Use of High Resolution Satellite Images for the Calibration of Hydro-geological Models in Semi-Arid Regions: A Case Study

In this paper we present the preliminary results of a project devoted to use hydrologic and remote sensing models and data for water resource management in semi-arid regions. The project is developed in the Sahel region of Burkina Faso, where a set of high resolution synthetic aperture radar (SAR) images was acquired. The rationale of the project along with the preliminary results obtained by the processing of high resolution Cosmo- SkyMed data are presented and discussed

Satellite-supported flood forecasting in river networks: a real case study

Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting

A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data

Accurate flood mapping is important for both planning activities during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this paper, a Bayesian network is proposed to integrate remotely sensed data, such as multitemporal SAR intensity images and interferometric-SAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood that occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%

Pixel tracking to estimate riverswater flow elevation using cosmo-skymed synthetic aperture radar data

The lack of availability of historical and reliable river water level information is an issue that can be overcome through the exploitation of modern satellite remote sensing systems. This research has the objective of contributing in solving the information-gap problem of river flow monitoring through a synthetic aperture radar (SAR) signal processing technique that has the capability to perform water flow elevation estimation. This paper proposes the application of a new method for the design of a robust procedure to track over the time double-bounce reflections from bridges crossing rivers to measure the gap space existing between the river surface and bridges. Specifically, the difference in position between the single and double bounce is suitably measured over the time. Simulated and satellite temporal series of SAR data from COSMO-SkyMed data are compared to the ground measurements recorded for three gauges sites over the Po and Tiber Rivers, Italy. The obtained performance indices confirm the effectiveness of the method in the estimation of water level also in narrow or ungauged rivers

Avaliação de dados polarimétricos e de atributos de textura em imagens SAR para discriminar a floresta secundária em uma área de domínio de floresta amazônica

This study aims to evaluate the ability of Sentinel-1 polarimetric and backscatter attributes in relation to COSMO-SkyMed (CSM) texture and backscatter features to discriminate secondary vegetation areas in an Amazon Forest domain area, located in Mato Grosso state. In this study, we used polarizations VV and VH from Sentinel-1 Synthetic Aperture Radar (SAR) image and HH from CSM SAR image, both in Single Look Complex format. In the Sentinel-1 image, a covariance matrix was generated and the H-Alpha target decomposition theorem was applied, allowing to obtain the attributes Entropy and Angle alpha. In the CSM image obtained the Gray-Level Co-Occurrence Matrix (GLCM) texture attributes: dissimilarity, contrast, homogeneity and second moment. The Support Vector Machine (SVM) algorithm was used for the classification. The Sentinel-1 polarimetric attributes result, with a Kappa index of 0.70 and an overall accuracy of 79.58%, performed better than those derived from CSM, with a Kappa index of 0.56 and overall accuracy 63.67%. However, the Sentinel-1 and CSM attributes did not present satisfactory results to discriminate the different stages of secondary forest.O objetivo do presente estudo foi avaliar a capacidade de atributos polarimétricos e de retroespalhamento do Sentinel-1 em relação às feições de textura e de retroespalhamento do COSMO-SkyMed (CSM), em discriminar diferentes estágios de floresta secundária em uma área de domínio de Floresta Amazônica, no estado do Mato Grosso. Neste estudo, utilizou-se uma imagem de Radar de Abertura Sintética (SAR) do Sentinel-1 nas polarizações VV e VH e uma imagem SAR do CSM na polarização HH, ambas no formato Single Look Complex. Na imagem Sentinel-1 foi gerada a matriz de covariância e aplicado o teorema de decomposição de alvos H-Alpha, para obtenção dos atributos Entropia e Ângulo alfa. Na imagem CSM, foram obtidos os atributos de textura a partir da matriz de co-ocorrência de níveis de cinza (GLCM): dissimilaridade, contraste, homogeneidade e segundo momento. Para a classificação, foi utilizado o algoritmo Máquina de Vetores de Suporte (SVM). A classificação derivada dos atributos polarimétricos do Sentinel-1, com índice Kappa de 0,70 e exatidão global de 79,58%, apresentou desempenho superior àquela derivada do CSM, com índice Kappa de 0,56 e exatidão global de 63,67%. Entretanto, tanto os atributos derivados do Sentinel-1 como do CSM não apresentaram resultados satisfatórios para discriminar os diferentes estágios de floresta secundária

3D space intersection features extraction from Synthetic Aperture Radar images

The main purpose of this Thesis is to develop new theoretical models in order to extend the capabilities of SAR images space intersection techniques to generate three dimensional information. Furthermore, the study aims at acquiring new knowledge on SAR image interpretation through the three dimensional comprehension of the scene. The proposed methodologies allow to extend the known radargrammetric applications to vector data generation, exploiting SAR images acquired with every possible geometries. The considered geometries are points, circles, cylinders and lines. The study assesses the estimation accuracy of the features in terms of absolute and relative position and dimensions, analyzing the nowadays operational SAR sensors with a special focus on the national COSMO-SkyMed system. The proposed approach is original as it does not require the direct matching between homologous points of different images, which is a necessary step for the classical radargrammetric techniques; points belonging to the same feature, circular or linear, recognized in different images, are matched through specific models in order to estimate the dimensions and the location of the feature itself. This approach is robust with respect to the variation of the viewing angle of the input images and allows to better exploit archive data, acquired with diverse viewing geometries. The obtained results confirm the validity of the proposed theoretical approach and enable important applicative developments, especially in the Defence domain: (i) introducing original three dimensional measurement tools to support visual image interpretation; (ii) performing an advanced modelling of building counting only on SAR images; (iii) exploiting SAR images as a source for geospatial information and data; (iv) producing geospatial reference information, such as Ground Control Point, without any need for survey on the ground

Simulating SAR geometric distortions and predicting Persistent Scatterer densities for ERS-1/2 and ENVISAT C-band SAR and InSAR applications: nationwide feasibility assessment to monitor the landmass of Great Britain with SAR imagery

We assess the feasibility of monitoring the landmass of Great Britain with satellite Synthetic Aperture Radar (SAR) imagery, by analysing ERS-1/2 SAR and ENVISAT IS2 Advanced SAR (ASAR) archive data availability, geometric distortions and land cover control on the success of (non-)interferometric analyses. Our assessment both addresses the scientific and operational question of whether a nationwide SAR-based monitoring of ground motion would succeed in Great Britain, and helps to understand controlling factors and possible solutions to overcome the limitations of undertaking SAR-based imaging of the landmass. This is the first time such a nationwide assessment is performed in preparation for acquisition and processing of SAR data in the United Kingdom, and any other country in the world. Analysis of the ERS-1/2 and ENVISAT archives reveals potential for multi-interferogram SAR Interferometry (InSAR) for the entirety of Britain using ERS-1/2 in descending mode, with 100% standard image frames showing at least 20 archive scenes available. ERS-1/2 ascending and both ENVISAT modes show potential for non-interferometric and single-pair InSAR for the vast majority of Britain, and multi-interferogram only for 13% to 38% of the available standard frames. Based on NEXTMap® Britain Digital Terrain Model (DTM) we simulate SAR layover, foreshortening and shadow to the ERS-1/2 and ENVISAT Lines-Of-Sight (LOS), and quantify changes of SAR distortions with variations in mode, LOS incidence angles and ground track angles, local terrain orientation, and the effect of scale due to the input DTM resolution. The simulation is extended to the ~ 230,000 km2 landmass, and shows limited control of local topography on the radar terrain visibility. According to the 50 m to 5 m DTM-based simulations, ~ 1.0–1.4% of Great Britain could potentially be affected by shadow and layover in each mode. Only ~ 0.02–0.04% overlapping between ascending and descending mode distortions is found, this indicating the negligible proportion of the landmass that cannot be monitored using either imaging mode. We calibrate the CORINE Land Cover 2006 (CLC2006) using Persistent Scatterer (PS) datasets available for London, Stoke-On-Trent, Newcastle and Bristol, to quantify land cover control on the PS distribution and characterise the CLC2006 classes in terms of the potential PS density they could provide. Despite predominance of rural land cover types, we predict potential for over 12.8 M monitoring targets for each acquisition mode using a set of image frames covering the entire landmass. We validate our assessment by processing with the Interferometric Point Target Analysis (IPTA) 55 ERS-1/2 SAR scenes depicting South Wales between 1992 and 1999. Although absolute differences between predicted and observed target density are revealed, relative densities and rankings among the various CLC2006 classes are found constant across the calibration and validation datasets. Rescaled predictions for Britain show potential for a total of 2.5 M monitoring targets across the landmass. We examine the use of the topographic and land cover feasibility maps for landslide studies in relation to the British Geological Survey's National Landslide Database and DiGMapGB mass movement layer. Building upon recent literature, we finally discuss future perspectives relating to the replication of our feasibility assessment to account for higher resolution SAR imagery, new Earth explorers (e.g., Sentinel-1) and improved processing techniques, showing potential to generate invaluable sources of information on land motions and geohazards in Great Britai

Applications of SAR Interferometry in Earth and Environmental Science Research

This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions