search, a top science and math competition … During the day, I design high-speed circuits at a semiconductor startup — e.g. In terms of cross validation, I used a random patch split of 10–20% across images (depending on class, the rarer the larger). L3Harris Geospatial offers an extensive selection of the highest resolution satellite imagery commercially available. NGA said Monday that it is seeking automated approaches that can trace, delineate and describe circles in satellite imagery as part of the Circle Finder challenge. The National Geospatial-Intelligence Agency is offering $50,000 in prizes for artificial intelligence solutions designed to help detect circles in satellite images. All classes (except trees) had no approximation, while trees were first resized to 1550x1550 — effectively approximating the polygons — before being converted to WKT format. 06/19/2017 ∙ by Vladimir Iglovikov, et al. Monday, January 18 2021 . As part of the Circle Finder challenge NGA is looking for novel automated approaches to help detect, delineate and describe circular shaped features using satellite images. Competition Encourages Use of Geospatial Software to Spread Awareness of Sustainable Development. Please check your email for further instructions. Complex Imagery and Map Data Projects Completed at Once; Impossible Ones Take Just a Bit Longer. Sorted by submission deadline. Users can explore the globe by entering addresses and … Immediately after that I was looking forward to the next image segmentation challenge, and this was the perfect opportunity. I made tweaks to the original architecture with batch-normalization on the downstream paths + dropout on the post-merge paths, and all activation layers switched to Exponential Linear Unit (ELU). clock-data recovery, locked loops, high-speed I/O, etc. However, in the real world, clouds and competition for satellite time are significant obstacles. For example, suppose there are N polygon labels for building footprints that are considered ground truth and suppose there are M proposed polygons by an entry in the SpaceNet competition. Welcome to Alexa's Site Overview. (3)"Host" is the host(s) of the Competitions. (hereinafter referred to as the "Client(s)"). The datasets created and released for this competition may serve as reference benchmarks for future research in satellite image analysis. In terms of submissions, I used a majority of the submissions trying to fine tune polygon approximation. Having said that, I am still a beginner in many areas in data science — and still learning, of course. From here, all you have to do is download. October 1, 2020 Compare that to OneWeb, a SpaceX competitor, whose satellite constellation will orbit at 1,200 … The Farming by Satellite Prize 2020, promoting the use of satellite technologies in agriculture, was awarded on Monday 30th November at the virtual awards ceremony. Get satellite imagery on your table without worrying about synchronization issues, storage, processing, de-compression algorithms, meta-data or sensor bands. But the download speeds are still slow and sluggish. The asterisk (*) for private LB score on crops indicate a bug with OpenCV’s findContours, that if I had used the correct WKT generating script for that class I would have had a crop private LB score of 0.8344 instead of 0.7089. Patience and persistence were key as he developed unique processing techniques, sampling strategies, and UNET architectures for the different classes. No augmentation with ensembling was performed on validation or test data. As far as band usage is concerned, I mostly used panchromatic RGB + M-band and some of the SWIR (A) bands. Contact us; Advertise with us; Shopping. Users can explore the globe by entering addresses and … artificial intelligence to detect circular-shaped elements in satellite images, Stacy Cummings to Take Acting Undersecretary Role for DoD, DOE Announces $124M Funding Opportunity for Domestic Manufacturing Projects, Technology Advancement Group Names Craig Janus as CEO, NGA to Increase Opportunities for Neurodiverse Workforce; Dr. Stacey Dixon Quoted, Aaron Weis Discusses U.S. Navy IT Modernization Priorities for 2021, NCI Secures $807M Task Order to Support GSA Digital Transformation; Paul Dillahay Quoted, VTG Buys Intelligent Shift in National Security Market Push; John Hassoun Quoted, AeroVironment to Buy Arcturus UAV in $405M Cash-Stock Deal; Wahid Nawabi Quoted, Ellen Lord: DOD’s Digital Marketplace Seeks to Drive ‘Trusted’ Partnerships Between Investors, Companies, NGA Issues Draft RFP for Potential $947M ‘Clover’ Lifecycle Acquisition, Financial Mgmt Support IDIQ, Lockheed Named Largest Contract Recipient in DOD’s Fiscal 2019 State-Level Spending Report, Jacobs Secures Navy Contract for Waterfront Facilities Services, Executive Spotlight: NCI President, CEO Paul Dillahay Discusses $807M GSA DIGIT Task Order Win, ECS Promotes John Heneghan to COO, Giles Kesteloot to CSO; George Wilson Quoted, Coalfire Federal Certified to Offer Consulting on DOD’s Contractor Cybersecurity Standards, SpaceX to Support Intuitive Machines’ Second NASA Lunar Payload Delivery Mission, Simba Chain Awarded Navy Contract to Continue Dev’t of Blockhain-Based Logistics Monitoring Tech. 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