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Lightning Talks

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2017-09-25 16:50 - 2017-09-25 18:00

Paper 106 - Session title: Lightning Talks

17:32 3D Cave Mapping Applied to the "CAVES" and "PANGAEA" ESA Programs

Santagata, Tommaso (1); Sauro, Francesco (1,2); De Waele, Jo (1,2); Bessone, Loredana (3) 1: La Venta Esplorazioni Geografiche, Italy; 2: Department of Biological, Geological and Environmental Sciences, University of Bologna; 3: Directorate of Human Space Flight and Operations, European Space Agency, Linder Höhe, 51147 Köln, Germany

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The PANGAEA (Planetary Analogue Geological and Astrobiological Exercise for Astronauts) and CAVES (Cooperative Adventure for Valuing and Exercising human behaviour and performance Skills) ESA training courses are designed to prepare European astronauts to become effective partners of planetary scientists and engeneers in designing for the next exploration missions and to give them a solid knoweledge in the geology of the solar system studying several caves, especially lava tubes, through geolgical field training courses and tests of new technologies. In recent years we have seen a remarkable developments of 3D mapping methods for cave surveys as cameras and softwares for digital photogrammetric and instruments as laser scanning or mobile mapping tools. During the 2016 CAVES training course in Sardinia (Italy), photogrammetry has been widely used in order to give astronauts a basic knoweledge of this 3D mapping technique and as a toll that can be used for documenting the surfaces of other planets during field geology activities. Photogrammetry allows to acquire metric data through the acquisition and analysis of a couple of frames that can be obtained using standard digital cameras. In 2017, laser scanning and UAV'S (Unmanned Aerial Vehicles) photogrammetry will be used during the PANGEA course to test new instruments to obtain 3D maps of the Corona lava tube on the Canarian island of Lanzarote (Spain) with the goal to realize virtual models that can be used to test rovers and to plan future space analogue missions. In both cases, the 3D models realized with photogrammetric and laser scanning technologies were subsequently analysed to obtain information about size, volume, shapes and morphologies of the detected surfaces. The aim of this work is to describe methods and technologies used during these tests and the results obtained.

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Paper 109 - Session title: Lightning Talks

17:35 A set of Software Tools supporting EO Satellites for Orbit and Instrument Swath Coverage

Pinol Sole, Montserrat; Zundo, Michele ESA/ESTEC, Netherlands, The

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This paper presents the software applications for satellite orbit and instrument swath visualization distributed by the ESA-ESTEC EOP System Support Division to users part of the ESA Earth Observation Earth Explorer and Copernicus satellites community. The ESOV NG [REF 1] and EOMER [REF 2]) software applications can be used to perform mission analysis activities related to instrument swath coverage over regions of interest and ground station contact. These tools can and have been used in the preparatory feasibility studies (e.g. to analyse coverage and revisit time), to support downlink and ground station visibility analysis as well as support to Calibration and Validation activities e.g. to plan on-ground campaigns during satellite commissioning or scheduling of ground transponders. The Earth observation Swath and Orbit Visualization (ESOV NG) is a 2D orbit and swath visualization application, delivered with a predefined set of missions (Aeolus, Biomass, Cryosat , EarthCARE, MetOp-SG, Sentinel 1, 2, 3, 5p, 6, SMOS, SWARM), although it is possible to configure user-defined satellites. This tool is multi-platform, available for Mac OS X, Linux and Windows. EOMER (Earth Observation Mission Evaluation and Representation) is a Windows application for multi-satellite and swath visualization in 2D/3D, tailored to ESA Earth Observation missions (currently supporting Aeolus, Biomass, MetOp-SG, Sentinel 1, 2, 3, 5p). Both ESOV NG and EOMER applications allow the user to visualize satellite orbit ground-tracks and instrument swaths, and to calculate ground station visibility passes, times of overpass a given ground point and times when an instrument swath overlaps with a given region of interest. Regarding this last point, a dedicated command line executable program (ZoneOverPass [REF 3]) is available to obtain overpass tables of a given satellite ground-track or instrument swath over an area of interest. Finding opportunities of observations over a given area may be useful to search relevant time-tagged products or plan future on-ground campaigns. Further exploiting these features, the InstrCollocation tool [REF 3] provides a mechanism to identify collocation opportunities between two different instruments. It would benefit users involved in instrument calibration activities or interested in combining data from different types of products, acquired over the same geographical area within a given period of time between observations. The output information produced by the ZoneOverPass and InstrCollocation tools are provided in both tabular and graphical formats. The coherence and accuracy of the orbital and geometrical calculations within ESOV NG application and the ZoneOverPass and InstrCollocation tools is ensured by the use of embedded Earth Observation CFI Software libraries (EOCFI SW). The libraries are used to obtain orbit ground-track, instrument swath, time passes over selected area of interest or ground. The EOMER application instead makes use of the SatX and GanttX components developed by Taitus to support respectively the orbital calculations and its timeline visualisation. The use of common interfaces (orbit files, swath files, SCF segments export format from ESOV NG, KML Google Earth) is a key point to facilitate sharing the input data and the comparison of the output results across the various software applications. REFERENCES [REF 1] ESOV website: http://eop-cfi.esa.int/index.php/applications/esov [REF 2] EOMER website: http://eop-cfi.esa.int/index.php/applications/eomer [REF 3] ZONE_OVERPASS / INSTRUMENT_COLLOCATION website: http://eop-cfi.esa.int/index.php/applications/tools

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Paper 127 - Session title: Lightning Talks

17:17 EarthStartsBeating: an innovative Earth Observation divulgation project

Palumbo, Giovanna; Tarchini, Salvatore; Cerreti, Fiammetta; Cadau, Enrico Giuseppe; Iannone, Rosario Quirino; Marino`, Fernando SerCo S.p.a, Italy

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This abstract proposes and describes a project aimed at the divulgation of scientific topics, mainly written for a non-expert audience. The outreach activities are performed through the writing of articles published on a website named EarthStartsBeating (https://earthstartsbeating.com/) and launched since early 2015. In line with the Copernicus free and open data access idea, EarthStartsBeating is intended to present and promote the multiple exploitation areas of the Copernicus Sentinels Earth Observation (EO) data, reaching the far-end users, i.e. the European citizens, drawing their attention to a broader usage of Earth Observation data. The proposed articles cover therefore various scientific disciplines and simple curiosities about the Earth natural/human processes through a weekly publication of Sentinels' eye-catching products elaborations. The publication of EO images fosters the understanding of subjects such as geological and atmospheric phenomena, including also the anthropic changes caused by the human activities. The main goal of the contributors is thus to work on communication and storytelling, approaching the information with a direct and simple style without neglecting the main scientific principles of the Remote Sensing. EarthStartsBeating website is structured in four thematic sections: • The 'Sentinels' section, which shows EO images of natural and anthropic phenomena, following the most significant events occurring throughout the Earth. The relevant material is then classified by three tags corresponding to the name of the Sentinels data exploited for the elaborations (i.e. Sentinel-1, Sentinel-2, and Sentinel-3). In this section, events like hurricanes, floods, forest fires, volcano eruptions are treated. • The 'Exploration' section is meant to re-experience the paths of the various historical explorers thanks to the eyes of the Sentinels. The first story tells about some stages of James Cook's first journey that led to the exploration and discovery of a great part of the South Pacific Ocean and Australia. • The 'Expert User' section is a more technical area where simple and basic scripts written in java/python where technical articles about the elaboration of EO images are reported. • The 'Interesting facts' section collects analysis done with data coming mainly from ESA not-Sentinels missions like PROBA-V. We present some examples of the main exposed themes, demonstrating that the proposed website represents an attractive tool not only for gathering information but also for the development of a forum in which to discuss the most relevant aspects linked to our Planet.

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[Authors] [ Overview programme]
Paper 130 - Session title: Lightning Talks

16:50 Complex SAR Data Processing For Evaluation Of Environmental Changes

Frasheri, Neki; Beqiraj, Gudar; Bushati, Salvatore Academy of Sciences of Albania, Albania

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Past experiments with Sentinel-1 interferograms applied in PreAdriatic Depression area in Albania gave some intriguing results, characterized by lack of fringes in southern part and dominance of fringes in northern part but from images with 12 days if difference. Such results indicated a strong impact of land coverage in interferograms, making difficult the evaluation of possible subsidence in beaches of Adriatic Sea. In this paper we present results from Sentinel-1 interferograms based on different polarisations and comparison with land coverage features obtained from combination of coherence, intensity averages and intensity differences. Results show a strong impact of land coverage spatial and temporal variations, as well as new information on subsidence areas. Processing of Sentinel-1 images was done with ESA’s SNAP software, post-processing of resulting images with GIMP, appliicable in framework of citizen science as well.

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Paper 132 - Session title: Lightning Talks

17:38 Virtual Exploitation Environment Demonstration for Atmospheric Missions

Natali, Stefano (1); Mantovani, Simone (1); Santillan, Daniel (2); Triebnig, Gerhard (2); Hirtl, Marcus (3); Lopes, Cristiano (4) 1: SISTEMA gmbH, Austria; 2: EOX IT Services GmbH, Austria; 3: Zentralanstalt für Meteorologie und Geodynamik, Austria; 4: ESA ESRIN, Italy

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The scientific and industrial communities are being confronted with a strong increase of Earth Observation (EO) satellite missions and related data. This is in particular the case for the Atmospheric Sciences communities, with the upcoming Copernicus Sentinel-5 Precursor, Sentinel-4, -5 and -3, and ESA’s Earth Explorers scientific satellites ADM-Aeolus and EarthCARE. The challenge is not only to manage the large volume of data generated by each mission / sensor, but to allow users to analyze the data streams in near-real-time and for long term monitoring tasks. Creating synergies among the different datasets will be key to exploit the full potential of the available information. As a preparation activity supporting scientific data exploitation for Earth Explorer and Sentinel atmospheric missions, ESA funded the “Technology and Atmospheric Mission Platform” (TAMP) [1] [2] project, with the twofold aim of demonstrating (1) that multiple data sources (satellite-based data, numerical model data and ground measurements) can be simultaneously exploited by users (mainly scientists), and (2) that a fully virtualized environment (Virtual Research Environment, VRE) that allows avoiding downloading all data locally, and retrieving only the processing results is the optimal solution. With the “Virtual Exploitation Environment Demonstration for Atmospheric Missions” (VEEDAM) project, the concept of VRE is further extended: a Jupyter notebook interface has been deployed aside of the data, providing the users with all data access and processing tools already available within the TAMP platform as libraries for further exploitation; thus the user can exploit the potentialities of the platform, including the freedom of writing and running own code directly on the VRE; moreover the user has the possibility to interact with other existing VREs using external data and processing resources. Finally the interactive 3D visualization capabilities of TAMP have been further evolved providing geographic (latitude, longitude, height) slicing capabilities. This interactive poster presents the VEEDAM capabilities, allowing the attendants of EO Science 2.0 to directly experience both the data visualization and exploitation potentialities of TAMP. [1] TAMP platform landing page http://vtpip.zamg.ac.at/ [2] TAMP introductory video https://www.youtube.com/watch?v=xWiy8h1oXQY

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[Authors] [ Overview programme]
Paper 142 - Session title: Lightning Talks

17:20 EO with Sentinel2A: a school-work path way experience

Amici, Stefania (1); Stelitano, Dario (1); D'addezio, Giuliana (1); Vento, Paola (2); Acocella, Francesca (2); Giorgetti, Giorgio (2); Rocchi, Giorgia (2); Sbrenni, Eleonora (2); Serenellini, Luca (2) 1: Istituto Nazionale di Geofisica e Vulcanologia; 2: Liceo Scientifico Stanislao Cannizzaro

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School path way experience known as alternanza scuola-lavoro (ASL) is an innovative learning-teaching module at Italian college schools. As detailed within the "Good School" law ( La Buona Scuola 107- 2015) it is aligned with the principle of open school. The idea is to anticipate the contact of students with working world providing them new skills and directions for future work choices within a sort of internship project with a private or public body. In this context Istituto Nazionale di Geofisica e Vulcanologia offers a list of projects within geophysical application. For the first time, researchers from INGV wanted to challenge college students on Remote Sensing to test their response and potential receptivity. The project, titled "Earth Observation with satellite: the case of burn areas" was selected by five students, here co-authoring, from Liceo Scientifico Cannizzaro in Rome. The school-work path way experience has been hold at INGV in Rome for a total of 40 hours (contact and not contact) during which the students have been guided to how to: • identify a problem • create an initial research questions • establish basic theoretical knowledge on satellite remote sensing • identify the algorithms suitable for solving the problem • select the satellite data (Sentinel2A) and the process tool (SNAP) • analyze and interpret data producing a scientific report As test case, two poorly characterized wildfires occurred in the area of Aidomaggiore (on 02 July 2016) , and Scano di Montiferro (on 24 August 2016 ) Sardinia Italy were selected. Images acquired by Seninel2A over the area were selected and used to produce NDVI and NBR map at 20m spatial resolution. The results have been summarized by students in a scientific report. Both students and researchers and professor as well considered the experience very positive and perhaps we have initiated the concept that "Junior Remote Sensing specialist" can be potentially extended to college students

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Paper 145 - Session title: Lightning Talks

16:53 Trend analysis of vegetation index in different land use land cover (Case study: Iran).

Fakharizadehshirazi, Elham (1,2); Sabziparvar, Ali akbar (2); Sodoudi, Sahar (1); Fallah hasanabadi, Bijan (1) 1: Free university of Berlin, Germany; 2: Bu-Ali Sina University,Iran

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Vegetation Is an Essential Element of the Land Surface System That Links Climate Change. Both Environmental and Anthropogenic Factors Are Effected on Vegetation Dynamics. There Are Several Remote Sensing Indices for Indicating Vegetation. Normalized Difference Vegetation Index (NDVI) Is a Common and Widely Used Index. NDVI Is Highly Sensitive to Ecosystem Conditions; Therefore, It Can Be Representative of Detecting Changes in Vegetation Activity. The Visible and near Infrared Bands on the Satellite Multi Spectral Sensors Have Monitored the Greenness of Vegetation. In This Research, We Present the Trend Analyses of 31 Years (1982-2012) Remote Sensing Vegetation Index Based on Long-term Time Series of NDVI Observation from the Global Inventory Modelling and Mapping Studies (GIMMS) Group Derived from NOAA AVHRR Imagery With 0.08 Degree Spatial Resolution over Iran (40 T0 65 East, 25- 45 North). Iran Has a Dry Climate Characterized by Long, Hot and Dry Summers. NDVI Has a Strong Seasonal Cycle, and in This Research, We Only Used the Mean Growth Season NDVI. We Depict Greening (NDVI Increase) and Browning (NDVI Decrease) Regions. NDVI, an Indicator of Vegetation Growth and Coverage, Has Been Described the Characteristics of Land Use and Land Cover. In This Research, We Also Have Investigated NDVI Changes in Different Land Use Land Cover to Find out the Relationship Between Land Use Land Cover and NDVI Trend. The Existence of Positive Autocorrelation in the Time Series Increases the Probability of Detecting Trends When Actually None Exist, and vice Versa. In This Study, the Effect of Autocorrelation on the Variance of the Mann-Kendall Trend Test Statistic Is Considered, Therefore We Have Used Modified Man-Kendall Method to Do Trend Analyses. According to the Results, Almost Regions Have Negative NDVI Trend and It Is Harmonic with Land Use Land Cover in Some Cases.

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[Authors] [ Overview programme]
Paper 161 - Session title: Lightning Talks

16:59 Crustal structure beneath Mt Cameroon region derived from gravity data

Ngatchou Heutchi, Evariste University of Yaounde 1, Cameroon

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In the present study, gravity information is available for improving the understanding of the crustal structure and its relationship to regional tectonics environment beneath the large volcanic system called Mt Cameroon. The multi-scale wavelet analysis method is applied to separate the gravity fields. The logarithmic power spectrum method is used to estimate different depths of the gravity field source. The results show that the crustal structure is very complicated beneath Mt Cameroon area with the crustal density exhibiting lateral inhomogeneity. The lateral discontinuities of density structure causes undulations of the gravity anomaly field whose complexity can be an indicator of past crustal instability. The Buea-Tiko region appears to be the most tectonic active zone in the Mt Cameroon area. The upper and middle crusts consist of many small-scale faults, uplifts and depressions. In the lower crust, these small-scale tectonic units disappear gradually, and replaced by large-scale units. The gravity anomalies in upper and middle crusts are correlated with geological and topographic features on the surface. Compared with the crust, the structure is relatively simple in uppermost mantle. The earthquakes occurred predominantly in upper and middle crusts, their epicenters are limited in transitional regions between high gravity anomaly and low gravity anomaly. The earthquake occurrence as well as complicated gravity behavior may be related to the Upwelling of high density magmatic materials and asthenosphere heat flow materials beneath Mt Cameroon. The overall results, in a good agreement with previous findings, show the performance of the wavelet-based filter in the possibility of getting a multi-resolution analysis and the study of structures using gravity data.

[Authors] [ Overview programme]
Paper 168 - Session title: Lightning Talks

17:02 Deep Learning Techniques For The Information Extraction From Large Earth Observation Data

Licciardi, Giorgio (1,2); Dalla Mura, Mauro (2); Chanussot, Jocelyn (2,3) 1: Research Consortium Hypatia, Italy; 2: Gipsa Lab Grenoble, France; 3: University of Iceland, Iceland

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Creation of valuable content from large and growing volume of EO derived data is a challenge for Research organizations, governments and companies. Several approaches have been proposed in the literature for the information-extraction from EO data, among which Deep learning (DL) algorithms have recently become a hotspot in the machine-learning area and have been introduced into the geoscience and remote sensing (RS) community for RS big data analysis. With the term Deep Learning is intended a set of machine learning systems (usually neural networks) with multiple layers. Deep learning involves a class of models, which try to hierarchically learn deep features of input data with very deep neural networks, typically deeper than three layers. The network is first layer-wise initialized via unsupervised training and then tuned in a supervised manner. In this scheme, high-level features can be learned from low-level ones, whereas the proper features can be formulated for pattern classification in the end. Thus, the use of more than three layers permits to extract more abstract, invariant features of data, and have been shown to yield promising performance in many fields of remote sensing including classification or regression tasks. By analyzing the practical demands in Earth Observation applications, in this paper we show how the use of deep learning approaches can be used anywhere in remote sensing analysis: from pre-processing to the recent challenging tasks of high-level semantic feature extraction and RS scene understanding. Different examples showing the use of DL techniques applied to different stages of EO data processing will be presented. In a first example, it will be shown an application for the spectral compression and the noise suppression of hyperspectral images [1][2]. Then, an example of how the DL can extract relevant information from data acquired from different sensors will be presented [3][4]. Finally, a large time-series dataset of meteorological images is processed with DL in order to extract relevant features [5]. REFERENCES [1] G. Licciardi, J. Chanussot, A. Piscini, “Spectral compression of hyperspectral images by means of nonlinear principal component analysis decorrelation”, ICIP 2014, 27-30 october 2014, Paris, France. [2] G. Licciardi, J. Chanussot, ‘Nonlinear PCA for visible and thermal hyperspectral image quality enhancement”, IEEE Geoscience and Remote Sensing Letters, Volume 12, issue 6, pages 1228-1231. 2015. [3] G. Licciardi, M. M. Khan, J. Chanussot, A. Montanvert, L. Condat, C. Jutten, “Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction”, EURASIP Journal of Advances in Signal Processing, 2012, 2012:207 [4] G. Licciardi, R. G. Avezzano, F. Del Frate, G. Schiavon, J. Chanussot “A Novel Approach to Polarimetric SAR Data Procesing Based on Nonlinear PCA”. Pattern Recognition, Volume 47, issue 5, pp: 1953-1967, 2014. [5] G. A. Licciardi, R. Dambreville , J. Chanussot, S. Dubost “Spatio-temporal pattern recognition and nonlinear PCA for global horizontal irradiance forecasting”, IEEE Geoscience and Remote Sensing Letters, Volume 12, issue 2, pages 284-288, 2014.

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[Authors] [ Overview programme]
Paper 171 - Session title: Lightning Talks

17:05 Contribution of the New satellites (Sentinel-1, Sentinel-2 and SPOT-6) to the Coastal Vegetation Monitoring in the Pays de Brest (France).

Talab Ou Ali, Halima; Niculescu, Simona LETG UBO, France

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The significant economic, societal and environmental changes that have occurred worldwide and at different regional levels account for the strong interest that scientists are currently showing in issues related to coastal land cover changes. The intense urban extension, the development of its related infrastructures and town planning, the deep transformations of agricultural practices and the increasingly intensive farming and exploitation of natural resources have all led to considerable changes in the coastal ecosystems. Our paper aims mainly at finding a methodological solution applicable for the processing of several heterogeneous coastal ecosystem parameters, which would allow their description in their full complexity. This complexity is the result of both local variations of ecological conditions and different anthropogenic factors having direct and indirect influences on plant communities’ dynamics of these ecosystems. Although understanding the dynamics which governs the changes occurring in these “patchwork” areas is still a difficult task (natural evolution of plant communities, human activities,…), we begin our paper by an interferogram calculation method of the main types of vegetation to achieve the coherence of a multi-temporal Sentinel-1 radar image series, in SLC format (C band, VV and VH polarization), between 2015 and 2016. We then proceed to calculating radar backscatter coefficient based on Sentinel-1 images in GRD format. The approach adopted relies on analysis of relations between state of different vegetation ecosystems and radar response, while establishing a link between the physical coherence responses and backscatter coefficients with the vegetation parameters (phenology, structure…) along with soil humidity due to precipitations. Assuming that backscatter coefficient may be considered suggestive of degree of vegetation development and of its various phenological stages, we were thus able to determine the different temporal patterns of the various classes of coastal vegetation. In addition to the spectral and spatial dimensions, the time component is a priceless source of information in terms of plant resource monitoring and management and land cover dynamics follow-up. Our study of radar image series collected especially during the growth stage enables us to improve the recognition of the main types of vegetation by relying on the temporal dynamics of the various classes of vegetation. The temporal analyses have proven that there is not only one date which would allow a satisfactory characterization of all vegetation classes. The temporal dimension, represented by the seasonal dynamic, is thus a vital component of any thorough inventory and analysis of the coastal vegetation ecosystems. A combination of coherence and intensity images complements the Sentinel-1 radar image processing, since the use of the two images may be employed for land cover classification. Second, our findings concern combinations of data collected and recorded by Sentinel- 1 using different optical satellite sensors (Sentinel-2 and Spot-6) to improve the accuracy of recognition and mapping of the main classes of vegetation in the Pays de Brest, going as plant formation. For this first stage, the findings show average accuracy levels for SPOT-6 and Sentinel-2 image classification. Furthermore, the combination of the three types of data insures excellent multi-sensor classification accuracy (higher than 92%).

[Authors] [ Overview programme]
Paper 185 - Session title: Lightning Talks

17:08 Evaluation of multi-source Earth Observation data exploitation for monitoring intensive crop farming.

Arcorace, Mauro; Delgado Blasco, Jose Manuel; Cuccu, Roberto; Sabatino, Giovanni; Rivolta, Giancarlo Progressive Systems Srl, Parco Scientifico di Tor Vergata, 00133, Rome, Italy

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The exploitation of satellite Earth Observation (EO) data has already played key roles in the agricultural sector where remote sensing contributions are traditionally strong. EO data can be used in fact to monitor fields in the cropping season, to estimate crop production loss due to drought or excessive rainfall, to estimate the humidity of the soil, to identify change in type of vegetation and to monitor deforestation. In this domain, we are exploring new capabilities on multi-source EO data exploitation for precise farming applications. The main goal of this applied research is to build a dedicated and customizable portfolio of services that can be easily adopted by private or public sector stakeholders to support agricultural needs at local scale. Having a versatile EO-based agricultural monitoring service in place would be, in fact, a key instrument to provide valuable and reliable information on crop conditions, promote the use of EO data within the industry, address crop field monitoring needs over extensive rural areas and guide local stakeholders to identify yield and production losses. A preliminary study over selected sites in Italy has been carried out to demonstrate the feasibility of prototypical tools for agricultural monitoring. In particular, in order to evaluate the applicability of remotely sensed indicators to enable cost reduction of agricultural activities, multiple investigations have been performed over different types of crop field. Thanks to the Google Earth Engine cloud-based platform, the information derived from Earth Observations, such as multi sensor (e.g. Sentinel-2, Landsat-8, ProbaV) low and medium resolution time series analysis, have been used to monitor crop growth dynamics and to better understand environmental behaviours meaningful for agriculture. First results, have been shown that by means of these satellite based measurements it is possible to identify a correlation with the crop season of different cultivation fields and to analyse other relevant features. For example, thanks to an integrated analysis of vegetation and water indexes, it is possible to assess crop field status and to estimate harvesting period and annual irrigation schedule. Furthermore, multi temporal remote sensed surface temperature analysis, retrieved from Landsat 8 Thermal Infrared (TIRS) are also useful to identify seasonal temperature fluctuation across the years. Besides creating value for the farmers, such a type of analysis can be used for other purposes as well, e.g. for measuring economic loss in case of disaster events. Precise farming is expected to be widely adopted by the agricultural community in the near future, as the continuously growing remote sensing data sources (satellite, UAV) and ground observations will enable the development of new ad-hoc services. This work is intended to pave the way towards future implementations of support services for agricultural industry and farmers, providing a wide range of satellite-derived indicators for precise farming applications, such as crop disease identification, pollution monitoring, soil mapping and yield prediction. The results derived from this study are expected to provide supportive evidence of the potential value of the envisioned support services for local-scale applications.

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Paper 186 - Session title: Lightning Talks

17:23 High School Students and Sentinels’ Data: Our Experiment

Liberti, Gian Luigi (1); Ciotoli, Elisa (2); Bilhac, Marius (2); Liberti, Juliette (3); Capannolo, Edoardo (2); Ciobano, Rafaela (2); Picone, Massimiliano (2) 1: ISAC-CNR, Via Fosso del Cavaliere 100, I-00133, Rome, Italy; 2: Liceo Scientifico Statale "Louis Pasteur" V. Giuseppe Barellai, 130 - 00135 Rome, Italy; 3: Liceo Scientifico Statale "Isacco Newton" V.le Manzoni 47, 00185 Roma

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Within the frame of the recent introduction (Alternanza Scuola Lavoro www.istruzione.it/alternanza/index.shtml) in the Italian public school system of compulsory stages in private and public enterprises, the possibility that high school students could contribute actively to a scientific project was explored. About 30 high school students from the 3rd and 4th year (roughly 16-18 years old) from two Scientific High Schools in Rome, “Louis Pasteur” (www.liceopasteur.it) and “Isacco Netwon” (www.liceonewtonroma.gov.it), were involved in different phases of a study performed at the Institute for Atmospheric Sciences and Climate of the Italian National Research Council (ISAC-CNR www.isac.cnr.it). The study was done in response to the ITT Sea-ice cloud screening for Copernicus Sentinel-3 Sea and Land Surface Temperature Radiometer issued by EUMETSAT. The project required to produce Probability Density Functions (PDF) for a three classes (Clear Sky/Cloud/Sea Ice) Bayesian classification of the Sentinel 3 SLSTR data over polar oceans. Student were involved mainly in two different job tasks: first, they were asked to organize a set of relevant reviewed literature, about 140 among journal articles, Technical Reports and Algorithm Theoretical Basis Documents (ATBD), and to summarize the main information used for cloud-sea ice detection from previous studies. Secondly, their contribution consisted in selecting and documenting study cases, used as a reference dataset for validation and tuning of the PDF’s in different phases of their development. Job Organization: Different approaches for the job organization were tested, such as not only a tutor vs. students formation, but also a peer-to-peer one. The students had the possibility to work and to develop their abilities both at the work place and remotely (their school or their houses). Even if they could also work far from the tutor, there was an intense exchange of information. The study cases’ selection was based on the use of these tools: SNAP (step.esa.int), a Cloud area to share results and data, Microsoft Office. This required the students to become familiar with them. As far as SNAP is concerned, they learnt how to manage it mostly taking advantage of the online tutorials. Earth Observation (EO) data used in this project were Sentinel-3(A) SLSTR L1 (scihub.copernicus.eu) data and daily sea ice 1 km concentration charts (SEAICE_ARC_SEAICE_L4_NRT_OBSERVATIONS_011_002), based mainly on observations from SAR, including the one on board of Sentinel 1. Furthermore, some examples of obtained results will be shown and discussed. Some difficulties emerged during the time the project was carried out. They were not due to the tools or to the EO data but mostly to the novelty of the situation the students had to face. Their scholastic background revealed itself to be less important than a constructive attitude aimed at an efficient way to manage time and resources. In particular, the inability to, adequately, report the work done and to respect deadlines appeared as common weaknesses. Both students and project’s gained benefits will be discussed.

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[Authors] [ Overview programme]
Paper 202 - Session title: Lightning Talks

17:44 Grand Ethiopian Renaissance Dam break scenario and expected effects over the archaeological sites

Elshobaki, Mohamed (1); Elfadaly, Abdelaziz (2) 1: Università degli Studi dell'Aquila-Italy; 2: Università degli Studi della Basilicata-Italy

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The Nile River flows for 6,700 kilometres through ten countries in north-eastern Africa. It is classified as one of the longest river in the world. Two main tributaries supply the discharge of the Nile being the White, and the Blue Nile. The Blue Nile currently attracts more attentions due to the construction of the Grand Ethiopian Renaissance Dam Project (GERDP). Large debate from the downstream countries (Egypt) has feared the consequences of such project. The GERDP left us with a huge concern in case of failure. Therefore, we provide a full numerical simulation based on the Shallow water mathematical model which solved by TELEMAC-2D provides the necessary water flow information in case of the Dam breaking. Satellite images data includes Sentinel1 and DEM data is used to supply the initial and boundary conditions of the simulations. Overall aim, the extracted simulation data are used to assess the potential impact of the GERDP failure on the archaeological area along the banks. Detect the expected environmental risks should supply the decision-makers with understandable information to protect the cultural heritage sites. Tsunami waves are expected.

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Paper 205 - Session title: Lightning Talks

17:11 Lena Delta Water Bodies Mapping And Level Heights Determination Based On Remote Sensing Data

Volynetc, Aleksandr St. Petersburg University, Russian Federation

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Low-lying permafrost-dominated Arctic river deltas are particularly sensitive to climate variability. This sensitivity is dramatically expressed in landscapes changes because of permafrost degradation (thermokarst and thermoabrasion processes) and river-ocean interactions changes due to rivers run-off increase. As thawing of permafrost may lead to the release of great amount of green-house gases and acceleration of climate change, close monitoring of permafrost affected regions dynamics using remotely sensed data becomes a prominent instrument for analysis of climate variability. One of the main features of permafrost degradation is thermokarst - expressed in formation, growth, decreasing and vanishing of thermokarst lakes. Thus water objects quantity size and level change can be considered as important indicators for the water balance and for frozen ground mutability in corresponding areas. The region of interest of this study is situated in continuous permafrost zone Lena Delta, which is the largest delta in the Arctic region with an area exceeds 32 000 km². It includes about 60 000 lakes, most of them are impacted by thermokarst, and numerous branches of the Lena River. On the base of high resolution (5m) multi-year RapidEye satellite imagery was created a map of water bodies in the Lena Delta. The first step of mapping was preprocessing of satellite images, which includes atmospheric correction of obtained images, orthorectification and projection in geodetic coordinate system UTM 52N (zone of the eastern part of Lena delta) using software provided by PCI Geomatics. On the next step near-infrared channels of appropriate ones were superimposed on each other, with the condition based on suitable ground reflectance values, and a binary raster image of water bodies was obtained. Received raster was filtered using different methods to remove noises and then converted in vector scheme. Thus vector map of lakes and channels in the Lena Delta was obtained, which contains about 34 000 objects. This map was overlaid by footprints of laser altimeter on board of ICESat, provides an unprecedented set of global elevation measurements of the Earth, and water level heights of appropriate water bodies were estimated. As a result was received sufficiently detailed map of Lena Delta water objects with elevations of several lakes and inclinations of main river channels.

[Authors] [ Overview programme]
Paper 215 - Session title: Lightning Talks

17:26 Communication Duration With Low Earth Orbiting Satellite

Gupta, Lalit Poornima Institute of Engineering and Technology Jaipur, India

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Communication via satellite begins when the satellite is positioned in the desired orbital position. The satellite’s coverage area on the Earth depends on orbital parameters. Ground stations can communicate with LEO (Low Earth Orbiting) satellites only when the satellite is in their visibility region. The duration of the visibility and so the communication duration varies for each satellite pass at the ground station. For low cost LEO satellite ground stations in urban environment it will be a big challenge to ensure communication down to the horizon. The communication at low elevation angles can be hindered through natural barriers or will be interfered by man made noise. This paper discusses the variations of the communication duration between the ground station and LEO satellites and investigates if it is useful to support low elevation passes. For this paper data recorded at the Vienna satellite ground station within the Canadian space observation project “MOST” (Micro variability and Oscillations of Stars) are applied.

[Authors] [ Overview programme]
Paper 218 - Session title: Lightning Talks

17:14 Datacube Analytics for the Digital Earth: Challenges and Opportunities

Mantovani, Simone (1); Natali, Stefano (1); Barboni, Damiano (1); Steer, Adam (2); Evans, Ben (2); Hogan, Patrick (3); Baumann, Peter (4) 1: MEEO, Italy; 2: National Computational Infrastructure - The Australian National University, Australia; 3: NASA Ames Research Center, USA; 4: JACOBS University, Bremen, Germany

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Recently, the term datacube is receiving increasing attention as it has the potential of greatly simplifying “Big Earth Data” services for users by providing massive spatio-temporal data in an analysis-ready way. The Datacube Manifesto [1] provides a concise, crisp definition of datacubes, based on the consolidated experience of project partners in datacube modeling (query languages, architectures, standards development, …) and in operation of Petascale datacube services at some of data centers worldwide. A number of datacube-aware platforms and services have emerged that enable a new collaborative approach for analysing the vast quantities of satellite imagery and other Earth Observations, making it quicker and easier to explore a time series of image data stored in global or regional datacubes. In this context, the European Space Agency and European Commission H2020-funded projects ([2], [3]) bring together multiple organisations in Europe, Australia and United States to allow federated data holdings to be analysed using web-based access to petabytes of multidimensional geospatial datasets. The aim is to create and ensure that these large spatial data sources can be accessed based on OGC Web Coverage Service (WCS) and Web Coverage Processing Service (WCPS) standards. Unlike Web Mapping Service (WMS) which returns spatial data as an image or ‘static map’, WC(P)S returns data in its raw form, with its original semantics enabling further data processing or the building of web applications, while at the same time the data volume transferred is minimised. WCS provides access to the full range of geospatial data served from a web server and allows for requesting only a subset of the data. A WCS supports slice and trim operations, where either the data dimension (slice) or the data extent (trim) is reduced. WCPS is an extension of the WCS 2.0 core specification and allows the user to craft queries to be run on the data using a text based query language, similar to SQL. This allows the user to not only limit the data transfer to the area they are interested in, but also web-based, on-demand data processing. In this study, we provide an overview of the existing datacubes (EarthServer-2 datacubes, Sentinel Datacube, European and Australian Landsat Datacubes, …), how the regional datacube structures differ, how interoperability is enabled through standards, and finally how the datacubes can be visualized on a virtual globe (ESA-NASA WebWorldWind) based on a WC(P)S query via any standard internet browser. The current study is co-financed by the European Space Agency under the MaaS project (ESRIN Contract No. 4000114186/15/I-LG) and the European Union’s Horizon 2020 research and innovation programme under the EarthServer-2 project (Grant Agreement No. 654367). [1] The Datacube Manifesto (http://earthserver.eu/sites/default/files/upload_by_users/The-Datacube-Manifesto.pdf) [2] MEA as a Service (http://eodatacube.eu) [3] EarthServer-2 (http://www.earthserver.eu)

Presentation

[Authors] [ Overview programme]
Paper 243 - Session title: Lightning Talks

17:29 Earth Observation Projects for Maximum Education

Fortunato, Ronald (1); Hogan, Patrick (2) 1: Trillium Learning, USA; 2: NASA, United States of America

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The World Bridge program integrates Earth observation technology to advance educational research as applied in the classroom. These projects dynamically design and implement Real-Time, Real-World Project-Based Learning into the local curriculum, and account for the classroom content needed to address academic standards. Three projects will be presented, all involving Earth observing web apps built entirely by students. One project involves the United Nation World Heritage sites that you can instantly zoom to and see in detail from a satellite view of the Earth. Another is a virtual globe web app for managing the water, sewer, power and road system for the city of Kodiak Alaska. Another project is a sophisticated monitoring system for measuring the Earth's magnetic field at 50Hz, at the nano-Gauss sensitivity for the x, y and z axes. The magnetic field has been show to become anomalous in the few days preceding an earthquake, measurable within a few hundred kilometers of the seismic hypo-center. This EO system is student designed, built and installed, and delivering data live via a virtual globe representing the exact location of the data. All of these Earth observing education projects are part of the World Bridge program, and entirely based on principles of open source and open data.

Presentation

[Authors] [ Overview programme]
Paper 249 - Session title: Lightning Talks

17:47 Crowdsourcing EO datasets to improve cloud detection algorithms and land cover change

Aleksandrov, Matej (1); Batič, Matej (1); Milčinski, Grega (1); See, Linda (2); Perger, Christoph (2); Moorthy, Inian (2); Fritz, Steffen (2) 1: Sinergise, Slovenia; 2: International Institute for Applied System Analysis (IIASA)

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Involving citizens in science is gaining considerable traction of late. With positive examples (e.g. Geo-Wiki, FotoQuest Austria), a number of projects are exploring the options to engage the public in contributing to scientific research, often by asking participants to collect some data or validate some results. The International Institute for Applied Systems Analysis (IIASA), with extensive experience in crowdsourcing and gamification, has joined Sinergise, Copernicus Masters 2016 winners, to engage the public in an initiative involving ESA’s Sentinel-2 satellite imagery. Sentinel-2 imagery offers high revisit times and sufficient resolution for land change detection applications. Unfortunately, simple (but fast) algorithms often fail due to many false-positives: changes in clouds are perceived as land changes. The ability to discriminate of cloudy pixels is thus crucial for any automatic or semi-automatic solutions that detect land change. A plethora of algorithms to distinguish clouds in Sentinel-2 data are available. However, there is a need for better data on where and when clouds occur to help improve these algorithms. To overcome this current gap in the data, we are engaging the public in this task. Using a number of tools, developed at IIASA, and Sentinel Hub services, which provide fast access to the entire global archive of Sentinel-2 data, the aim is to obtain a large data resource of curated cloud classifications. The resulting dataset will be published as open data and made available through Geopedia platform. The gamified process will start by asking users if there are clouds on a small image (e.g. 8x8 pixels at the highest Sentinel-2 resolution of 10 m/px), which will provide us with a screening process to pinpoint cloudy areas, employing Picture Pile crowdsourcing game from IIASA. The next step will involve a more detailed workflow, as users will get a slightly larger image (e.g. 64x64 pixels) and will then be asked to delineate different types of clouds: opaque clouds (nothing is seen through the clouds), thick clouds (where the surface is still discernible through the clouds), and thin clouds (where the surface is unequivocally covered by a cloud); the rest of the image will be implicitly cloud-free. The resulting data will be made available through the Geopedia portal, both for exploring and downloading. This paper will demonstrate this process and show some results from a crowdsourcing campaign. The approach will also allow us to collect other datasets in a rapid and efficient manner. For example, using a slightly modified configuration, a similar workflow could be used to obtain a manually curated land cover classification data set, which could be used as training data for machine learning algorithms.

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