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This paper provides a compact overview of SESAME, a mission concept in which two receive-only small Synthetic Aperture Radar (SAR) satellites flying in close formation would allow single-pass interferometric observations using Sentinel-1 as transmitter.
The concept of a passive receiving small satellite flying in formation with an active satellite for bistatic Synthetic Aperture Radar (SAR) imaging has been the subject of numerous national and international studies. In 2013, ESA received an offer from the National Commission for Space Activities of Argentina (CONAE) to launch a small satellite with the SAOCOM-1b satellite, and to collaborate during...
This work aims at defining applications, products and user requirements, as well as the hardware and ground processing design of a companion satellite mission which shall carry aboard a “passive” radar working in tandem with the Argentinian L-band radar developed by CONAE and denoted as SAOCOM. The primary objective (i.e., science driver) of the SAOCOM companion satellite mission (SAOCOM-CS) is forest...
This contribution is dedicated to present tomographic investigations on 3D vegetation imaging for future spaceborne SAR missions. The main problem to tackle when performing tomography via repeat-pass spaceborne data is that the temporal decorrelation between acquisitions can be very severe making it difficult to achieve reliable results. In this context, if two or more sensors are available to perform...
In this work we discuss the differences between SAR tomographic analyses produced by direct 3D focusing, which we refer to as coherent tomography, and by processing simultaneous interferometric pairs collected in different passes, which we refer to as incoherent tomography. While the application of coherent tomography using space-borne sensors is often hindered by temporal decorrelation, incoherent...
SAOCOM (Satélite Argentino de Observación Con Microondas) is a CONAE L-band SAR mission with a constellation of two LEO spacecrafts in a Sun-synchronous dusk-dawn orbit. SAOCOM-CS is an ESA's receive-only Companion Satellite flying in formation with SAOCOM-1B, which would act as an illuminator. SAOCOM-CS will introduce a new type of SAR missions with simultaneous observations providing polarimetry,...
Companion missions provide a path to add single-pass interferometric capabilities to existing monostatic SAR missions. Large baselines, only achievable through formation flying, are necessary both to achieve the required performance in many interferometric applications and to enable SAR tomography. Some of the main challenges include meeting tight formation flying requirements, often calling for multiple-companion...
The contribution focuses on the technical aspects related to the focusing and interferometric processing of bistatic data acquired by companion satellite (CS) SAR missions. In particular, the processing aspects related to the large along-track baseline configuration will be addressed, for the processing needs to properly consider a potential high squint angle. The technical challenges encompass synchronization,...
This paper introduces the concept of a fractionated MirrorSAR which is based on a set of mutually separated transmitter and receiver satellites. As opposed to previously published bi- and multistatic SAR systems, the receiver satellites are considerably simplified, as their main functionality is reduced to a kind of microwave mirror (or space transponder) which routes the radar echoes towards the...
Companion SAR missions offer a cost-effective solution to enhance the added value of existing SAR satellites. In particular, they offer new possibilities to extend the observation space and provide one or several single-pass interferometric channels for the acquisitions. The paper aims to provide a description of an end-to-end performance simulation for companion SAR missions, including the evaluation...
Change detection in multitemporal hyperspectral images (HSI) can be regarded as a classification task, consisting of two steps: change feature extraction and identification. To extract clean change features from heavily corrupted spectral change vectors (SCV) of multitemporal HSI, this paper proposes a novel spectrally-spatially regularized low-rank and sparse decomposition model (LRSDSS). It exploits...
Multitemporal Hyperspectral (HS) images can be used in Change Detection (CD) to identify and discriminate among different kinds of change due to the fine sampling of the spectrum by HS sensors. In this work we propose a novel method for unsupervised multiple CD in multitemporal HS data based on binary Spectral Change Vectors (SCVs) and an agglomerative hierarchical clustering. First, we perform binary...
This work presents a semi-automated procedure for monitoring deforestation and forest degradation in the Brazilian Amazon using a multi-temporal dataset of satellite imagery. Degradation in forest cover in the Brazilian Amazon region is mainly due to selective logging of intact/un-managed forests and to uncontrolled fires. For this study, part of a Landsat TM scene located in the State of Mato Grosso,...
A novel spectral-spatial joint multiscale approach is developed to address the multi-class change detection problem in bitemporal multispectral remote sensing images. The proposed approach is based on a multiscale morphological compressed change vector analysis (M2C2VA), which extend the state-of-the-art spectrum-based compressed change vector analysis (C2VA) while preserving more geometrical details...
This paper presents a novel semisupervised framework for detecting multi-class changes in bitemporal hyperspectral images. By taking advantages of the state-of-the-art unsupervised change representation technique and the advanced supervised classifiers, the proposed framework allows the generation of pseudo training samples associated with the no-change and each change class that learned from the...
Due to their weather and illumination independence and due to their large area coverage at high spatial resolution, Synthetic Aperture Radar (SAR) images have been recognized as a valuable data source for the mapping and tracking of aufeis flooding events. We modified and utilized the change detection approach of [1], based on wavelet analysis to map aufeis-related flooding on the Sagavanirktok River...
Feature extraction is an important issue for image interpretation, many valuable feature extraction methods have been proposed to address synthetic aperture radar (SAR) image registration. However, the current methods care little about changes over multi-temporal SAR images, which result in unstable output features. The unstable property is a latent factor to affect the accuracy of SAR image registration...
This paper proposed a difference of standard deviation operator to detect temporal changes in multi-temporal Radarsat-1 SAR images which is derived from the classical multiplicative model. When changes are occurred, textures of the terrestrial surface will be modified resulting in the variation of standard deviation of the terrestrial surface. The new Riemannian metric is introduced into the unsupervised...
This study aims to evaluate the potential of coherent change detection using multi-temporal polarimetric interferometric SAR data. One of the limitations in damage area extraction is that the decorrelation caused by the disaster is commonly coupled with the natural changes. Also, the interpretation of the coherence is troublesome and requires the coherence model. The approach used in this study is...
This article presents a methodology to improve the flood classification results of an automatic Sentinel-1 Flood Service (S-1FS) in arid areas, where reliable SAR-based water detection is usually not possible. Statistical information of Sentinel-1 (S-1) backscatter time series data were used to remove water look-alikes related to sand surfaces which generally lead to significant overestimations of...
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