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Der vorliegende Band präsentiert ausgewählte Beiträge des 5. IAA Symposium on Small Satellites for Earth Observation. Die von der International Academy of Astronautics (IAA) mit Sitz in Paris organisierte Tagung fand vom 4.-8. April 2005 in Berlin statt. Gastgeber war das Deutsche Zentrum für Luft- und Raumfahrt , Berlin. The biennial IAA Symposium on Small Satellites for Earth Observation provides a forum for scientists, engineers and managers to exchange information about planned and on-going programs and missions, and present new ideas, covering small satellite mission objectives as well as technology and management aspects for dedicated earth observation satellites. This volume presents selected contributions of the 5th IAA Symposium on Small Satellites for Earth Observation, April 4 - 8, 2005, organized by the International Academy of Astronautics (IAA), Paris, France, and hosted by the German Aerospace Center (DLR), Berlin, Germany.

Artificial satellites --- Artificial satellites in remote sensing --- Earth observation. --- Small satellite.

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In the near future, it is expected to have an increased number of satellites with hyperspectral imager instruments in orbit. Consequently, in the context of an internship and a Master’s thesis performed in Liège Space Center (CSL-Acronym in French) it has been proposed to model a hyperspectral instrument for Earth observation (HIEO). Indeed, a few models of hyperspectral devices from satellite imaginary have been founded and none of them provides a clear estimation of the photon-electron energy nor its SNR (Signal to Noise ratio) transfer from a standard scene until reaching the detector. In order to reach this objective, three modulus were built; the scene, the optical-mechanical system and the photon-detector. This project aims to build and implement from scratch a radiometric model of a hyperspectral instrument for Earth observation, using key data parameters (KDP) for the scene module, optical module and detector module , in the narrow region VNIR (Visible and Near Infrared domain from 400 nm to 1100 nm).

It was found that the modeled optical-detector system convert a tiny amount of photons into electrons. Furthermore, higher values of SNR (>100) were found in the region between 500 nm to 900 nm. Moreover, the SNR drastically drops towards the extremes of the spectrum. In conclusion, the relation signal noise has a non-linear relation between the grating efficiency, quantum yield and the quantum efficiency. Thus, futures studies could improve the prediction of these parameters to have better data for the correction of hyperspectral radiance profiles.

Hyperspectral Instrument --- Earth Observation --- SNR --- Radiometric model --- Satellite --- Ingénierie, informatique & technologie > Ingénierie aérospatiale

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Earth Observations (EO) encompasses different types of sensors (e.g., SAR, LiDAR, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO information have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works.

LiDAR --- InSAR --- remote sensing --- earthquake --- UAV --- landslide --- land subsidence --- earth observation --- surface displacement --- geohazards --- deformation --- optical --- damage assessment

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This work introduces the state-of-the-art for very-high resolution Earth imagery from space, and the position of the Veoware startup in this sector. 

Earth observation has never been so intense than now. Many private actors emerge with even better images than before and with specialized and innovative web services. The growing interest for smaller satellites at a more affordable cost has driven these players to enter the market and propose new products and services to customers. The need is justified by many clients, who want to monitor frequently areas of the Earth with a high resolution. Applications can be transport vehicles counting to assess economic trends or insurance claims, trade intelligence to get a picture of the global economy or urban planning for example. Because of the huge amount of data created, powerful algorithms are necessary. Thereof the artificial intelligence is now a fully integrated part of space imagery. It helps to perform pattern recognition automatically for example. 

In this report we are interested in the following question: how will Veoware evolve in the Earth observation market? In particular some hints are proposed as to develop added value services with artificial intelligence. 

Veoware evolves in this environment and propose competitive solutions on the market. In particular the founders are developing a more agile satellite that is able to shoot in between the clouds, blank pixels that the customer does not want to pay for. Together with a flexible service offer and disruptive technology, the startup can keep an advantage in the competitive environment.

space industry --- earth observation --- very-high resolution --- corporate strategy --- artificial intelligence --- Sciences économiques & de gestion > Stratégie & innovation

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Achieving the 17 UN Sustainable Development Goals (SDGs) requires accurate, consistent and cost-efficient data. The papers in this book set out some of the frontiers regarding the use of Earth Observation (EO) data derived from satellites to help populate sustainable development indicators. It sets out the current challenges and opportunities in the field along with some case studies from around the world illustrating applications, such as exploring the use of EO for tracking SDG indicators using population grids to assessing resilience to extreme events such as flooding. Likewise, it covers diverse approaches that offer insights and guidance on environmental land management, desertification and support for evaluating education from space.

earth observation --- end-users --- environmental management --- land use --- Brazil --- Sustainable Development Goals --- hazards --- Earth observations --- remote sensing --- demography --- urbanization --- gridded population --- very high resolution satellite data --- habitat suitability --- habitat assessment --- Environmental Land Management --- monitoring --- verification --- reporting --- soil organic carbon --- soil organic matter --- Earth Observation --- SDGs --- indicator type --- data challenges --- UN sustainable development goals --- education --- socio-economic --- overcrowded schools --- vulnerability --- flooding --- Earth Observation (EO) --- Google Street View (GSV) --- climate change --- uncertainty evaluation --- desertification --- global change --- Earth observation --- planetary measurement --- Land Degradation Neutrality