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.

ABSTRACT:The process of capturing and modelling buildings has gained increased focus in recent years with the rise of Building Information Modelling (BIM). At the heart of BIM is a process change for the construction and facilities management industries whereby a BIM aids more collaborative working through better information exchange, and as a part of the process Geomatic/Land Surveyors are not immune from the changes. Terrestrial laser scanning has been proscribed as the preferred method for rapidly capturing buildings for BIM geometry. This is a process change from a traditional measured building survey just with a total station and is aided by the increasing acceptance of point cloud data being integrated with parametric building models in BIM tools such as Autodesk Revit or Bentley Architecture. Pilot projects carried out previously by the authors to investigate the geometry capture and modelling of BIM confirmed the view of others that the process of data capture with static laser scan setups is slow and very involved requiring at least two people for efficiency. Indoor Mobile Mapping Systems (IMMS) present a possible solution to these issues especially in time saved. Therefore this paper investigates their application as a capture device for BIM geometry creation over traditional static methods through a fit-for-purpose test.

The documentation of heritage buildings is the preliminary action to deal with any problem related to the built heritage. The procedure of documentation requires a very diverse range of data (quantitative and qualitative) to be obtained and investigated in order to produce an accurate digital representation of the building. This type of work of data capture and interpretation is often conducted in isolation by different stakeholders and for a range of purposes, leading to a lack of communication between different data types, repeated effort and incomplete documentation. Heritage Building Information Modelling (H-BIM) is set to play a key role in the digital documentation of heritage buildings, as it can combine quantitative and qualitative data and facilitate the integration of different stakeholders and specialised data into the digital management of the different phases of dealing with heritage buildings. This paper aims to review the multitude of data types that could be included in the documentation and investigation process of the built heritage, in order to assess the breadth and depth by which heritage buildings can be documented. Four main categories that span the whole documentation data areas are being suggested which vary from outer geometry surveys, to subsurface materials and structural integrity investigations, to data concerning the building performance, as well as the historic records concerning the building’s morphology over time, which can help to create a more in-depth knowledge about the heritage building’s status and performance and can create a solid base for any required restoration and retrofitting processes (Khalil and Stravoravdis 2019a).