Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review

The purpose of this paper is to survey and assess the state-of-the-art in automatic target recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an exhaustive survey of the voluminous literature, but rather to capture in one place the various approaches for implementing the SAR-ATR system. This paper is meant to be as self-contained as possible, and it approaches the SAR-ATR problem from a holistic end-to-end perspective. A brief overview for the breadth of the SAR-ATR challenges is conducted. This is couched in terms of a single-channel SAR, and it is extendable to multi-channel SAR systems. Stages pertinent to the basic SAR-ATR system structure are defined, and the motivations of the requirements and constraints on the system constituents are addressed. For each stage in the SAR-ATR processing chain, a taxonomization methodology for surveying the numerous methods published in the open literature is proposed. Carefully selected works from the literature are presented under the taxa proposed. Novel comparisons, discussions, and comments are pinpointed throughout this paper. A two-fold benchmarking scheme for evaluating existing SAR-ATR systems and motivating new system designs is proposed. The scheme is applied to the works surveyed in this paper. Finally, a discussion is presented in which various interrelated issues, such as standard operating conditions, extended operating conditions, and target-model design, are addressed. This paper is a contribution toward fulfilling an objective of end-to-end SAR-ATR system design.

Caractérisation des occupations du sol en milieu urbain par imagerie radar

Cette étude vise à tester la pertinence des images RSO - de moyenne et de haute résolution - à la caractérisation des types d’occupation du sol en milieu urbain. Elle s’est basée sur des approches texturales à partir des statistiques de deuxième ordre. Plus spécifiquement, on recherche les paramètres de texture les plus pertinents pour discriminer les objets urbains. Il a été utilisé à cet égard des images Radarsat-1 en mode fin en polarisation HH et Radarsat-2 en mode fin en double et quadruple polarisation et en mode ultrafin en polarisation HH. Les occupations du sol recherchées étaient le bâti dense, le bâti de densité moyenne, le bâti de densité faible, le bâti industriel et institutionnel, la végétation de faible densité, la végétation dense et l’eau. Les neuf paramètres de textures analysés ont été regroupés, en familles selon leur définition mathématique. Les paramètres de ressemblance/dissemblance regroupent l’Homogénéité, le Contraste, la Similarité et la Dissimilarité. Les paramètres de désordre sont l’Entropie et le Deuxième Moment Angulaire. L’Écart-Type et la Corrélation sont des paramètres de dispersion et la Moyenne est une famille à part. Il ressort des expériences que certaines combinaisons de paramètres de texture provenant de familles différentes utilisés dans les classifications donnent de très bons résultants alors que d’autres associations de paramètres de texture de définition mathématiques proches génèrent de moins bons résultats. Par ailleurs on constate que si l’utilisation de plusieurs paramètres de texture améliore les classifications, la performance de celle-ci plafonne à partir de trois paramètres. Malgré la bonne performance de cette approche basée sur la complémentarité des paramètres de texture, des erreurs systématiques dues aux effets cardinaux subsistent sur les classifications. Pour pallier à ce problème, il a été développé un modèle de compensation radiométrique basé sur la section efficace radar (SER). Une simulation radar à partir du modèle numérique de surface du milieu a permis d'extraire les zones de rétrodiffusion des bâtis et d'analyser les rétrodiffusions correspondantes. Une règle de compensation des effets cardinaux fondée uniquement sur les réponses des objets en fonction de leur orientation par rapport au plan d'illumination par le faisceau du radar a été mise au point. Des applications de cet algorithme sur des images RADARSAT-1 et RADARSAT-2 en polarisations HH, HV, VH, et VV ont permis de réaliser de considérables gains et d’éliminer l’essentiel des erreurs de classification dues aux effets cardinaux.

Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

Kernel-based mapping of orographic rainfall enhancement in the Swiss Alps as detected by weatherradar

In this paper, we develop a data-driven methodology to characterize the likelihood of orographic precipitation enhancement using sequences of weather radar images and a digital elevation model (DEM). Geographical locations with topographic characteristics favorable to enforce repeatable and persistent orographic precipitation such as stationary cells, upslope rainfall enhancement, and repeated convective initiation are detected by analyzing the spatial distribution of a set of precipitation cells extracted from radar imagery. Topographic features such as terrain convexity and gradients computed from the DEM at multiple spatial scales as well as velocity fields estimated from sequences of weather radar images are used as explanatory factors to describe the occurrence of localized precipitation enhancement. The latter is represented as a binary process by defining a threshold on the number of cell occurrences at particular locations. Both two-class and one-class support vector machine classifiers are tested to separate the presumed orographic cells from the nonorographic ones in the space of contributing topographic and flow features. Site-based validation is carried out to estimate realistic generalization skills of the obtained spatial prediction models. Due to the high class separability, the decision function of the classifiers can be interpreted as a likelihood or susceptibility of orographic precipitation enhancement. The developed approach can serve as a basis for refining radar-based quantitative precipitation estimates and short-term forecasts or for generating stochastic precipitation ensembles conditioned on the local topography.

Mise à jour de la Base de Données Topographiques du Québec à l'aide d'images à très haute résolution spatiale et du progiciel Sigma0 : le cas des voies de communication

Le Ministère des Ressources Naturelles et de la Faune (MRNF) a mandaté la compagnie de géomatique SYNETIX inc. de Montréal et le laboratoire de télédétection de l’Université de Montréal dans le but de développer une application dédiée à la détection automatique et la mise à jour du réseau routier des cartes topographiques à l’échelle 1 : 20 000 à partir de l’imagerie optique à haute résolution spatiale. À cette fin, les mandataires ont entrepris l’adaptation du progiciel SIGMA0 qu’ils avaient conjointement développé pour la mise à jour cartographique à partir d’images satellitales de résolution d’environ 5 mètres. Le produit dérivé de SIGMA0 fut un module nommé SIGMA-ROUTES dont le principe de détection des routes repose sur le balayage d’un filtre le long des vecteurs routiers de la cartographie existante. Les réponses du filtre sur des images couleurs à très haute résolution d’une grande complexité radiométrique (photographies aériennes) conduisent à l’assignation d’étiquettes selon l’état intact, suspect, disparu ou nouveau aux segments routiers repérés. L’objectif général de ce projet est d’évaluer la justesse de l’assignation des statuts ou états en quantifiant le rendement sur la base des distances totales détectées en conformité avec la référence ainsi qu’en procédant à une analyse spatiale des incohérences. La séquence des essais cible d’abord l’effet de la résolution sur le taux de conformité et dans un second temps, les gains escomptés par une succession de traitements de rehaussement destinée à rendre ces images plus propices à l’extraction du réseau routier. La démarche globale implique d’abord la caractérisation d’un site d’essai dans la région de Sherbrooke comportant 40 km de routes de diverses catégories allant du sentier boisé au large collecteur sur une superficie de 2,8 km2. Une carte de vérité terrain des voies de communication nous a permis d’établir des données de référence issues d’une détection visuelle à laquelle sont confrontés les résultats de détection de SIGMA-ROUTES. Nos résultats confirment que la complexité radiométrique des images à haute résolution en milieu urbain bénéficie des prétraitements telles que la segmentation et la compensation d’histogramme uniformisant les surfaces routières. On constate aussi que les performances présentent une hypersensibilité aux variations de résolution alors que le passage entre nos trois résolutions (84, 168 et 210 cm) altère le taux de détection de pratiquement 15% sur les distances totales en concordance avec la référence et segmente spatialement de longs vecteurs intacts en plusieurs portions alternant entre les statuts intact, suspect et disparu. La détection des routes existantes en conformité avec la référence a atteint 78% avec notre plus efficace combinaison de résolution et de prétraitements d’images. Des problèmes chroniques de détection ont été repérés dont la présence de plusieurs segments sans assignation et ignorés du processus. Il y a aussi une surestimation de fausses détections assignées suspectes alors qu’elles devraient être identifiées intactes. Nous estimons, sur la base des mesures linéaires et des analyses spatiales des détections que l’assignation du statut intact devrait atteindre 90% de conformité avec la référence après divers ajustements à l’algorithme. La détection des nouvelles routes fut un échec sans égard à la résolution ou au rehaussement d’image. La recherche des nouveaux segments qui s’appuie sur le repérage de points potentiels de début de nouvelles routes en connexion avec les routes existantes génère un emballement de fausses détections navigant entre les entités non-routières. En lien avec ces incohérences, nous avons isolé de nombreuses fausses détections de nouvelles routes générées parallèlement aux routes préalablement assignées intactes. Finalement, nous suggérons une procédure mettant à profit certaines images rehaussées tout en intégrant l’intervention humaine à quelques phases charnières du processus.

Fotopedologia, espectroscopia e sistema de informação geográfica na caracterização de solos desenvolvidos do Grupo Barreiras no Amapá

O presente trabalho utilizou ferramentas de sensoriamento remoto e sistema de informação geográfica, aliadas às informações espectrais do solo e quantitativas e qualitativas do relevo, para a caracterização e discriminação das classes de solos desenvolvidos do Grupo Barreiras na região do município de Porto Grande, Amapá. Após o mapeamento semidetalhado de solos, realizou-se a caracterização pontual das amostras dos perfis por meio de espectroscopia de visível e infravermelho (400-2500 nm), e a análise espacial das redes de drenagem e relevo a partir de fotos aéreas e imagens de radar. As informações quantitativas do relevo foram mais eficientes na caracterização e discriminação dos solos estudados do que as qualitativas, enquanto as informações espectrais permitiram caracterizar os solos em nível pontual. Métodos espaciais utilizando redes de drenagem e relevo e métodos espectrais utilizando amostras pontuais complementam-se na caracterização e discriminação de solos na paisagem.

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ice thickness measurements in the Lincoln Sea and adjacent Arctic Ocean

Results of helicopter-borne electromagnetic measurements of total (ice plus snow) sea-ice thickness performed in May 2004 and 2005 in the Lincoln Sea and adjacent Arctic Ocean up to 86° N are presented. Thickness distributions south of 84° N are dominated by multi-year ice with modal thicknesses of 3.9 m in 2004 and 4.2 m in 2005 (mean thicknesses 4.67 and 5.18 m, respectively). Modal and mean snow thickness on multi-year ice amounted to 0.18 and 0.30 m in 2004, and 0.28 and 0.35 m in 2005. There are also considerable amounts of 0.9-2.2 m thick first-year ice (modal thickness), mostly representing ice formed in the recurring, refrozen Lincoln Polynya. Results are in good agreement with ground-based electromagnetic thickness measurements and with ice types demarcated in satellite synthetic aperture radar imagery. Four drifting buoys deployed in 2004 between 86° N and 84.5° N show a similar pattern of a mean southward drift of the ice pack of 83 ± 18 km between May 2004 and April 2005, towards the coast of Ellesmere Island and Nares Strait. The resulting area decrease of 26% between the buoys and the coast is larger than the observed thickness increase south of 84° N. This points to the importance of shear in a narrow band along the coast, and of ice export through Nares Strait in removing ice from the study region.

Permanent open water surfaces in central Siberia from ENVISAT ASAR wide swath data 2003/2004, link to shapefile

Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.

Wetlands in central Siberia from ASAR WS 2003, link to shapefiles

An area in central Siberia (partial coverage of Turukhansky und Yeniseysky districts) was investigated using satellite data. It covers freshwater ecosystems of non-forested peatlands in boreal forests. The satellite data represent the growing seasons of 2003/2004. Microwave data were acquired by the Advanced Synthetic Aperture Radar (ASAR) instrument onboard ENVISAT. The multi-temporal capabilities and resolution (150mx150m in WS mode) of the ASAR wide swath mode enabled the detection of dynamic features >2ha over this vast area. Scatterometer (QuikScat) data could be employed to distinguish hydro-periods. Wetland types have been identified on the basis of seasonal changes in backscatter. Results for peatlands have been compared with Russian forest inventory data which contain information on wetland distribution.

Radar analysis of the life cycle of mesoscale convective systems during the 10 June 2000 event

The 10 June 2000 event was the largest flash flood event that occurred in the Northeast of Spain in the late 20th century, both as regards its meteorological features and its considerable social impact. This paper focuses on analysis of the structures that produced the heavy rainfalls, especially from the point of view of meteorological radar. Due to the fact that this case is a good example of a Mediterranean flash flood event, a final objective of this paper is to undertake a description of the evolution of the rainfall structure that would be sufficiently clear to be understood at an interdisciplinary forum. Then, it could be useful not only to improve conceptual meteorological models, but also for application in downscaling models. The main precipitation structure was a Mesoscale Convective System (MCS) that crossed the region and that developed as a consequence of the merging of two previous squall lines. The paper analyses the main meteorological features that led to the development and triggering of the heavy rainfalls, with special emphasis on the features of this MCS, its life cycle and its dynamic features. To this end, 2-D and 3-D algorithms were applied to the imagery recorded over the complete life cycle of the structures, which lasted approximately 18 h. Mesoscale and synoptic information were also considered. Results show that it was an NS-MCS, quasi-stationary during its stage of maturity as a consequence of the formation of a convective train, the different displacement directions of the 2-D structures and the 3-D structures, including the propagation of new cells, and the slow movement of the convergence line associated with the Mediterranean mesoscale low.

Estimating discharge from inundation imagery

Remote sensing from space-borne platforms is often seen as an appealing method of monitoring components of the hydrological cycle, including river discharge, due to its spatial coverage. However, data from these platforms is often less than ideal because the geophysical properties of interest are rarely measured directly and the measurements that are taken can be subject to significant errors. This study assimilated water levels derived from a TerraSAR-X synthetic aperture radar image and digital aerial photography with simulations from a two dimensional hydraulic model to estimate discharge, inundation extent, depths and velocities at the confluence of the rivers Severn and Avon, UK. An ensemble Kalman filter was used to assimilate spot heights water levels derived by intersecting shorelines from the imagery with a digital elevation model. Discharge was estimated from the ensemble of simulations using state augmentation and then compared with gauge data. Assimilating the real data reduced the error between analyzed mean water levels and levels from three gauging stations to less than 0.3 m, which is less than typically found in post event water marks data from the field at these scales. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows where gauge data are unavailable or of poor quality. Posterior estimates of discharge had standard deviations between 63.3 m3s-1 and 52.7 m3s-1, which were below 15% of the gauged flows along the reach. Therefore, assuming a roughness uncertainty of 0.03-0.05 and no model structural errors discharge could be estimated by the EnKF with accuracy similar to that arguably expected from gauging stations during flood events. Quality control prior to assimilation, where measurements were rejected for being in areas of high topographic slope or close to tall vegetation and trees, was found to be essential. The study demonstrates the potential, but also the significant limitations of currently available imagery to reduce discharge uncertainty in un-gauged or poorly gauged basins when combined with model simulations in a data assimilation framework.