![]() ![]() The system is based on a network of nodes on planetary surfaces, in stable orbits around the Earth, the moon or Mars, or at well-defined points in space where the gravitational force between the two bodies (in this case, the Earth and the moon) cancel each other out. The latest version, SpaceNet 1.3, was released this month. de Weck, associate professor of aeronautics and astronautics and engineering systems, and David Simchi-Levi, professor of engineering systems and civil and environmental engineering, created SpaceNet, a software tool for modeling interplanetary supply chains. In the past, I have also served regularly on interview panels for final selection of Fulbright MS and PhD candidates from Pakistan.To figure out how to do that, MIT researchers Olivier L. I was an invited panelist at the School of Tomorrow event in Karachi, held in Nov., 2018. I was an invited speaker at the TEDxIslamabad event held in Nov., 2014, and have also served as a mentor in the NASA International Space Apps Challenge Islamabad events in April 20. From 2013 – 2017, I have been the Pakistan National Point of Contact for Space Generation Advisory Council (SGAC). I am an alumnus of Pakistan National Physics Talent Contest (NPTC), an alumnus of the Lindau Nobel Laureate Meetings, and a Fulbright fellow. I am a reviewer for various international scientific journals and conferences. My core specialization makes me think of myself as an Earth Scientist or Remote Sensing Scientist, with specialized skills in EO / SAR remote sensing, satellite oceanography, scientific programming, and strategic management of technical teams with diverse skill sets. (), leading the complete technical team there. Since late 2021, I am the CTO at Offshore Monitoring Ltd. I also spent a few months as a Visiting Researcher at Radar Remote Sensing Group, Division of Microwave & Optical Remote Sensing, Department of Space, Earth & Environment, Chalmers University of Technology, Gothenburg, Sweden. of Space Science, Institute of Space Technology (IST), Islamabad, Pakistan, where I initiated the Radar Remote Sensing group, and was one of the founders of the Geospatial Research & Education Lab (GREL). ![]() Thereafter, I served for many years in the faculty of the Dept. of Aerospace Engineering Sciences, with specialization in Remote Sensing, Earth and Space Science, as a Fulbright fellow. I received my PhD in 2013 from the University of Colorado, Boulder, USA, from the Dept. SpaceNet datasets can be accessed on AWS here. To read more about the launch of SpaceNet, see coverage on GISCafe, TechCrunch, MIT Technology Review, and Popular Science. SpaceNet plans a massive increase in both images and labeled features to be made available over the platform in the future. Incidentally, the name SpaceNet is inspired from ImageNet, a similar database of images created to help spur early advancements in computer vision. Application examples include detection of each building as a separate object and determining a bounding box around it, and semantic segmentation to partition the image into regions of pixels that can be given a common label, such as “building”, “forest”, “road”, or “water”. Scripts are already cropping up on GitHub for manipulating and using the satellite imagery data on SpaceNet: see code examples from Development Seed here and from CosmiQ Works here. NVIDIA has also released a detailed case study of analysis of SpaceNet data using their Deep Learning GPU Training System ( DIGITS) platform, demonstrating the power and capability of GPU-based deep learning algorithms applied over high resolution satellite imagery. This dataset is being made public to advance the development of algorithms to automatically extract geometric features such as roads, building footprints, and points of interest using satellite imagery. True color WV-2 high resolution imagery sample from the SpaceNet repository, along with corresponding building footprints.
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