<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

towards disruptions in earth observation new earth observation systems and markets evolution possible scenarios and impacts

Abstract This paper reviews the trends in Earth observation (EO) and the possible impacts on markets of the new initiatives, launched either by existing providers of EO data or by new players, privately funded. After a presentation of the existing models, the paper discusses the new approaches, addressing both commercial and institutional markets. New concepts for the very high resolution markets, in Europe and in the US, are the main focus of this analysis. Two complementary perspectives are summarised: on the one hand, the type of system and its operational performance and, on the other, the related business models, concepts of operation and ownership schemes. Until now, Earth observation systems for the most critical institutional needs are mainly dedicated assets owned and operated by governments or public organisations, often at national level. Even in the case of dual use missions, the governmental and commercial operations are in general fully segregated for the very high resolution satellites. Recent evolutions could affect this paradigm. Firstly, the increased performance of commercial satellites has a high degree of convergence with defence needs: 25–30 cm resolution is now the benchmark or at least a very short term target for commercial missions. The second evolution is the development of hybrid procurement schemes, combining proprietary missions and data buy framework contracts, partly triggered by the budgetary constraints of public customers, some failures in the execution of large spy satellites contracts and by the willingness to foster the competitiveness of industry on the export market. New space is another trend, which is more disruptive. This trend begun in the Silicon Valley and spread worldwide, arousing our expectations, sometimes excessively. This new model involves not only start-ups but also big web actors with substantial investment capacity. Both aim to transforming space into a commodity, taking benefit from the convergence between Information technology and EO. Beside the massive constellations for broadband Internet access, some initiatives have been launched for Earth observation markets, targeting high resolution and high revisit. Last but not least, more and more countries, the newcomers, invest in their own EO capacity, confirming the soft power dimension of space but also opening new opportunities for international or regional cooperation. As many unpredictable events may occur, even in a short time frame, the last part of the paper has a prospective dimension. Based on market trends and industrial stakes, it discusses the realism and likelihood of possible scenarios and identifies their impacts on the EO landscape and the main stakeholders involved, in particular in Europe: – The governmental and institutional actors, using Earth observation data for their operational missions, with an evolving balance between sovereign assets and external services. – The commercial operators of very high resolution satellites, with the new market opportunities and the possible emergence of worldwide champions. – The satellite manufacturers and their competitiveness. – The role of nations and space agencies, including the non-dependence or national sovereignty and international cooperation dimensions. Based on the comparison of three "radical" scenarios, the conclusion shows that there are opportunities for service providers and satellite manufacturers. Even without clear answer to the future industrial, technical and political structure of EO systems, relevant indicators to be monitored during the next three-five years are identified. The last section focuses on Europe and the role of institutions in order to support European champions and small and medium companies in the new worldwide competition

Accuracy comparison of Pléiades satellite ortho-images using GPS device based GCPs against TerraSAR-X-based GCPs

Conducting single frame orthorectification on satellite images to create an ortho-image requires four basic components, namely an image, a geometric sensor model, elevation data (for example a digital elevation model (DEM)) and ground control points (GCPs). For this study, orthorectification entailed the use of a single scene Pléiades primary panchromatic image, applying the Pléiades rigorous geometric model, utilising a high-quality 2 m DEM and using GCPs that were acquired from two different collection methods. The application of these different GCPs to the execution of orthorectification encompassed the aim of this paper, which was to investigate and compare the positional accuracies of ortho-images under two scenarios. Firstly, GCPs were manually collected through fieldwork utilising a Trimble GeoExplorer 6000 series handheld GPS device and secondly, by utilising TerraSAR-X based GCPs that were acquired from Airbus Defence and Space. The objective of this study was to determine the geolocation accuracy of a high-resolution satellite ortho-image when different types of ground control are used. This required the execution of two orthorectification tests where only the type of GCPs differed. The results of these tests were interesting since it highlighted the difference in positional accuracy when utilising various sources of ground control to perform orthorectification on satellite imagery. The comparison results showed that utilising the manual GCPs produced a better positional accurate ortho-image as opposed to using the TerraSAR-X based GCPs. Nonetheless, the TerraSAR-X based GCPs still produced a sub 2 m accurate ortho-image, which is more than sufficient for the production of most geospatial products.Keywords: orthorectification, digital elevation model (DEM), ground control point (GCP), high-resolution satellite imagery, TerraSAR-X based GCPs, WorldDEM™, Airbus Defence and Spac

Summary of the 2017 South Southeast Research Initiative (SARI) Agricultural Workshop

South/Southeast Asian countries are growing rapidly in terms of population, industrialization, andurbanization. As a result of this growth, one of the key policy challenges facing the region is foodsecuritythat is, those conditions when all people, at all times, have physical and economic access tosufficient, safe and nutritious food that meets their dietary needs and food preferences for an active andhealthy life.1 Although total food production has increased in the region since 1960 due to land areahaving been converted to agricultural use, more recently it has decreased, mostly due to loss ofproductive agricultural land due to urbanization and industrial development. Furthermore, the region isexperiencing variability in the timing of the monsoon and extreme weather events, resulting in droughtor flooding, which impact agricultural production. Monitoring crop production in a timely manner isessential to predict and prepare for disruptions in the food supply. To achieve such timely monitoringrequires improved and uptodate information on agricultural landuse practices.Although there has been significant progress in remote sensing and geospatial technologies over thepast few decades, there has been little emphasis placed on developing robust methods for operationalmapping and monitoring of areas devoted to crops. In South/Southeast Asia generally, most mappingefforts to date have focused on the broader classification of land cover types and generalized croplandareas into a single or limited number of thematic classes. Only a few countries have access to uptodatecrop type information. There is an urgent need to make this nearrealtime information morereadily available to stakeholders and to enhance national and regional operational systems formonitoring agricultural crops.

Fusion of Interferometric SAR and Photogrammetric Elevation Data

Neurology & clinical neurophysiolog

Gaia Data Release 1: Summary of the astrometric, photometric, and survey properties

At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. We summarize Gaia DR1 and provide illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Gaia DR1 consists of: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the Hipparcos and Tycho-2 catalogues and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set,consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ~3000 Cepheid and RR Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas/yr for the proper motions. A systematic component of ~0.3 mas should be added to the parallax uncertainties. For the subset of ~94000 Hipparcos stars in the primary data set, the proper motions are much more precise at about 0.06 mas/yr. For the secondary astrometric data set, the typical uncertainty of the positions is ~10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ~0.03 mag over the magnitude range 5 to 20.7. Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data