Study of the speckle noise effects over the eigen decomposition of polarimetric SAR data: a review

This paper is focused on considering the effects of speckle noise on the eigen decomposition of the co- herency matrix. Based on a perturbation analysis of the matrix, it is possible to obtain an analytical expression for the mean value of the eigenvalues and the eigenvectors, as well as for the Entropy, the Anisotroopy and the dif- ferent a angles. The analytical expressions are compared against simulated polarimetric SAR data, demonstrating the correctness of the different expressions.Peer ReviewedPostprint (published version

Assessment of high resolution SAR imagery for mapping floodplain water bodies: a comparison between Radarsat-2 and TerraSAR-X

Flooding is a world-wide problem that is considered as one of the most devastating natural hazards. New commercially available high spatial resolution Synthetic Aperture RADAR satellite imagery provides new potential for flood mapping. This research provides a quantitative assessment of high spatial resolution RADASAT-2 and TerraSAR-X products for mapping water bodies in order to help validate products that can be used to assist flood disaster management. An area near Dhaka in Bangladesh is used as a test site because of the large number of water bodies of different sizes and its history of frequent flooding associated with annual monsoon rainfall. Sample water bodies were delineated in the field using kinematic differential GPS to train and test automatic methods for water body mapping. SAR sensors products were acquired concurrently with the field visits; imagery were acquired with similar polarization, look direction and incidence angle in an experimental design to evaluate which has best accuracy for mapping flood water extent. A methodology for mapping water areas from non-water areas was developed based on radar backscatter texture analysis. Texture filters, based on Haralick occurrence and co-occurrence measures, were compared and images classified using supervised, unsupervised and contextual classifiers. The evaluation of image products is based on an accuracy assessment of error matrix method using randomly selected ground truth data. An accuracy comparison was performed between classified images of both TerraSAR-X and Radarsat-2 sensors in order to identify any differences in mapping floods. Results were validated using information from field inspections conducted in good conditions in February 2009, and applying a model-assisted difference estimator for estimating flood area to derive Confidence Interval (CI) statistics at the 95% Confidence Level (CL) for the area mapped as water. For Radarsat-2 Ultrafine, TerraSAR-X Stripmap and Spotlight imagery, overall classification accuracy was greater than 93%. Results demonstrate that small water bodies down to areas as small as 150m² can be identified routinely from 3 metre resolution SAR imagery. The results further showed that TerraSAR-X stripmap and spotlight images have better overall accuracy than RADARSAT-2 ultrafine beam modes images. The expected benefits of the research will be to improve the provision of data to assess flood risk and vulnerability, thus assisting in disaster management and post-flood recovery

Design Options For Low Cost, Low Power Microsatellite Based SAR.

This research aims at providing a system design that reduces the mass and cost of spaceborne Synthetic Aperture Radar (SAR) missions by a factor of two compared to current (TecSAR - 300 kg, ~ £ 127 M) or planned (NovaSAR-S — 400 kg, ~ £ 50 M) mission. This would enable the cost of a SAR constellation to approach that of the current optical constellation such as Disaster Monitoring Constellation (DMC). This research has identified that the mission cost can be reduced significantly by: focusing on a narrow range of applications (forestry and disasters monitoring); ensuring the final design has a compact stowage volume, which facilitates a shared launch; and building the payload around available platforms, rather than the platform around the payload. The central idea of the research has been to operate the SAR at a low instantaneous power level—a practical proposition for a micro-satellite based SAR. The use of a simple parabolic reflector with a single horn at L-band means that a single, reliable and efficient Solid State Power Amplifier (SSPA) can be used to lower the overall system cost, and to minimise the impact on the spacecraft power system. A detailed analysis of basic pulsed (~ 5 - 10 % duty cycle) and Continuous Wave (CW) SAR (100 % duty cycle) payloads has shown their inability to fit directly into existing microsatellite buses without involving major changes, or employing more than one platform. To circumvent the problems of pulsed and CW techniques, two approaches have been formulated. The first shows that a CW SAR can be implemented in a mono-static way with a single antenna on a single platform. In this technique, the SAR works in an Interrupted CW (ICW) mode, but these interruptions introduce periodic gaps in the raw data. On processing, these gapped data result in artefacts in the reconstructed images. By applying data based statistical estimation techniques to “fill in the gaps” in the simulated raw SAR data, this research has shown the possibility of minimising the effects of these artefacts. However, once the same techniques are applied to the real SAR data (in this case derived from RADARSAT-1), the artefacts are shown to be problematic. Because of this the ICW SAR design technique it is—set aside. The second shows that an extended chirp mode pulsed (ECMP) SAR (~ 20 - 54 % duty cycle) can be designed with a lowered peak power level which enables a single SSPA to feed a parabolic Cassegrain antenna. The detailed analysis shows the feasibility of developing a microsatellite based SAR design at a comparable price to those of optical missions

Application of open-access and 3rd party geospatial technology for integrated flood risk management in data sparse regions of developing countries

Floods are one of the most devastating disasters known to man, caused by both natural and anthropogenic factors. The trend of flood events is continuously rising, increasing the exposure of the vulnerable populace in both developed and especially developing regions. Floods occur unexpectedly in some circumstances with little or no warning, and in other cases, aggravate rapidly, thereby leaving little time to plan, respond and recover. As such, hydrological data is needed before, during and after the flooding to ensure effective and integrated flood management. Though hydrological data collection in developed countries has been somewhat well established over long periods, the situation is different in the developing world. Developing regions are plagued with challenges that include inadequate ground monitoring networks attributed to deteriorating infrastructure, organizational deficiencies, lack of technical capacity, location inaccessibility and the huge financial implication of data collection at local and transboundary scales. These limitations, therefore, result in flawed flood management decisions and aggravate exposure of the most vulnerable people. Nigeria, the case study for this thesis, experienced unprecedented flooding in 2012 that led to the displacement of 3,871,53 persons, destruction of infrastructure, disruption of socio-economic activities valued at 16.9 billion US Dollars (1.4% GDP) and sadly the loss of 363 lives. This flood event revealed the weakness in the nation’s flood management system, which has been linked to poor data availability. This flood event motivated this study, which aims to assess these data gaps and explore alternative data sources and approaches, with the hope of improving flood management and decision making upon recurrence. This study adopts an integrated approach that applies open-access geospatial technology to curb data and financial limitations that hinder effective flood management in developing regions, to enhance disaster preparedness, response and recovery where resources are limited. To estimate flood magnitudes and return periods needed for planning purposes, the gaps in hydrological data that contribute to poor estimates and consequently ineffective flood management decisions for the Niger-South River Basin of Nigeria were filled using Radar Altimetry (RA) and Multiple Imputation (MI) approaches. This reduced uncertainty associated with missing data, especially at locations where virtual altimetry stations exist. This study revealed that the size and consistency of the gap within hydrological time series significantly influences the imputation approach to be adopted. Flood estimates derived from data filled using both RA and MI approaches were similar for consecutive gaps (1-3 years) in the time series, while wide (inconsecutive) gaps (> 3 years) caused by gauging station discontinuity and damage benefited the most from the RA infilling approach. The 2012 flood event was also quantified as a 1-in-100year flood, suggesting that if flood management measures had been implemented based on this information, the impact of that event would have been considerably mitigated. Other than gaps within hydrological time series, in other cases hydrological data could be totally unavailable or limited in duration to enable satisfactory estimation of flood magnitudes and return periods, due to finance and logistical limitations in several developing and remote regions. In such cases, Regional Flood Frequency Analysis (RFFA) is recommended, to collate and leverage data from gauging stations in proximity to the area of interest. In this study, RFFA was implemented using the open-access International Centre for Integrated Water Resources Management–Regional Analysis of Frequency Tool (ICI-RAFT), which enables the inclusion of climate variability effect into flood frequency estimation at locations where the assumption of hydrological stationarity is not viable. The Madden-Julian Oscillation was identified as the dominant flood influencing climate mechanism, with its effect increasing with return period. Similar to other studies, climate variability inclusive regional flood estimates were less than those derived from direct techniques at various locations, and higher in others. Also, the maximum historical flood experienced in the region was less than the 1-in-100-year flood event recommended for flood management. The 2012 flood in the Niger-South river basin of Nigeria was recreated in the CAESAR-LISFLOOD hydrodynamic model, combining open-access and third-party Digital Elevation Model (DEM), altimetry, bathymetry, aerial photo and hydrological data. The model was calibrated/validated in three sub-domains against in situ water level, overflight photos, Synthetic Aperture Radar (SAR) (TerraSAR-X, Radarsat2, CosmoSkyMed) and optical (MODIS) satellite images where available, to access model performance for a range of geomorphological and data variability. Improved data availability within constricted river channel areas resulted in better inundation extent and water level reconstruction, with the F-statistic reducing from 0.808 to 0.187 downstream into the vegetation dominating delta where data unavailability is pronounced. Overflight photos helped improve the model to reality capture ratio in the vegetation dominated delta and highlighted the deficiencies in SAR data for delineating flooding in the delta. Furthermore, the 2012 flood was within the confine of a 1-in-100-year flood for the sub-domain with maximum data availability, suggesting that in retrospect the 2012 flood event could have been managed effectively if flood management plans were implemented based on a 1-in-100-year flood. During flooding, fast-paced response is required. However, logistical challenges can hinder access to remote areas to collect the necessary data needed to inform real-time decisions. Thus, this adopts an integrated approach that combines crowd-sourcing and MODIS flood maps for near-real-time monitoring during the peak flood season of 2015. The results highlighted the merits and demerits of both approaches, and demonstrate the need for an integrated approach that leverages the strength of both methods to enhance flood capture at macro and micro scales. Crowd-sourcing also provided an option for demographic and risk perception data collection, which was evaluated against a government risk perception map and revealed the weaknesses in the government flood models caused by sparse/coarse data application and model uncertainty. The C4.5 decision tree algorithm was applied to integrate multiple open-access geospatial data to improve SAR image flood detection efficiency and the outputs were further applied in flood model validation. This approach resulted in F-Statistic improvement from 0.187 to 0.365 and reduced the CAESAR-LISFLOOD model overall bias from 3.432 to 0.699. Coarse data resolution, vegetation density, obsolete/non-existent river bathymetry, wetlands, ponds, uncontrolled dredging and illegal sand mining, were identified as the factors that contribute to flood model and map uncertainties in the delta region, hence the low accuracy depicted, despite the improvements that were achieved. Managing floods requires the coordination of efforts before, during and after flooding to ensure optimal mitigation in the event of an occurrence. In this study, and integrated flood modelling and mapping approach is undertaken, combining multiple open-access data using freely available tools to curb the effects of data and resources deficiency on hydrological, hydrodynamic and inundation mapping processes and outcomes in developing countries. This approach if adopted and implemented on a large-scale would improve flood preparedness, response and recovery in data sparse regions and ensure floods are managed sustainably with limited resources

Space Security 2008

Provides data and analysis on space activities in 2007 and their cumulative impact on security issues, including space laws, policies, and doctrines; civil space programs and global utilities; commercial uses; and environmental and military issues

New target detector based on geometrical perturbation filters for polarimetric Synthetic Aperture Radar (POL-SAR)

Synthetic Aperture Radar (SAR) is an active microwave remote sensing system able to acquire high resolution images of the scattering behaviour of an observed scene. The contribution of SAR polarimetry (POLSAR) in detection and classification of objects is described and found to add valuable information compared to previous approaches. In this thesis, a new target detection/classification methodology is developed that makes novel use of the polarimetric information of the backscattered field from a target. The detector is based on a geometrical perturbation filter which correlates the target of interest with its perturbed version. Specifically, the operation is accomplished with a polarimetric coherence representing a weighted and normalised inner product between the target and its perturbed version, where the weights are extracted from the observables. The mathematical formulation is general and can be applied to any deterministic (point) target. However, in this thesis the detection is primarily focused on multiple reflections and oriented dipoles due to their extensive availability in common scenarios. An extensive validation against real data is provided exploiting different datasets. They include one airborne system: E-SAR L-band (DLR, German Aerospace Centre); and three satellite systems: ALOS-PALSAR L-band (JAXA, Japanese Aerospace Exploration Agency), RADARSAT-2 C-band (Canadian Space Agency) and TerraSAR-X X-band (DLR). The attained detection masks reveal significant agreement with the expected results based on the theoretical description. Additionally, a comparison with another widely used detector, the Polarimetric Whitening Filter (PWF) is presented. The methodology proposed in this thesis appears to outperform the PWF in two significant ways: 1) the detector is based on the polarimetric information rather than the amplitude of the return, hence the detection is not restricted to bright targets; 2) the algorithm is able to discriminate among the detected targets (i.e. target recognition)

Potencial das capacidades de observação da terra em África para melhorar a sustentabilidade ambiental da região

Duas décadas antes da publicação do “Relatório Brundtland”, a sustentabilidade ambiental já recorria a imagens de Observação da Terra (OT), recolhidas por satélites artificiais, úteis para meteorologia, monitorizar a poluição, desertificação, e alterações climáticas. África deu os primeiros passos no Espaço nos anos 70. Os países africanos investiram já mais de 300M de dólares em satélites de OT, e alguns constroem os seus próprios CubeSat. Ao contrário da Europa, nunca se materializou uma Agência Espacial que unisse esforços dos países africanos. Muitos stakeholders de ambiente africanos usam dados espaciais, e era importante perceber porque não fruiu ainda uma iniciativa espacial multinacional, e como poderia semelhante cooperação servir a sustentabilidade ambiental naquela região. A metodologia seguida aliou a pesquisa bibliográfica a um inquérito feito a entidades africanas dos setores de Espaço e de ambiente. Na primeira fase analisaram-se as 24 iniciativas espaciais africanas. Foram classificadas segundo uma escala proposta pelo autor, que dá primazia ao conhecimento, sobre a industrialização e orçamento. Concluiu-se que a África do Sul, a Argélia, a Nigéria, e Egito são os maiores casos de sucesso. Sendo evidente que as aplicações de OT têm impacto positivo na sustentabilidade ambiental, em África e noutras regiões do globo, foi realizado um inquérito (segunda fase) que obteve 95 respostas. Os inquiridos conhecem iniciativas espaciais, sobretudo não africanas, valorizam o Espaço como resposta aos desafios da sustentabilidade ambiental, e creem ser prioritário o conhecimento versus tecnologia. A casuística dos insucessos de iniciativas multinacionais africanas, torna irrealista esse tipo cooperação em Espaço, e impossível de emular o modelo da Agência Espacial Europeia. Propõe-se então, o roadmap para ajudar atores africanos a melhor guiar os seus esforços espaciais para sustentabilidade ambiental. O roadmap abrange boas práticas para iniciativas espaciais nacionais e multinacionais africanas, e o desenvolvimento local de aplicações de OT. São enfatizadas as potencialidades dos drones e das tendências “New Space”. Considera-se que os atores de Espaço africanos poderão alcançar mais sucesso investindo na educação e em políticas de dados abertas para a produção de informação pertinente aos stakeholders do ambiente.Already two decades before the “Brundtland” Report” was published, environmental sustainability was being served by Earth Observation (EO) images, collected by man-made satellites, and useful for meteorology, monitoring pollution, desertification and climate change. Africa took its first step into space in the 1970s. Over 700M USD have been since invested in EO satellites by African Nations, some building CubeSats on their own. Unlike in Europe, a Space Agency that would have joined African Nations’ forces never materialized. However, many environmental stakeholders in Africa use space data, and it is important to grasp why a multinational space initiative has not come into fruition, and how such cooperation could serve environmental sustainability in the region. The methodology followed combined bibliographic research and a survey made with African entities from the space and environment sectors. In the first phase, the 24 African space initiatives were analysed. This classification was made with a scale proposed by the author, which over emphasizes know-how over industrialisation and budget. Algeria, Nigeria, Egypt and South Africa were graded as the most successful. Evidence showing that EO applications can leave a positive impact on environmental sustainability in Africa and other regions in the world, a survey (undertaken in the second phase) gathered 95 responses, covering 34 of the 54 African nations. The responders were found to be knowledgeable about space initiatives, especially non-African, value space as a response to environmental sustainability challenges, and believe know-how should be a priority over technology. The underlying reasons why multinational initiatives have not succeeded in Africa, makes such type of cooperation unrealistic in space, and impossible to emulate the European Space Agency model. A roadmap is then devised to help African actors guide their space efforts towards environmental sustainability. This roadmap covers best practices for national and multinational African space initiatives, and the development of OT applications. The potential offered by drones and New Space trends are emphasized. It is considered that African space actors can achieve more success by investing in education and open data policies in order to produce information pertinent to environment stakeholders

Estimación de biomasa forestal mediante el uso de imágenes radar.

La importancia de la Biomasa a nivel mundial, ha llevado a que más de 130 países celebren el protocolo de Kioto sobre el cambio climático dictaminando como objetivo la reducción de las emisiones de seis gases de efecto invernadero y tres gases industriales fluorados, así como la incorporación de la fijación del CO2 como un objetivo dentro de los criterios de gestión de bosques. Entre las metodologías no destructivas para estimación de biomasa, aquí desarrolladas se describen tres técnicas que varios autores han propuesto para calcular los valores de biomasa y carbono, tal como el uso de ecuaciones alométricas por medio de la medición de variables dasométricas como el DAP, la aplicación de la teoría de huecos (v.g. DHP, TRAC), y la obtención de biomasa mediante información radar. Las imágenes radar proporcionan una clara ventaja al poder ser adquiridas en cualquier momento del día e independientemente de las condiciones climatológicas. Se han adquirido dos imágenes de sensores diferentes, tal como ALOSPALSAR que trabaja en la banda L y RADARSAT-2 que trabaja en la banda C, se aplica la metodología descrita por Saatchi et al. (2007), desarrollando los algoritmos semiempíricos propuestos para la estimación de biomasa del fuste (Ws) y biomasa de la copa (Wc), obteniendo los coeficientes a partir de información adquirida en campo. ABSTRACT The importance of biomass worldwide has led to more than 130 countries to celebrate the Kyoto Protocol, aimed at reducing emissions of six greenhouse gases and three fluorinated industrial gases, and the incorporation of the fixation of CO2 as an objective within forest management criteria. Among the non-destructive methods for estimating biomass, three techniques were developed. These have been described by some authors, as the use of allometric equations by measuring forest variables such as the DAP, the application of the Gap Theory (e.g. DHP, TRAC), as well as deriving biomass by radar information. The radar images provide a clear advantage since they can be gathered at any time of the day regardless of the weather conditions. For this purpose, two radar products have acquired from different sensors, such as ALOSPALSAR operating on L frequency band and RADARSAT-2 operating on C frequency band. The methodology applied in this work is described in Saatchi et al. (2007), that develop semiempirical algorithms for estimating stem biomass (Ws) and crown biomass (Wc). The corresponding coefficients are determined by means of regression procedures using field information derived from allometric and radiation measurements