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The Moroccan coastline, in particular the Atlantic coast, presents a unique geographical and environmental context that requires special attention. Beaches in this region are subject to natural and anthropogenic forces that influence their dynamic evolution. This study focuses on the in-depth analysis and monitoring of Anza beach in Agadir, Morocco. The aim is to provide an in-depth understanding of the evolution of the Anza coastline. Shoreline analysis quantifies shoreline variations and changes over time using the Digital Shoreline Analysis System tool (DSAS). This analysis provides important information on the erosion and accumulation processes that influence the stability of Anza beach.

Bu çalışmanın amacı; RADAR (Results, Approachs, Deploy, Assess And Refine) uygulaması ile örgütsel bağlılık arasındaki ilişkinin araştırılmasıdır. Araştırmanın ana sorunsalı “RADAR uygulamaları ile çalışan bağlılığı arasında nasıl bir ilişki vardır?” şeklinde belirlenmiştir. Çalışmada, araştırmanın amacına ve kapsamına uygun olarak nitel araştırma yöntemi kullanılmıştır. Araştırmada amaca uygun olarak nitel araştırma desenlerinden durum çalışması deseni ve bütüncül tekli durum deseni tercih edilmiştir. Çalışmada, RADAR uygulamalarının örgütsel bağlıkla olumlu bir ilişkisi olduğu ve gerek yöneticiler gerekse çalışanlar düzeyinde örgütsel bağlılığı arttırdığı bulgulanmıştır.

This article gives some explanations on the technique of interferometry of radar images: how to use it, which products are obtained and what are the constraints to use it. Since its beginnings in the late 1980s, this method, thanks to the multiplication of acquisitions of radar images, the consideration of different types of pixels and the variable image geometries, knows constant progress to make its use more automatic and more efficient. Here we present some of these advances, which allows us to better identify current and future uses. [ABSTRACT FROM AUTHOR]

Due to the weather conditions, airborne and spaceborne radar imagery is an essential source of information for updating the topographic information in the Amazon. This article presents an overview of mapping initiatives in the Amazon using radar techniques in planimetry as well as in altimetry. Instrumental and algorithmic tendencies are described. The challenges of research on radar mapping methods and their applications are discussed. [ABSTRACT FROM AUTHOR]

This article presents some illustrations of (fully or partial) polarimetric radar data applications for the monitoring of terrestrial surfaces. The first part is dedicated to fully polarimetric radar data. Firstly, a theoretical reminder presents the specificity of fully polarimetric data. Then illustrations are given for vegetation types cartography as well as spatio-temporal processes of sedimentation in a semi-arid area in Tunisia. The second part focuses on partially polarimetric data, of the type acquired by the Sentinel-1A/1B satellite SAR sensors, which will be widely used in future years due to their significant contribution to land surface observations studies for environmental sciences. [ABSTRACT FROM AUTHOR]

Last two decades have proven that remote sensing represents a key tool to improve our knowledge of volcanic systems but also to monitor active volcanoes. Based on the specific case of Piton de la Fournaise, Reunion Island, the most active French volcanoes, we here illustrate how Synthetic Aperture Radar (SAR) data, providing information even in cloudy conditions, make it possible to map eruptive deposits, to quantify their volumes but also to estimate the volcanoes topography (with metric precision) as well as surface deformation fields (with a precision reaching a few millimeters). [ABSTRACT FROM AUTHOR]

Remote sensing is a particularly suitable tool for monitoring land use but also particularly suited for déforestation monito-ring. By launching the Setinel-1 and Sentinel-2 satellites in the Copernicus program, the community now has free data with important time-revisits allowing the greatest number of people to effectively monitor land cover of a study area. This paper présents a land use monitoring method based on the combination of two approaches computed using Open Source tools (QGIS, Orfeo ToolBox, python). First, we focus on land use monitoring at an annual time scale using Sentinel-1 and Sentinel-2 data, and then, by the use f entienl-1 data, we detect changes in the forest cover due to déforestation at bi-monthly time scale. The results obtained show a very good synergy of thèse approaches allowing the complementary of optical and radar data. In order to make accessible the proposed method, ail the used open source tools are available on this link http ://remotesensing4all.net/index.php/2018/09/11/kit-use-des-donnees-radar-sentinel-1-in-de-latelier-radar-du-FOSS4G-en-2018-2/. [ABSTRACT FROM AUTHOR]

Les surfaces en herbe jouent un rôle important tant en terme économique qu'environnemental. Elles regroupent une grande diversité de végétation herbacée (pérenne ou éphémère) et occupent une partie importante de l'espace agricole français (zones de pâtures, prairies, milieux agro-naturels présents entre deux cultures principales). Dans ce contexte, cette étude vise à quantifier l'apport de l'imagerie satellitaire multi-spectrale (optique et radar) pour la mise en évidence des surfaces en herbe. Pour ce faire, des classifications supervisées orientées objet, basées sur un algorithme Random Forest et un zonage majoritaire en post-traitement sont utilisées. Cette étude émane de l'expérience de surveillance des cultures multi-capteurs (MCM'10) menée en 2010 sur une zone de polyculture située dans le sud-ouest de la France, à proximité de Toulouse. L'étude s'appuie sur des images satellites acquises entre le 14 et le 18 avril 2010, avec, en radar, des images en bandes X, C et L (de polarisation HH), en optique, une image Formosat-2, et des données terrain concomitantes acquises le 14 avril 2010. Les résultats montrent que la combinaison des images acquises en bande L (Alos) et en optique (Formosat-2) améliore les performances de la classification (précision globale = 0,85 ; Kappa = 0,81) par rapport à l'utilisation des seuls capteurs radar ou optique. Par ailleurs, la performance F-score obtenue pour les surfaces en herbe varie entre 0,1 pour Formosat-2 ; 0,34 pour la combinaison Formosat-2/ Alos et 0,52 pour Alos. Ainsi, les résultats montrent que la qualité de la classification des surfaces en herbe augmente avec l'augmentation de la longueur d'onde des images utilisées.

This paper presents a new concept of aircraft tracking based on a LEO constellation of small satellites, each of them carrying receiving and transmitting devices in order to check the integrity of the ADS-B (Automatic Dependent Surveillance - Broadcast) positioning information and proceed with a non-cooperative independent localization of the aircraft, if a flight anomaly comes out. To do so, on side of the conventional ADS-B processing, authors propose to add a multilateration process and two active radar modes, able to perform a finer and reliable localization of the aircraft, as well as a first information on the nature of the flight anomaly. The paper deals with a preliminary system analysis, although underpinned by some illustrations of existing sensor technologies, already or nearly operational in space. The concept has been patented [1].

Les surfaces en herbe jouent un rôle important tant en terme économique qu'environnemental. Elles regroupent une grande diversité de végétation herbacée (pérenne ou éphémère) et occupent une partie importante de l'espace agricole français (zones de pâtures, prairies, milieux agro-naturels présents entre deux cultures principales). Dans ce contexte, cette étude vise à quantifier l'apport de l'imagerie satellitaire multi-spectrale (optique et radar) pour la mise en évidence des surfaces en herbe.Pour ce faire, des classifications supervisées orientées objet, basées sur un algorithme Random Forest et un zonage majoritaire en post-traitement sont utilisées. Cette étude émane de l'expérience de surveillance des cultures multi-capteurs (MCM'10) menée en 2010 sur une zone de polyculture située dans le sud-ouest de la France, à proximité de Toulouse. L'étude s'appuie sur des images satellites acquises entre le 14 et le 18 avril 2010, avec, en radar, des images en bandes X, C et L (de polarisation HH), en optique, une image Formosat-2, et des données terrain concomitantes acquises le 14 avril 2010. Les résultats montrent que la combinaison des images acquises en bande L (Alos) et en optique (Formosat-2) améliore les performances de la classification (précision globale = 0,85 ; Kappa = 0,81) par rapport à l'utilisation des seuls capteurs radar ou optique. Par ailleurs, la performance F-score obtenue pour les surfaces en herbe varie entre 0,1 pour Formosat-2 ; 0,34 pour la combinaison Formosat-2/ Alos et 0,52 pour Alos. Ainsi, les résultats montrent que la qualité de la classification des surfaces en herbe augmente avec l'augmentation de la longueur d'onde des images utilisées. [ABSTRACT FROM AUTHOR]

Este artículo habla de la experiencia de Thomas Kuhn como físico: su educación en la disciplina, su servicio como experto durante la Segunda Guerra Mundial, y su investigación doctoral. Estudiamos un lapso de tiempo que va de 1940 a 1951. El objetivo en última instancia es ofrecer base empírica para valorar una afirmación como la de Mara Beller (1999), que dice que la descripción kuhniana de la ciencia normal está parcialmente basada en circunstancias y experiencias personales, no sólo en los datos históricos o en la evidencia disponible de la sociología de la ciencia. En este artículo se establece que dicha tesis es plausible.

ABSTRACT: Carajás Mineral Province, Amazon region, is the most important one in Brazil. Vale S.A. Company has the right to operate in the area of the N5E mine. The work is conducted on rock alteration products of low geomechanical quality related to sandstones, siltstones, and a lateritic cover. In order to monitor ground deformation, 33 TerraSAR-X images covering the period of March 2012-April 2013 were used in the investigation. An interferometric synthetic aperture radar (InSAR) approach based on permanent scatterer interferometry (PSI) using an interferometric point target analysis algorithm was applied. Results demonstrated that most of the area was considered stable during the time span of the image acquisition. However, persistent scatterers (PSs) with high deformation rates were mapped over a landfill probably related to settlements. To validate the PSI data, graphs were generated with the displaced information based on topographic measurements in the field. The graphs showed that the surface deformations during TSX-1 runway coverage are within the miner’s safety threshold and do not present a risk of major problems. The PSI data provided a synoptic and detailed view of the deformation process that affects the mining complex without the need of field campaign or instrumentation.

The land-use and land-cover map is fundamental for environmental planning, management, and conservation. Remote sensing data is the information basis for the development of such maps, providing speed and cost-effectiveness. In the Amazon region, the constant presence of cloud cover and smoke makes the use of radar images more adequate for operating independently of these barriers. The present research aims to propose a methodology to classify land use and coverage from PALSAR-2/ALOS-2 multitemporal images in the region of Bananal island. The Bananal island is the second largest fluvial island in the world with approximately 750 km long and 100 km wide. The study area is in the confluence between the Javaés and Araguaia rivers, located in the middle Araguaia river basin. The methodology adopted considers the following steps: acquisition of four multitemporal images Palsar 2/ALOS 2 at processing level 1.5 (L band with resolution of 6.25 meters); (b) Probability Density Component Analysis (PDCA); (c) noise reduction using the Minimum Noise Fraction (MNF) transformation; and (d) classification by the Support Vector Machine method considering the temporal signatures. The ACDP and MNF combination allowed the formulation of different features that describe the different classes present in the image. Comparatively, the images were processed using the Gamma adaptive filter and the SVM classifier. The Kappa coefficient results were 0.62 on the SVM/CDP-MNF images and 0.57 on the SVM / Gamma images. The main factor for the decrease of the Kappa coefficient was the confusion between the areas of Savana Rupestre and anthropic use (pasture) in the areas adjacent to the Bananal island