References of "Schumann, Guy"
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See detailTowards global flood mapping onboard low cost satellites with machine learning
Mateo‑Garcia, Gonzalo; Veitch‑Michaelis, Joshua; Smith, Lewis et al

in Scientific Reports (2021), 11(7249 (2021)),

Spaceborne Earth observation is a key technology for flood response, offering valuable information to decision makers on the ground. Very large constellations of small, nano satellites— ’CubeSats’ are a ... [more ▼]

Spaceborne Earth observation is a key technology for flood response, offering valuable information to decision makers on the ground. Very large constellations of small, nano satellites— ’CubeSats’ are a promising solution to reduce revisit time in disaster areas from days to hours. However, data transmission to ground receivers is limited by constraints on power and bandwidth of CubeSats. Onboard processing offers a solution to decrease the amount of data to transmit by reducing large sensor images to smaller data products. The ESA’s recent PhiSat-1 mission aims to facilitate the demonstration of this concept, providing the hardware capability to perform onboard processing by including a power-constrained machine learning accelerator and the software to run custom applications. This work demonstrates a flood segmentation algorithm that produces flood masks to be transmitted instead of the raw images, while running efficiently on the accelerator aboard the PhiSat-1. Our models are trained on WorldFloods: a newly compiled dataset of 119 globally verified flooding events from disaster response organizations, which we make available in a common format. We test the system on independent locations, demonstrating that it produces fast and accurate segmentation masks on the hardware accelerator, acting as a proof of concept for this approach. [less ▲]

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See detailConventional EO Satellites vs. CubeSats; FDL - AI flood detection onboard a Nano Satellite
Backes, Dietmar UL; Schumann, Guy; Teferle, Felix Norman UL

Scientific Conference (2019, December 11)

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See detailFlood Detection On Low Cost Orbital Hardware
Mateo-Garcia, Gonzalo; Oprea, Silviu; Smith, Lewis et al

Scientific Conference (2019, October)

Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the ... [more ▼]

Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response organisations like UNICEF. Two main challenges are rapid access to data, and the ability to automatically identify flooded regions in images. We describe a prototypical flood segmentation system, identifying cloud, water and land, that could be deployed on a constellation of small satellites, performing processing on board to reduce downlink bandwidth by 2 orders of magnitude. We target PhiSat-1, part of the FSSCAT mission, which is planned to be launched by the European Space Agency (ESA) near the start of 2020 as a proof of concept for this new technology. [less ▲]

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See detailA comparison between conventional Earth Observation Satellites and CubeSats; Requirements, Capabilities and Data Quality
Backes, Dietmar UL; Hassani, Saif Alislam UL; Teferle, Felix Norman UL et al

Scientific Conference (2019, September 11)

From its early beginning as an educational tool in 1999, cubesats have evolved into a popular platform for technology demonstrations and scientific instruments. Ideas and innovations sparked from an ... [more ▼]

From its early beginning as an educational tool in 1999, cubesats have evolved into a popular platform for technology demonstrations and scientific instruments. Ideas and innovations sparked from an enthusiastic community led to the development of new Earth Observation (EO) technology concepts based on large constellations of satellites with high-resolution optical imagers previously considered as infeasible. Probably the most significant constellation today is deployed by Planet who are currently operating a fleet larger than 120 3U Dove satellites, which provide an imaging service with up to 3m Ground Sample Distance (GSD). The number of low-cost EO Cubesat systems is constantly increasing. However, for a number of reasons there still seems to be a reluctance to use such data for many EO applications. A better understanding of the capabilities of the current generation of small Cubesats compared to the traditional well-established bigger operational missions of high and medium resolution EO satellites is required. What are the critical capabilities and quality indicators? Due to the limited size and weight of Cubesats, critical system components, e.g. for navigation and communication, always compete with operational payloads such as optical camera/sensor systems. A functional EO system requires balanced payload, which provides adequate navigational capabilities, that match the requirements of the optical imagers (camera) deployed with the system. This study reviews the current performance and capabilities of Cubesats for optical EO and compares them to the capabilities of conventional, dedicated high and medium resolution EO systems. We summarise key performance parameters and quality indicators to evaluate the difference between the systems. An empirical study compares recent very high-resolution (VHR) imagery from big EO satellite missions with available images from Cubesats for the use case in disaster monitoring. Small and agile Nanosatellites or Cubesats already show remarkable performance. Although it is not expected that their performance and capability will match those of current bigger EO satellite missions, they are expected to provide a valuable tool for EO and remote sensing, in particular for downstream industry applications. [less ▲]

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See detailTowards a high-resolution drone-based 3D mapping dataset to optimise flood hazard modelling
Backes, Dietmar UL; Schumann, Guy; Teferle, Felix Norman UL et al

in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019, June), XLII-2/W13

The occurrence of urban flooding following strong rainfall events may increase as a result of climate change. Urban expansion, ageing infrastructure and an increasing number of impervious surfaces are ... [more ▼]

The occurrence of urban flooding following strong rainfall events may increase as a result of climate change. Urban expansion, ageing infrastructure and an increasing number of impervious surfaces are further exacerbating flooding. To increase resilience and support flood mitigation, bespoke accurate flood modelling and reliable prediction is required. However, flooding in urban areas is most challenging. State-of-the-art flood inundation modelling is still often based on relatively low-resolution 2.5 D bare earth models with 2-5m GSD. Current systems suffer from a lack of precise input data and numerical instabilities and lack of other important data, such as drainage networks. Especially, the quality and resolution of the topographic input data represents a major source of uncertainty in urban flood modelling. A benchmark study is needed that defines the accuracy requirements for highly detailed urban flood modelling and to improve our understanding of important threshold processes and limitations of current methods and 3D mapping data alike. This paper presents the first steps in establishing a new, innovative multiscale data set suitable to benchmark urban flood modelling. The final data set will consist of high-resolution 3D mapping data acquired from different airborne platforms, focusing on the use of drones (optical and LiDAR). The case study includes residential as well as rural areas in Dudelange/Luxembourg, which have been prone to localized flash flooding following strong rainfall events in recent years. The project also represents a cross-disciplinary collaboration between the geospatial and flood modelling community. In this paper, we introduce the first steps to build up a new benchmark data set together with some initial flood modelling results. More detailed investigations will follow in the next phases of this project. [less ▲]

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