Remote sensing of the Earth with spaceborne imaging radars

Spaceborne imaging sensors in the visible, infrared and passive microwave have been used to observe and study the Earth's surface since the early stages of the space program. More recently, active microwave imaging sensors (radars) have been developed to extend our capability to study the Earth surface processes. Imaging radars, flown on Seasat (1978) and the Shuttle (1981, 1984), acquired synoptic images of a variety of geologic, biologic, and oceanographic features and provided new insight in some of the land and ocean processes. Subsurface synoptic imaging was achieved for the first time in some of the arid regions of the world. Soil moisture distribution after a rainstorm was clearly delineated, opening the possibility of its monitoring on a global basis. Polar ice distribution and dynamics over large areas in the Beaufort Sea were monitored over a three-month period, thus allowing the possibility of operational observation of ice dynamics in support of polar navigation. The successful development and flight of these spaceborne imaging radars was the result of major technological developments in the 1970s. They used some of the largest spaceborne lightweight planar array antennas (2X10 m) with printed radiating elements. The transmitters were fully solid state and generated a 1 kw peak power signal at L-band (1.2 Ghz). The processing of the received data to generate the high-resolution (25 to 40 m) imagery was done using both optical and digital processors. More advanced imaging radar systems are under development. Multispectral, multipolarization imaging radar systems are under development for flight in the late 1980s, thus extending our capability of detailed studies of the Earth surface processes and the nature of its cover. Extremely fast SAR digital processors are under development using the most advanced integrated circuits and allowing real-time processing of the data. This corresponds to a computational capability of 6 X 10^9 operations/s. This chapter consists of a review of the recent scientific and technological developments in the field of Earth observation with spaceborne imaging radars and an overview of planned activities in the 1980s

Contribution to ground-based and UAV SAR systems for Earth observation

Mankind's way of life is the main driver of a planetary-scale change that is marked by the growing of human population's demand of energy, food, goods, services and information. As a result, it have emerged new ecological, economical, social and geopolitical concerns. In this scenario, SAR remote sensing is a potential tool that provides unique information about the Earth's properties and processes that can be used to solve societal challenges of local and global dimension. SARs, which are coherent systems that are able to provide high resolution images with weather independence, represent a suitable alternative for EO with diverse applications. Some examples of SAR application areas are topography (DEM generation with interferometry), agriculture (crop classification or soil moisture), or geology (monitoring surface deformation). In this framework, the encompassing objective of the present doctoral work has been part of the implementation and the subsequent evaluation of capabilities of two X-band SAR sensors. On the one hand, the RISKSAR-X radar designed to be operated at ground to monitor small-scale areas of observation and, on the other, the ARBRES-X sensor designed to be integrated into small UAVs. Despite its inherently dissimilar conception, the concurrence of both sensors has been evidenced along this manuscript. By taking advantage of the similarities between them, it has been possible to analogously assess both sensors to obtain conclusions. In this context, the common link has been the development of the polarimetric OtF operation mode of the RISKSAR-X, allowing this sensor to be operated equivalently to the ARBRES-X. Regarding the RISKSAR-X SAR sensor, several hardware contributions have been developed during part of this Ph.D. with the aim of improving the system performance. By endowing the system with the capability to operate in the fully polarimetric OtF acquisition mode, the relative long scanning time has been reduced. It is of great interest since the measured scatterers that present a short term variable reflectivity during the scanning time, such as moving vegetation, may degrade the extracted parameters from the retrieved data and the SAR image reconstruction. During this doctoral activity, it has been studied the image blurring, the decorrelation and the coherence degradation introduced by this effect. Furthermore, a new term in the differential interferometric coherence that takes into account the image blurring has been introduced. Concerning the ARBRES-X SAR system, one of the main objectives pursued during this Ph.D. has been the integration of the sensor into a small UAV MP overcoming restrictions of weight, size and aerodynamics of the platform. The use of this type of platforms is expected to open up new possibilities in airborne SAR remote sensing, since it offers much more versatility than the commonly used fixed wings UAVs. Different innovative flight strategies with this type of platforms have been assessed and some preliminary results have been obtained with the use of the ARBRES-X SAR system. During the course of the present doctoral work, much effort has been devoted to achieve the first experimental repeat-pass interfereometric results obtained with the UAV MP together with the ARBRES-X. Moreover, the sensor has been endowed with fully polarimetric capabilities by applying the improvements developed to the RISKSAR-X radar, which is another example of the duality between both systems. Finally, a vertical and a semicircular aperture have been successfully performed obtaining SLC images of the scenario, which envisages the capability of the UAV MP to perform tomographic images and complete circular apertures in the future. In conclusion, the UAV MP is a promising platform that opens new potentials for several applications, such as repeat-pass interferometry or differential tomography imaging with the realization of almost arbitrary trajectories.El mode de viure de la humanitat és el principal motor d'un canvi a escala planetària que està marcat per la creixent demanda d'energia, d'aliment, de béns, de serveis i d'informació de les poblacions humanes. Com a resultat, han sorgit noves inquietuds ecològiques, econòmiques, socials i geopolítiques. En aquest escenari, la detecció remota SAR és una eina potencial que proporciona informació única sobre les propietats i processos de la Terra que es pot utilitzar per resoldre reptes socials de dimensió local i global. Els SARs, que són sistemes coherents que poden proporcionar imatges d'alta resolució amb independència del temps, representen una alternativa adequada per a l'observació de la Terra. Alguns exemples d'àrees d'aplicació SAR són la topografia (generació de DEM amb interferometria), l'agricultura (classificació de cultius o humitat del sòl) o la geologia (monitoratge de deformació superficial). En aquest context, l'objectiu general del present doctorat ha estat part de la implementació i posterior avaluació de les capacitats de dos sensors SAR de banda X. D'una banda, el radar RISKSAR-X dissenyat per funcionar a terra i monitoritzar àrees d'observació a petita escala i, d'altra, el sensor ARBRES-X dissenyat per ser integrat en petits UAVs. Malgrat la seva concepció inherentment diferent, la concurrència d'ambdós sensors s'ha evidenciat al llarg d'aquest manuscrit. Aprofitant les similituds entre ells, s'han pogut avaluar de forma anàloga els dos sensors per obtenir conclusions. En aquest sentit, el vincle comú ha estat el desenvolupament del mode de funcionament polimètric OtF del RISKSAR-X, permetent que aquest sensor operi de forma equivalent a l'ARBRES-X. Pel que fa al sensor RISKSAR-X, s'han desenvolupat diverses contribucions hardware durant part d'aquest doctorat amb l'objectiu de millorar el rendiment del sistema. En dotar el sistema de la possibilitat d'operar en el mode d'adquisició totalment polarimètric OtF, s'ha reduït el relatiu llarg temps d'escaneig. Això és de gran interès ja que els blancs mesurats que presenten una reflectivitat variable a curt termini, com ara la vegetació en moviment, poden degradar els paràmetres extrets de les dades recuperades i la reconstrucció d'imatges SAR. Durant aquesta activitat doctoral s'ha estudiat el desenfocat de la imatge, la decorrelació i la degradació de la coherència introduïts per aquest efecte. A més, s'ha introduït un nou terme en la coherència interferomètrica diferencial que té en compte el desenfocat de la imatge. Pel que fa al sistema ARBRES-X, un dels principals objectius perseguits durant aquest doctorat ha estat la integració del sensor en un petit UAV MP superant les restriccions de pes, grandària i aerodinàmica de la plataforma. S'espera que l'ús d'aquest tipus de plataformes obri noves possibilitats en la detecció remota SAR aerotransportada, ja que ofereix molta més versatilitat que els UAV d'ales fixes habituals. S'han avaluat diferents estratègies de vol innovadores amb aquest tipus de plataformes i s'han obtingut resultats preliminars amb l'ús del sistema ARBRES-X. Durant el transcurs del present treball, s'ha dedicat molt esforç a assolir els primers resultats experimentals d'interferometria de múltiple passada obtinguts amb l'UAV MP conjuntament amb l'ARBRES-X. A més, el sensor ha estat dotat de capacitats totalment polarimètriques aplicant les millores desenvolupades al radar RISKSAR-X, el qual constitueix un altre exemple de la dualitat entre ambdós sistemes. Finalment, s'han realitzat amb èxit una apertura vertical i semicircular obtenint imatges SLC de l'escenari, el qual permet preveure la capacitat de l'UAV MP per a realitzar imatges tomogràfiques i apertures circulars completes en el futur. En conclusió, l'UAV MP és una plataforma prometedora que obre nous potencials per a diverses aplicacions, com ara la interferometria de múltiple passada o la tomografia diferencial amb la realització de trajectòries gairebé arbitràries.Postprint (published version

Contribution to ground-based and UAV SAR systems for Earth observation

Mankind's way of life is the main driver of a planetary-scale change that is marked by the growing of human population's demand of energy, food, goods, services and information. As a result, it have emerged new ecological, economical, social and geopolitical concerns. In this scenario, SAR remote sensing is a potential tool that provides unique information about the Earth's properties and processes that can be used to solve societal challenges of local and global dimension. SARs, which are coherent systems that are able to provide high resolution images with weather independence, represent a suitable alternative for EO with diverse applications. Some examples of SAR application areas are topography (DEM generation with interferometry), agriculture (crop classification or soil moisture), or geology (monitoring surface deformation). In this framework, the encompassing objective of the present doctoral work has been part of the implementation and the subsequent evaluation of capabilities of two X-band SAR sensors. On the one hand, the RISKSAR-X radar designed to be operated at ground to monitor small-scale areas of observation and, on the other, the ARBRES-X sensor designed to be integrated into small UAVs. Despite its inherently dissimilar conception, the concurrence of both sensors has been evidenced along this manuscript. By taking advantage of the similarities between them, it has been possible to analogously assess both sensors to obtain conclusions. In this context, the common link has been the development of the polarimetric OtF operation mode of the RISKSAR-X, allowing this sensor to be operated equivalently to the ARBRES-X. Regarding the RISKSAR-X SAR sensor, several hardware contributions have been developed during part of this Ph.D. with the aim of improving the system performance. By endowing the system with the capability to operate in the fully polarimetric OtF acquisition mode, the relative long scanning time has been reduced. It is of great interest since the measured scatterers that present a short term variable reflectivity during the scanning time, such as moving vegetation, may degrade the extracted parameters from the retrieved data and the SAR image reconstruction. During this doctoral activity, it has been studied the image blurring, the decorrelation and the coherence degradation introduced by this effect. Furthermore, a new term in the differential interferometric coherence that takes into account the image blurring has been introduced. Concerning the ARBRES-X SAR system, one of the main objectives pursued during this Ph.D. has been the integration of the sensor into a small UAV MP overcoming restrictions of weight, size and aerodynamics of the platform. The use of this type of platforms is expected to open up new possibilities in airborne SAR remote sensing, since it offers much more versatility than the commonly used fixed wings UAVs. Different innovative flight strategies with this type of platforms have been assessed and some preliminary results have been obtained with the use of the ARBRES-X SAR system. During the course of the present doctoral work, much effort has been devoted to achieve the first experimental repeat-pass interfereometric results obtained with the UAV MP together with the ARBRES-X. Moreover, the sensor has been endowed with fully polarimetric capabilities by applying the improvements developed to the RISKSAR-X radar, which is another example of the duality between both systems. Finally, a vertical and a semicircular aperture have been successfully performed obtaining SLC images of the scenario, which envisages the capability of the UAV MP to perform tomographic images and complete circular apertures in the future. In conclusion, the UAV MP is a promising platform that opens new potentials for several applications, such as repeat-pass interferometry or differential tomography imaging with the realization of almost arbitrary trajectories.El mode de viure de la humanitat és el principal motor d'un canvi a escala planetària que està marcat per la creixent demanda d'energia, d'aliment, de béns, de serveis i d'informació de les poblacions humanes. Com a resultat, han sorgit noves inquietuds ecològiques, econòmiques, socials i geopolítiques. En aquest escenari, la detecció remota SAR és una eina potencial que proporciona informació única sobre les propietats i processos de la Terra que es pot utilitzar per resoldre reptes socials de dimensió local i global. Els SARs, que són sistemes coherents que poden proporcionar imatges d'alta resolució amb independència del temps, representen una alternativa adequada per a l'observació de la Terra. Alguns exemples d'àrees d'aplicació SAR són la topografia (generació de DEM amb interferometria), l'agricultura (classificació de cultius o humitat del sòl) o la geologia (monitoratge de deformació superficial). En aquest context, l'objectiu general del present doctorat ha estat part de la implementació i posterior avaluació de les capacitats de dos sensors SAR de banda X. D'una banda, el radar RISKSAR-X dissenyat per funcionar a terra i monitoritzar àrees d'observació a petita escala i, d'altra, el sensor ARBRES-X dissenyat per ser integrat en petits UAVs. Malgrat la seva concepció inherentment diferent, la concurrència d'ambdós sensors s'ha evidenciat al llarg d'aquest manuscrit. Aprofitant les similituds entre ells, s'han pogut avaluar de forma anàloga els dos sensors per obtenir conclusions. En aquest sentit, el vincle comú ha estat el desenvolupament del mode de funcionament polimètric OtF del RISKSAR-X, permetent que aquest sensor operi de forma equivalent a l'ARBRES-X. Pel que fa al sensor RISKSAR-X, s'han desenvolupat diverses contribucions hardware durant part d'aquest doctorat amb l'objectiu de millorar el rendiment del sistema. En dotar el sistema de la possibilitat d'operar en el mode d'adquisició totalment polarimètric OtF, s'ha reduït el relatiu llarg temps d'escaneig. Això és de gran interès ja que els blancs mesurats que presenten una reflectivitat variable a curt termini, com ara la vegetació en moviment, poden degradar els paràmetres extrets de les dades recuperades i la reconstrucció d'imatges SAR. Durant aquesta activitat doctoral s'ha estudiat el desenfocat de la imatge, la decorrelació i la degradació de la coherència introduïts per aquest efecte. A més, s'ha introduït un nou terme en la coherència interferomètrica diferencial que té en compte el desenfocat de la imatge. Pel que fa al sistema ARBRES-X, un dels principals objectius perseguits durant aquest doctorat ha estat la integració del sensor en un petit UAV MP superant les restriccions de pes, grandària i aerodinàmica de la plataforma. S'espera que l'ús d'aquest tipus de plataformes obri noves possibilitats en la detecció remota SAR aerotransportada, ja que ofereix molta més versatilitat que els UAV d'ales fixes habituals. S'han avaluat diferents estratègies de vol innovadores amb aquest tipus de plataformes i s'han obtingut resultats preliminars amb l'ús del sistema ARBRES-X. Durant el transcurs del present treball, s'ha dedicat molt esforç a assolir els primers resultats experimentals d'interferometria de múltiple passada obtinguts amb l'UAV MP conjuntament amb l'ARBRES-X. A més, el sensor ha estat dotat de capacitats totalment polarimètriques aplicant les millores desenvolupades al radar RISKSAR-X, el qual constitueix un altre exemple de la dualitat entre ambdós sistemes. Finalment, s'han realitzat amb èxit una apertura vertical i semicircular obtenint imatges SLC de l'escenari, el qual permet preveure la capacitat de l'UAV MP per a realitzar imatges tomogràfiques i apertures circulars completes en el futur. En conclusió, l'UAV MP és una plataforma prometedora que obre nous potencials per a diverses aplicacions, com ara la interferometria de múltiple passada o la tomografia diferencial amb la realització de trajectòries gairebé arbitràries

Subsurface radar imaging from space

© Cranfield University, 2018Ground Penetrating Radar (GPR) and Synthetic Aperture Radar (SAR) are two widely used techniques for acquiring radar images. GPR, as its name suggests, produces radar images of the below ground environment. SAR is a remote sensing technique which allows moving radar systems to produce radar images with dramatically improved resolutions over conventional radar systems. Despite their benefits, both GPR and SAR suffer from certain limitations. In the case of GPR, the radar system has to be in close proximity with the subsurface volume being surveyed, which limits the process to relatively small areas that are easily accessible. SAR allows large areas to be surveyed rapidly from large distances, but cannot distinguish buried objects from surface objects. This thesis focuses on a radar technique that offers the opportunity to overcome these limitations and allow subsurface radar imaging of large areas using radar data gathered by remote sensing systems. This novel technique is known as Virtual Bandwidth SAR (VB-SAR). VB-SAR utilises changes in soil moisture over a series of SAR images to differentiate buried objects from objects on the surface. In addition to this differentiation, VB-SAR also allows extremely high (centimetre scale) subsurface range resolutions to be obtained from SAR images with range resolutions measured in metres. This research has experimentally demonstrated the basic feasibility of performing remote subsurface radar imaging with the VB-SAR scheme. Within the laboratory environment a buried target has been successfully imaged using VB-SAR and the fundamentals of VB-SAR have been verified. Dramatic increases in subsurface range resolutions have been demonstrated, as has the ability of the VB-SAR scheme to work correctly over a range of radar frequencies, observation angles and polarisations. This laboratory work has been enabled by use of the Tomographic Profiling (TP) imaging scheme. TP is a synthetic aperture based imaging algorithm, but unlike conventional SAR TP produces images with a constant look angle over the entire imaging scene. This enabled the performance of the VB-SAR imaging scheme to be easily evaluated over a range of look angles using a single radar dataset and simplified the experimental setup. In addition to the experimental work, simulation exercises have been conducted and image processors have been implemented. Simulation, using a simulator created as part of this work, has allowed testing of the VB-SAR scheme in a range of scenarios (sidelooking SAR, different soils, multiple buried targets). The image processor work has implemented a high performance TP processor and a practical VB-SAR imager

Sensors for Desert Surveillance

Various types of sensors-visible, passive night vision, infrared, synthetic aperture radar, etc can be used for desert surveillance. The surveillance capability of these sensors depends to a large extent, on various atmospheric effects, viz., absorption, scattering, aerosol, turbulence, and optical mirage. In this paper, effects of various atmospheric phenomena on the transmission of signals, merits and demerits of different means of surveillance under desert environmental conditions are discussed. Advanced surveillance techniques, ie, multisensor fusion, multi and hyperspectral imaging, having special significance for desert surveillance, have also been discussed

Metrics to evaluate compressions algorithms for RAW SAR data

Modern synthetic aperture radar (SAR) systems have size, weight, power and cost (SWAP-C) limitations since platforms are becoming smaller, while SAR operating modes are becoming more complex. Due to the computational complexity of the SAR processing required for modern SAR systems, performing the processing on board the platform is not a feasible option. Thus, SAR systems are producing an ever-increasing volume of data that needs to be transmitted to a ground station for processing. Compression algorithms are utilised to reduce the data volume of the raw data. However, these algorithms can cause degradation and losses that may degrade the effectiveness of the SAR mission. This study addresses the lack of standardised quantitative performance metrics to objectively quantify the performance of SAR data-compression algorithms. Therefore, metrics were established in two different domains, namely the data domain and the image domain. The data-domain metrics are used to determine the performance of the quantisation and the associated losses or errors it induces in the raw data samples. The image-domain metrics evaluate the quality of the SAR image after SAR processing has been performed. In this study three well-known SAR compression algorithms were implemented and applied to three real SAR data sets that were obtained from a prototype airborne SAR system. The performance of these algorithms were evaluated using the proposed metrics. Important metrics in the data domain were found to be the compression ratio, the entropy, statistical parameters like the skewness and kurtosis to measure the deviation from the original distributions of the uncompressed data, and the dynamic range. The data histograms are an important visual representation of the effects of the compression algorithm on the data. An important error measure in the data domain is the signal-to-quantisation-noise ratio (SQNR), and the phase error for applications where phase information is required to produce the output. Important metrics in the image domain include the dynamic range, the impulse response function, the image contrast, as well as the error measure, signal-to-distortion-noise ratio (SDNR). The metrics suggested that all three algorithms performed well and are thus well suited for the compression of raw SAR data. The fast Fourier transform block adaptive quantiser (FFT-BAQ) algorithm had the overall best performance, but the analysis of the computational complexity of its compression steps, indicated that it is has the highest level of complexity compared to the other two algorithms. Since different levels of degradation are acceptable for different SAR applications, a trade-off can be made between the data reduction and the degradation caused by the algorithm. Due to SWAP-C limitations, there also remains a trade-off between the performance and the computational complexity of the compression algorithm.Dissertation (MEng)--University of Pretoria, 2019.Electrical, Electronic and Computer EngineeringMEngUnrestricte

Biomass Representation in Synthetic Aperture Radar Interferometry Data Sets

This work makes an attempt to explain the origin, features and potential applications of the elevation bias of the synthetic aperture radar interferometry (InSAR) datasets over areas covered by vegetation. The rapid development of radar-based remote sensing methods, such as synthetic aperture radar (SAR) and InSAR, has provided an alternative to the photogrammetry and LiDAR for determining the third dimension of topographic surfaces. The InSAR method has proved to be so effective and productive that it allowed, within eleven days of the space shuttle mission, for acquisition of data to develop a three-dimensional model of almost the entire land surface of our planet. This mission is known as the Shuttle Radar Topography Mission (SRTM). Scientists across the geosciences were able to access the great benefits of uniformity, high resolution and the most precise digital elevation model (DEM) of the Earth like never before for their a wide variety of scientific and practical inquiries. Unfortunately, InSAR elevations misrepresent the surface of the Earth in places where there is substantial vegetation cover. This is a systematic error of unknown, yet limited (by the vertical extension of vegetation) magnitude. Up to now, only a limited number of attempts to model this error source have been made. However, none offer a robust remedy, but rather partial or case-based solutions. More work in this area of research is needed as the number of airborne and space-based InSAR elevation models has been steadily increasing over the last few years, despite strong competition from LiDAR and optical methods. From another perspective, however, this elevation bias, termed here as the “biomass impenetrability”, creates a great opportunity to learn about the biomass. This may be achieved due to the fact that the impenetrability can be considered a collective response to a few factors originating in 3D space that encompass the outermost boundaries of vegetation. The biomass, presence in InSAR datasets or simply the biomass impenetrability, is the focus of this research. The report, presented in a sequence of sections, gradually introduces terminology, physical and mathematical fundamentals commonly used in describing the propagation of electromagnetic waves, including the Maxwell equations. The synthetic aperture radar (SAR) and InSAR as active remote sensing methods are summarised. In subsequent steps, the major InSAR data sources and data acquisition systems, past and present, are outlined. Various examples of the InSAR datasets, including the SRTM C- and X-band elevation products and INTERMAP Inc. IFSAR digital terrain/surface models (DTM/DSM), representing diverse test sites in the world are used to demonstrate the presence and/or magnitude of the biomass impenetrability in the context of different types of vegetation – usually forest. Also, results of investigations carried out by selected researchers on the elevation bias in InSAR datasets and their attempts at mathematical modelling are reviewed. In recent years, a few researchers have suggested that the magnitude of the biomass impenetrability is linked to gaps in the vegetation cover. Based on these hints, a mathematical model of the tree and the forest has been developed. Three types of gaps were identified; gaps in the landscape-scale forest areas (Type 1), e.g. forest fire scares and logging areas; a gap between three trees forming a triangle (Type 2), e.g. depending on the shape of tree crowns; and gaps within a tree itself (Type 3). Experiments have demonstrated that Type 1 gaps follow the power-law density distribution function. One of the most useful features of the power-law distributed phenomena is their scale-independent property. This property was also used to model Type 3 gaps (within the tree crown) by assuming that these gaps follow the same distribution as the Type 1 gaps. A hypothesis was formulated regarding the penetration depth of the radar waves within the canopy. It claims that the depth of penetration is simply related to the quantisation level of the radar backscattered signal. A higher level of bits per pixels allows for capturing weaker signals arriving from the lower levels of the tree crown. Assuming certain generic and simplified shapes of tree crowns including cone, paraboloid, sphere and spherical cap, it was possible to model analytically Type 2 gaps. The Monte Carlo simulation method was used to investigate relationships between the impenetrability and various configurations of a modelled forest. One of the most important findings is that impenetrability is largely explainable by the gaps between trees. A much less important role is played by the penetrability into the crown cover. Another important finding is that the impenetrability strongly correlates with the vegetation density. Using this feature, a method for vegetation density mapping called the mean maximum impenetrability (MMI) method is proposed. Unlike the traditional methods of forest inventories, the MMI method allows for a much more realistic inventory of vegetation cover, because it is able to capture an in situ or current situation on the ground, but not for areas that are nominally classified as a “forest-to-be”. The MMI method also allows for the mapping of landscape variation in the forest or vegetation density, which is a novel and exciting feature of the new 3D remote sensing (3DRS) technique. Besides the inventory-type applications, the MMI method can be used as a forest change detection method. For maximum effectiveness of the MMI method, an object-based change detection approach is preferred. A minimum requirement for the MMI method is a time-lapsed reference dataset in the form, for example, of an existing forest map of the area of interest, or a vegetation density map prepared using InSAR datasets. Preliminary tests aimed at finding a degree of correlation between the impenetrability and other types of passive and active remote sensing data sources, including TerraSAR-X, NDVI and PALSAR, proved that the method most sensitive to vegetation density was the Japanese PALSAR - L-band SAR system. Unfortunately, PALSAR backscattered signals become very noisy for impenetrability below 15 m. This means that PALSAR has severe limitations for low loadings of the biomass per unit area. The proposed applications of the InSAR data will remain indispensable wherever cloud cover obscures the sky in a persistent manner, which makes suitable optical data acquisition extremely time-consuming or nearly impossible. A limitation of the MMI method is due to the fact that the impenetrability is calculated using a reference DTM, which must be available beforehand. In many countries around the world, appropriate quality DTMs are still unavailable. A possible solution to this obstacle is to use a DEM that was derived using P-band InSAR elevations or LiDAR. It must be noted, however, that in many cases, two InSAR datasets separated by time of the same area are sufficient for forest change detection or similar applications

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

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