Development of the TanDEM-X Calibration Concept: Analysis of Systematic Errors

The TanDEM-X mission, result of the partnership between the German Aerospace Center (DLR) and Astrium GmbH, opens a new era in spaceborne radar remote sensing. The first bistatic satellite synthetic aperture radar mission is formed by flying the TanDEM-X and TerraSAR-X in a closely controlled helix formation. The primary mission goal is the derivation of a high-precision global digital elevation model (DEM) according to High-Resolution Terrain Information (HRTI) level 3 accuracy. The finite precision of the baseline knowledge and uncompensated radar instrument drifts introduce errors that may compromise the height accuracy requirements. By means of a DEM calibration, which uses absolute height references, and the information provided by adjacent interferogram overlaps, these height errors can be minimized. This paper summarizes the exhaustive studies of the nature of the residual-error sources that have been carried out during the development of the DEM calibration concept. Models for these errors are set up and simulations of the resulting DEM height error for different scenarios provide the basis for the development of a successful DEM calibration strategy for the TanDEM-X mission

Advanced Data Chain Technologies for the Next Generation of Earth Observation Satellites Supporting On-Board Processing for Rapid Civil Alerts

The growing number of planned Earth Observation (EO) satellites, together with the increase in payload resolution and swath, brings to the fore the generation of unprecedented volumes of data that needs to be downloaded, processed and distributed with low latency. This creates a severe bottleneck problem, which overloads ground infrastructure, communications to ground, and hampers the provision of EO products to the End User with the required performances. The European H2020 EO-ALERT project (http://eo-alert-h2020.eu/), proposes the definition of next-generation EO missions by developing an on-board high speed EO data processing chain, based on a novel flight segment architecture that moves optimised key EO data processing elements from the ground segment to on-board the satellite. EO-ALERT achieves, globally, latencies below five minutes for EO products delivery, reaching latencies below 1 minute in some scenarios. The proposed architecture solves the above challenges through a combination of innovations in the on-board elements of the data chain and the communications link. Namely, the architecture introduces innovative technological solutions, including on-board reconfigurable data handling, on-board image generation and processing for generation of alerts (EO products) using Artificial Intelligence (AI), high-speed on-board avionics, on-board data compression and encryption using AI and reconfigurable high data rate communication links to ground including a separate chain for alerts with minimum latency and global coverage. Those key technologies have been studied, developed, implemented in software/hardware (SW/HW) and verified against previously established technologies requirements to meet the identified user needs. The paper presents an overview of the development of the innovative solutions defined during the project for each of the above mentioned technological areas and the results of the testing campaign of the individual SW/HW implementations within the context of two operational scenarios: ship detection and extreme weather observation (nowcasting), both requiring a high responsiveness to events to reduce the response time to few hours, or even to minutes, after an emergency situation arises. The technologies have been experimentally evaluated during the project using relevant EO historical sensor data. The results demonstrate the maturity of the technologies, having now reached TRL 4-5. Generally, the results show that, when implemented using COTS components and available communication links, the proposed architecture can generate and delivery globally EO products/alerts with a latency lower than five minutes, which demonstrates the viability of the EO-ALERT concept. The paper also discusses the implementation on an Avionic Test Bench (ATB) for the validation of the integrated technologies chain

Scalloping Correction in TOPS Imaging Mode SAR Data

This paper presents an investigation on scalloping correction in the TOPS imaging mode for SAR systems with electronically steered phased array antennas. A theoretical simulation of the scalloping is performed and two correction methods are introduced. The simulation is based on a general cardinal sine (sinc) antenna model as well as on the TerraSAR-X antenna model. Real TerraSAR-X data acquired over rainforest are used for demonstration and verification of the scalloping simulation and correction. Furthermore a calibration approach taking into account the special TOPS imaging mode properties is introduced

Assimilating SAR-derived water level data into a hydraulic model: a case study

Satellite-based active microwave sensors not only provide synoptic overviews of flooded areas, but also offer an effective way to estimate spatially distributed river water levels. If rapidly produced and processed, these data can be used for updating hydraulic models in near real-time. The usefulness of such approaches with real event data sets provided by currently existing sensors has yet to be demonstrated. In this case study, a Particle Filter-based assimilation scheme is used to integrate ERS-2 SAR and ENVISAT ASAR-derived water level data into a one-dimensional (1-D) hydraulic model of the Alzette River. Two variants of the Particle Filter assimilation scheme are proposed with a global and local particle weighting procedure. The first option finds the best water stage line across all cross sections, while the second option finds the best solution at individual cross sections. The variant that is to be preferred depends on the level of confidence that is attributed to the observations or to the model. The results show that the Particle Filter-based assimilation of remote sensing-derived water elevation data provides a significant reduction in the uncertainty at the analysis step. Moreover, it is shown that the periodical updating of hydraulic models through the proposed assimilation scheme leads to an improvement of model predictions over several time steps. However, the performance of the assimilation depends on the skill of the hydraulic model and the quality of the observation data

Radarkaugseire rakendused metsaüleujutuste ja põllumajanduslike rohumaade jälgimiseks

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Käesolev doktoritöö keskendub radarkaugseire rakenduste arendamisele kahes keerukas looduskeskkonnas: üleujutatud metsas ja põllumajanduslikel rohumaadel. Uurimistöö viidi läbi Tartu Observatooriumis, Tartu Ülikoolis, Ventspilsi Kõrgkoolis ja Aalto Ülikoolis. Töö esimene osa käsitleb X-laineala polarimeetrilise radarisignaali käitumist regulaarselt üleujutatavas metsas Soomaa näitel ning teine osa põllumajanduslike rohumaade seisundi ja polarimeetriliste ning interferomeetriliste tehisava-radari parameetrite vahelisi seoseid. 2012 kevadel Soomaa testalal TerraSAR-X andmetega läbi viidud eksperiment näitas, et topelt-peegeldusele tundlik HH-VV polarimeetriline kanal pakub tõesti kontrastsemat tagasihajumisepõhist üleujutatud metsa eristust üleujutamata metsast kui traditsiooniline HH polarimeetriline kanal. HH-VV kanali eelis HH kanali ees on seda suurem, mida madalam on mets ning raagus tingimustes lehtmetsas oli HH-VV kanali eelis HH kanali ees suurem kui okasmetsas. Lisaks on üleujutusele tundlik HH ja VV kanali polarimeetriline faasivahe, mida on soovitatud ka varasemates töödes kasutada täiendava andmeallikana üleujutuste kaardistamisel. Käesolevas doktoritöös mõõdeti polarimeetrilise X-laineala tehisava-radari HH/VV faasivahe suurenemine üleujutuste tõttu erineva kõrgusega okas- ja lehtmetsas. 2013 a vegetatsiooniperioodil korraldati Rannu test-alal välimõõtmistega toetatud eksperiment uurimaks X- ja C-laineala polarimeetrilise ning X-laineala interferomeetrilise tehisava-radari parameetrite undlikkust rohumaade tingimuste muutustele. Ilmnes, et ühepäevase vahega kogutud X-laineala tehisava-radari interferomeetriliste paaride koherentsus korreleerus rohu kõrgusega. Koherentsus oli seda madalam, mida kõrgem oli rohi - leitud seost on võimalik potentsiaalselt rakendada niitmise tuvastamiseks. TerraSAR-X ja RADARSAT-2 polarimeetriliste aegridade analüüsi tulemusel leiti kaks niitmisele tundlikku parameetrit: HH/VV polarimeetriline koherentsus ja polarimeetriline entroopia. Niitmise järel langes HH/VV polarimeetriline koherentsus järsult ning polarimeetriline entroopia tõusis järsult. Rohu tagasikasvamise faasis hakkas HH/VV polarimeetriline koherentsus aeglaselt kasvama ning entroopia aeglaselt kahanema. Täheldatud efekt oli tugevam TerraSARX X-laineala aegridadel kui RADARSAT-2 C-riba tehisava-radari mõõtmistel ning seda selgemini nähtav mida rohkem biomassi niitmise järgselt maha jäi. Leitud HH/VV polarimeetrilise koherentsuse ja polarimeetrilise entroopia käitumine vastas taimkatte osakestepilve radarikiirguse tagasihajumismudelile. Mudeli järgi põhjus- 60 tas eelnimetatud parameetrite iseloomulikku muutust rohukõrte kui dipoolide orientatsiooni ja korrastatuse muut niitmise tõttu, mis on kooskõlas meie välimõõtmiste andmetega.This thesis presents research about the application of radar remote sensing for monitoring of complex natural environments, such as flooded forests and agricultural grasslands. The study was carried out in Tartu Observatory, University of Tartu, Ventspils University College, and Aalto University. The research consists of two distinctive parts devoted to polarimetric analysis of images from a seasonal flooding of wetlands, and to polarimetric and interferometric analysis of a summer-long campaign covering eleven agricultural grasslands. TerraSAR-X data from 2012 were used to assess the use of the double-bounce scattering mechanism for improving the mapping of flooded forest areas. The study confirmed that the HH–VV polarimetric channel that is sensitive to double-bounce scattering provides increased separation between flooded and unflooded forest areas when compared to the conventional HH channel. The increase in separation increases with decreasing forest height, and it is more pronounced for deciduous forests due to the leaf-off conditions during the study. The phase difference information provided by the HH–VV channel may provide additional information for delineating flooded and unflooded forest areas. Time series of X-band (TanDEM-X and COSMO-SkyMed) and C-band (RADARSAT-2) data from 2013 were analyzed in respect to vegetation parameters collected during a field survey. The one-day repeat-pass X-band interferometric coherence was shown to be correlated to the grassland vegetation height. The coherence was also found to be potentially useful for detecting mowing events. The polarimetric analysis of TanDEM-X and RADARSAT-2 data identified two parameters sensitive to mowing events - the HH/VV polarimetric coherence magnitude and the H2α entropy. Mowing of vegetation consistently caused the coherence magnitude to decrease and the entropy to increase. The effect was more pronounced in case of X-band data. Additionally, the effect was stronger with more vegetation left on the ground after mowing. The effect was explained using a vegetation particle scattering model. The changes in polarimetric variables was shown to be caused by the change of orientation and the randomness of the vegetation

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones