Individual performance on a per city basis varies significantly, however, as can be seen in Table 1. The top three solutions to this challenge were in fact quite close to each other in overall performance.
SpaceNet Roads Extraction and Routing Challenge Results: One benefit of this metric is its continuity with past SpaceNet challenges: the SCOT tracking term reduces to the original SpaceNet Metric when evaluated at a single time step. Each solution comes with a description of the algorithm by the competitor, as well as instructions for how to build the Docker container, perform the model training process, and perform inference on the SpaceNet dataset using the released source code. Accordingly, we created the SpaceNet Change and Object Tracking (SCOT) metric that combines an object tracking and change term into a singular score. We are happy to announce the source code for the top five competitors is now available at the SpaceNet Github repository under an Apache 2 License. During the two-month long competition, we received 342 submissions from 33 competitors. APLS is designed to measure the routing capability of a network graph, as opposed to traditional pixel mask based metrics that do not address the underlying road connectivity. The SpaceNet Road Detection and Routing Challenge tasked competitors to develop algorithms to extract road networks from satellite imagery.įor the competition, SpaceNet released a new roads dataset with over 8000 kilometers of roads labeled, and introduced a novel metric for road extraction, Average Path Length Similarity (APLS). More details on this metric is provided here. APLS sums the differences in optimal path lengths between nodes in the ground truth graph G and the proposal graph G’. Currently, road networks are traced by hand from overhead imagery or created from ground surveys. The Spacenet 3 challenge proposes a graph theoretic metric based upon Dijkstra’s shortest path algorithm, called the Average Path Length Similarity (APLS) metric. Accurate road networks are an important map feature that is required for everything from logistics planning to turn-by-turn directions.
The mapping on this website is provided by external mapping providers and is for general information purposes only.In March, we concluded the SpaceNet Road Detection and Routing Challenge hosted by CosmiQ Works, Radiant Solution and NVIDIA. Please contact your local authorized Land Rover Retailer for availability and prices. Some vehicles are shown with optional equipment and retailer-fit accessories that may not be available in all markets. The information, specification, engines and colors on this website are based on European specifications and may vary from market to market and are subject to change without notice. Some features may vary between optional and standard for different model year vehicles. Jaguar Land Rover Limited is constantly seeking ways to improve the specification, design and production of its vehicles, parts, options and/or accessories and alterations take place continually, and we reserve the right to make changes without notice. Please contact your local authorized Land Rover Retailer for detailed 2022 model year specifications.
As a result, available features, options, trim and color schemes may differ from many images shown and therefore you should not rely solely on such images in making purchasing decisions. Until these unique events are resolved, please note that many vehicle images cannot be updated to 2022 model year specifications.
Furthermore, the global impact of micro-chip shortages is further affecting launch timings and build specifications, including options and accessories. Due to the COVID-19 pandemic, we have been prevented or delayed in the creation of new images of current model year vehicles. The SpaceNet 7 Multi-Temporal Urban Development Challenge aims to improve these methods, while simultaneously advancing the state of the art in SpaceNet’s core mission of foundational mapping. Important note on imagery & specifications. © 2022 Jaguar Land Rover North America, LLC
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