scholarly journals Utilization of BEAM and NEST open source toolboxes in education and research

2010 ◽  
Vol 5 ◽  
pp. 37-48
Author(s):  
Markéta Potůčková ◽  
Eva Štefanová

European Space Agency (ESA) provides several open source toolboxes for visualization, processing and analyzing satellite images acquired both in optical and microwave domains. Basic ERS & Envisat (A)ATSR and MERIS Toolbox (BEAM) was originally developed for easier handling ENVISAT optical data. Today this toolbox supports several raster data formats and datasets collected with other EO instruments such as MODIS, AVHRR, CHRIS/Proba. The NEXT ESA SAR Toolbox (NEST) has been created for processing radar data acquired from different satellites such as ERS 1&2, ENVISAT, RADARSAT or TerraSAR X. Both toolboxes are suitable for the education of the basic principles of data processing (geometric and radiometric corrections, classification, filtering of radar data) but also for research. Possibilities for utilization of these toolboxes in remote sensing courses based on two examples of practical exercises are described. Use of the NEST toolbox is demonstrated on a research project dealing with snow cover detection from SAR imagery.

Author(s):  
V N Kopenkov

At the present time, a lot of problems in a sphere of fundamental sciences as well as technical and applied tasks can be solved only with the use of satellite images, since their usage reduces material, financial and time costs significantly in comparison with traditional methods. One of the modern integrated approach remote sensing processing is to join the measurements obtained from the various sources, such as optical and radar sensors, allowing to achieve a gain in comparison with independent processing due to the extension of the information volume and the opportunities of data acquisition (weather conditions, spectral ranges, etc.). However, methods of digital processing and interpretation of radar data, as well as qualitative and proven methods and algorithms for joint processing of optical and radar satellite images, has not sufficiently been well developed yet. Therefore, the development of new methods and information technology of joint analysis and interpretation of optical and radar data which are a major issue of the current paper, are certainly relevant. The paper presents an information technology for joint processing of optical and radar satellite imagery, based on training the processing procedure based on the reference values of data from sensors of the one type (optical data), followed by applying to both data types: optical and SAR data.


2019 ◽  
Vol 11 (16) ◽  
pp. 4454 ◽  
Author(s):  
Stefano Morelli ◽  
Matteo Del Soldato ◽  
Silvia Bianchini ◽  
Veronica Pazzi ◽  
Ervis Krymbi ◽  
...  

The European Space Agency satellites Sentinel-1 radar and Sentinel-2 optical data are widely used in water surface mapping and management. In this work, we exploit the potentials of both radar and optical images for satellite-based quick detection and extent mapping of inundations/water raising events over Shkodër area, which occurred in the two last years (2017–2018). For instance, in March 2018 the Shkodër district (North Albania) was affected twice by the overflow of the Drin and Buna (Bojana) Rivers and by the Shkodër lake plain inundation. Sentinel-1 radar data allowed a rapid mapping of seasonal fluctuations and provided flood extent maps by discriminating water surfaces (permanent water and flood areas) from land/non-flood areas over all the informal zones of Shkodër city. By means of Sentinel-2 data, two color composites maps were produced and the Normalized Difference Water Index was estimated, in order to further distinguish water/moisturized soil surfaces from built-up and vegetated areas. The obtained remote sensing-based maps were combined and discussed with the urban planning framework in order to support a sustainable urban and environmental management. The provided multi-temporal analysis could be easily exploited by the local authorities for flood prevention and management purposes in the inherited territorial context. The proposed approach outputs were validated by comparing them with official Copernicus EMS (Emergency Management Service) maps available for one of the chosen events. The comparison shows good accordance results. As for a further enhancement in the future perspective, it is worth to highlight that a more accurate result could be obtained by performing a post-processing edit to further refine the flooded areas, such as water mask application and supervised classification to filter out isolated flood elements, to remove possible water-lookalikes and weed out false positives.


2021 ◽  
Vol 13 (2) ◽  
pp. 299
Author(s):  
Andrea Pulella ◽  
Francescopaolo Sica

Situational awareness refers to the process of aggregating spatio-temporal variables and measurements from different sources, aiming to improve the semantic outcome. Remote Sensing satellites for Earth Observation acquire key variables that, when properly aggregated, can provide precious insights about the observed area. This article introduces a novel automatic system to monitor the activity levels and the operability of large infrastructures from satellite data. We integrate multiple data sources acquired by different spaceborne sensors, such as Sentinel-1 Synthetic Aperture Radar (SAR) time series, Sentinel-2 multispectral data, and Pleiades Very-High-Resolution (VHR) optical data. The proposed methodology exploits the synergy between these sensors for extracting, at the same time, quantitative and qualitative results. We focus on generating semantic results, providing situational awareness, and decision-ready insights. We developed this methodology for the COVID-19 Custom Script Contest, a remote hackathon funded by the European Space Agency (ESA) and the European Commission (EC), whose aim was to promote remote sensing techniques to monitor environmental factors consecutive to the spread of the Coronavirus disease. This work focuses on the Rome–Fiumicino International Airport case study, an environment significantly affected by the COVID-19 crisis. The resulting product is a unique description of the airport’s area utilization before and after the air traffic restrictions imposed between March and May 2020, during Italy’s first lockdown. Experimental results confirm that the proposed algorithm provides remarkable insights for supporting an effective decision-making process. We provide results about the airport’s operability by retrieving temporal changes at high spatial and temporal resolutions, together with the airplane count and localization for the same period in 2019 and 2020. On the one hand, we detected an evident change of the activity levels on those airport areas typically designated for passenger transportation, e.g., the one close to the gates. On the other hand, we observed an intensification of the activity levels over areas usually assigned to landside operations, e.g., the one close to the hangar. Analogously, the airplane count and localization have shown a redistribution of the airplanes over the whole airport. New parking slots have been identified as well as the areas that have been dismissed. Eventually, by combining the results from different sensors, we could affirm that different airport surface areas have changed their functionality and give a non-expert interpretation about areas’ usage.


2020 ◽  
Vol 12 (6) ◽  
pp. 961 ◽  
Author(s):  
Marinalva Dias Soares ◽  
Luciano Vieira Dutra ◽  
Gilson Alexandre Ostwald Pedro da Costa ◽  
Raul Queiroz Feitosa ◽  
Rogério Galante Negri ◽  
...  

Per-point classification is a traditional method for remote sensing data classification, and for radar data in particular. Compared with optical data, the discriminative power of radar data is quite limited, for most applications. A way of trying to overcome these difficulties is to use Region-Based Classification (RBC), also referred to as Geographical Object-Based Image Analysis (GEOBIA). RBC methods first aggregate pixels into homogeneous objects, or regions, using a segmentation procedure. Moreover, segmentation is known to be an ill-conditioned problem because it admits multiple solutions, and a small change in the input image, or segmentation parameters, may lead to significant changes in the image partitioning. In this context, this paper proposes and evaluates novel approaches for SAR data classification, which rely on specialized segmentations, and on the combination of partial maps produced by classification ensembles. Such approaches comprise a meta-methodology, in the sense that they are independent from segmentation and classification algorithms, and optimization procedures. Results are shown that improve the classification accuracy from Kappa = 0.4 (baseline method) to a Kappa = 0.77 with the presented method. Another test site presented an improvement from Kappa = 0.36 to a maximum of 0.66 also with radar data.


2021 ◽  
Vol 13 (20) ◽  
pp. 4087
Author(s):  
Maria Teresa Melis ◽  
Luca Pisani ◽  
Jo De Waele

Hundreds of large and deep collapse dolines dot the surface of the Quaternary basaltic plateau of Azrou, in the Middle Atlas of Morocco. In the absence of detailed topographic maps, the morphometric study of such a large number of features requires the use of remote sensing techniques. We present the processing, extraction, and validation of depth measurements of 89 dolines using tri-stereo Pleiades images acquired in 2018–2019 (the European Space Agency (ESA) © CNES 2018, distributed by Airbus DS). Satellite image-derived DEMs were field-verified using traditional mapping techniques, which showed a very good agreement between field and remote sensing measures. The high resolution of these tri-stereo images allowed to automatically generate accurate morphometric datasets not only regarding the planimetric parameters of the dolines (diameters, contours, orientation of long axes), but also for what concerns their depth and altimetric profiles. Our study demonstrates the potential of using these types of images on rugged morphologies and for the measurement of steep depressions, where traditional remote sensing techniques may be hindered by shadow zones and blind portions. Tri-stereo images might also be suitable for the measurement of deep and steep depressions (skylights and collapses) on Martian and Lunar lava flows, suitable targets for future planetary cave exploration.


2019 ◽  
Vol 11 (20) ◽  
pp. 2389 ◽  
Author(s):  
Deodato Tapete ◽  
Francesca Cigna

Illegal excavations in archaeological heritage sites (namely “looting”) are a global phenomenon. Satellite images are nowadays massively used by archaeologists to systematically document sites affected by looting. In parallel, remote sensing scientists are increasingly developing processing methods with a certain degree of automation to quantify looting using satellite imagery. To capture the state-of-the-art of this growing field of remote sensing, in this work 47 peer-reviewed research publications and grey literature are reviewed, accounting for: (i) the type of satellite data used, i.e., optical and synthetic aperture radar (SAR); (ii) properties of looting features utilized as proxies for damage assessment (e.g., shape, morphology, spectral signature); (iii) image processing workflows; and (iv) rationale for validation. Several scholars studied looting even prior to the conflicts recently affecting the Middle East and North Africa (MENA) region. Regardless of the method used for looting feature identification (either visual/manual, or with the aid of image processing), they preferred very high resolution (VHR) optical imagery, mainly black-and-white panchromatic, or pansharpened multispectral, whereas SAR is being used more recently by specialist image analysts only. Yet the full potential of VHR and high resolution (HR) multispectral information in optical imagery is to be exploited, with limited research studies testing spectral indices. To fill this gap, a range of looted sites across the MENA region are presented in this work, i.e., Lisht, Dashur, and Abusir el Malik (Egypt), and Tell Qarqur, Tell Jifar, Sergiopolis, Apamea, Dura Europos, and Tell Hizareen (Syria). The aim is to highlight: (i) the complementarity of HR multispectral data and VHR SAR with VHR optical imagery, (ii) usefulness of spectral profiles in the visible and near-infrared bands, and (iii) applicability of methods for multi-temporal change detection. Satellite data used for the demonstration include: HR multispectral imagery from the Copernicus Sentinel-2 constellation, VHR X-band SAR data from the COSMO-SkyMed mission, VHR panchromatic and multispectral WorldView-2 imagery, and further VHR optical data acquired by GeoEye-1, IKONOS-2, QuickBird-2, and WorldView-3, available through Google Earth. Commonalities between the different image processing methods are examined, alongside a critical discussion about automation in looting assessment, current lack of common practices in image processing, achievements in managing the uncertainty in looting feature interpretation, and current needs for more dissemination and user uptake. Directions toward sharing and harmonization of methodologies are outlined, and some proposals are made with regard to the aspects that the community working with satellite images should consider, in order to define best practices of satellite-based looting assessment.


1994 ◽  
Vol 160 ◽  
pp. 381-394
Author(s):  
Yves Langevin

The European Space Agency (ESA) has selected Rosetta as the next cornerstone mission, to be launched in 2003. The goal is to perfom one or more fly-bys to main belt asteroids, followed by a rendez-vous with an active comet. Advanced in situ analysis, both in the coma and on the surfaces of the nucleus, will be possible, as well as monitoring by remote sensing instruments of the nucleus and of the inner coma for a time span of more than one year, until perihelion. This paper outlines the scientific and technological choices done in the definition of the mission.


2020 ◽  
Author(s):  
Alexander Kokhanovsky ◽  
Jason Box ◽  
Baptiste Vandecrux ◽  
Michael Kern

<p><span>In this work we propose a simple technique to derive snow and atmosphere properties from satellite top-of-atmosphere spectral reflectance observations using asymptotic radiative transfer theory valid for the case of weakly absorbing and optically thick media. The following snow properties are derived and analyzed: ice grain size, snow specific surface area, snow pollution load, snow spectral and broadband albedo. The developed retrieval technique includes both atmospheric correction and cloud screening routines and is based on Ocean and Land Colour Instrument (OLCI) measurements on board Sentinel-3A, B. The spectral aerosol optical thickness, total ozone and water vapour column are derived fitting the measured and simulated OLCI-registered spectral reflectances at 21 OLCI channels.</span></p><p><span>The derived results are validated using ground - based observations. It follows that satellite observations can be used to study time series of spectral and broadband albedo over Greenland. The deviations of satellite and ground observations are due to problems with cloud screening over snow and also due to different spatial scale of satellite and ground observations (Kokhanovsky et al., 2020).</span></p><p>Acknowledgements</p><p>The work has been supported by the European Space Agency in the framework of ESRIN contract No. 4000118926/16/I-NB ‘Scientific Exploitation of Operational Missions (SEOM) Sentinel-3 Snow (Sentinel-3 for Science, Land Study 1: Snow’) and ESRIN contract 4000125043 – ESA/AO/1-9101/17/I-NB EO science for society ‘Pre-operational Sentinel-3 snow and ice products’.</p><p><span>References</span></p><p>Kokhanovsky, A.A., et al. (2020), The determination of snow albedo from satellite observations using fast atmospheric correction technique, Remote Sensing, 12 (2), 234,  https://doi.org/10.3390/rs12020234.</p>


European Remote Sensing Satellite Number 1 (ERS-1) is a truly international project promoted by the European Space Agency (E.S.A.) and involving 10 countries. The decisions about what should be the aims of the satellite have been reached as the result of lengthy discussions between E.S.A. and potential customers, and of course have also had to take into account the budgetary limitations imposed by the participating countries. The major objectives of ERS-1 are set out in the paper together with a very brief outline of the capabilities of the instruments required to meet these objectives. The paper concludes by suggesting areas in which there is a need for technological advance, which combined with concentrated marketing activity will ensure a commercial future for the remote sensing capability that will be demonstrated by ERS-1.


2007 ◽  
Vol 3 (S248) ◽  
pp. 1-7
Author(s):  
C. Turon ◽  
F. Arenou

AbstractThe European Space Agency decision to include the Hipparcos satellite into its Science Programme is placed in the context of the years 1965-1980 and in the historical perspective of the progress of astrometry. The motivation and ideas which lead to the Hipparcos design are reviewed as well as its characteristics and performance. The amount and variety of applications represent an impressive evolution from the original science case and opened the way to much more ambitious further space missions, especially Gaia, based on the same basic principles. A giant step in technology led to a giant step in science. Next steps are presented at this Symposium.


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