Concepts for on-board satellite image registration, volume 1

The NASA-NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. One very specific area of interest is the preprocessing required to register imaging sensor data which have been distorted by anomalies in subsatellite-point position and/or attitude control. The concepts and considerations involved in using state-of-the-art positioning systems such as the Global Positioning System (GPS) in concert with state-of-the-art attitude stabilization and/or determination systems to provide the required registration accuracy are discussed with emphasis on assessing the accuracy to which a given image picture element can be located and identified, determining those algorithms required to augment the registration procedure and evaluating the technology impact on performing these procedures on-board the satellite

Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery

The volume of data generated by earth observation satellites has increased tremendously over the last few decades and will increase further in the coming decade thanks in particular to the launch of nanosatellites constellations. These data should open new avenues for Earth surface monitoring due to highly improved spectral, spatial and temporal resolution. Many applications depend, however, on the accuracy of the image geometric model. The geometry of optical images, whether acquired from pushbroom or frame systems, is now commonly represented using a Rational Function Model (RFM). While the formalism has become standard, the procedures used to generate these models and their accuracies are diverse. As a result, the RFM models delivered with commercial data are commonly not accurate enough for 3-D extraction, subpixel registration or ground deformation measurements. In this study, we present a methodology for RFM optimization and demonstrate its potential for 3D reconstruction using tri-stereo and multi-date Cubesat images provided by SkySat and PlanetScope, respectively. We use SkySat data over the Morenci Mine, Arizona, which is the largest copper mine in the United States. The re-projection error after the RFM refinement is 0.42 pix without using ground control points (GCPs). Comparison of our Digital Elevation Model (DEM with ~3 m GSD) with a reference DEM obtained from an airborne LiDAR survey (with ~1 m GSD) over stable areas yields a standard deviation of the elevation differences of ~3.9 m. The comparison of the two DEMs allows detecting and measuring the topographic changes due to the mine activity (excavation and stockpiles). We assess the potential of PlanetScope data, using multi-date DOVE-C images from the Shisper glacier, located in the Karakoram (Pakistan), which is known for its recent surge. We extracted DEMs in 2017 and 2019 before and after the surge. The re-projection error after the RFM refinement is 0.38 pix without using GCPs. The accuracy of our DEMs (with ~9 m GSD) is evaluated through comparison with the SRTM DEM (GSD ~30 m) and with a DEM (GSD ~2 m) calculated from Geoeye-1 (GE-1) and World-View-2 (WV-2) stereo images. The standard deviation of the elevation differences in stable areas between the PlanetScope DEM and SRTM is ~12 m, and ~7 m with the GE-1&WV-2 DEM. The mass transfer due to the surge is clearly revealed from a comparison of the 2017 and 2019 DEMs. The study demonstrates that, with the proposed scheme for RFM optimization, times series of DEM extracted from SkySat and PlanetScope images can be used to measure topographic changes due to mining activities or ice flow, and could also be used to monitor geomorphic processes such as landslides, or coastal erosion for example

Optimization of Optical Image Geometric Modeling, Application to Topography Extraction and Topographic Change Measurements Using PlanetScope and SkySat Imagery

The volume of data generated by earth observation satellites has increased tremendously over the last few decades and will increase further in the coming decade thanks in particular to the launch of nanosatellites constellations. These data should open new avenues for Earth surface monitoring due to highly improved spectral, spatial and temporal resolution. Many applications depend, however, on the accuracy of the image geometric model. The geometry of optical images, whether acquired from pushbroom or frame systems, is now commonly represented using a Rational Function Model (RFM). While the formalism has become standard, the procedures used to generate these models and their accuracies are diverse. As a result, the RFM models delivered with commercial data are commonly not accurate enough for 3-D extraction, subpixel registration or ground deformation measurements. In this study, we present a methodology for RFM optimization and demonstrate its potential for 3D reconstruction using tri-stereo and multi-date Cubesat images provided by SkySat and PlanetScope, respectively. We use SkySat data over the Morenci Mine, Arizona, which is the largest copper mine in the United States. The re-projection error after the RFM refinement is 0.42 pix without using ground control points (GCPs). Comparison of our Digital Elevation Model (DEM with ~3 m GSD) with a reference DEM obtained from an airborne LiDAR survey (with ~1 m GSD) over stable areas yields a standard deviation of the elevation differences of ~3.9 m. The comparison of the two DEMs allows detecting and measuring the topographic changes due to the mine activity (excavation and stockpiles). We assess the potential of PlanetScope data, using multi-date DOVE-C images from the Shisper glacier, located in the Karakoram (Pakistan), which is known for its recent surge. We extracted DEMs in 2017 and 2019 before and after the surge. The re-projection error after the RFM refinement is 0.38 pix without using GCPs. The accuracy of our DEMs (with ~9 m GSD) is evaluated through comparison with the SRTM DEM (GSD ~30 m) and with a DEM (GSD ~2 m) calculated from Geoeye-1 (GE-1) and World-View-2 (WV-2) stereo images. The standard deviation of the elevation differences in stable areas between the PlanetScope DEM and SRTM is ~12 m, and ~7 m with the GE-1&WV-2 DEM. The mass transfer due to the surge is clearly revealed from a comparison of the 2017 and 2019 DEMs. The study demonstrates that, with the proposed scheme for RFM optimization, times series of DEM extracted from SkySat and PlanetScope images can be used to measure topographic changes due to mining activities or ice flow, and could also be used to monitor geomorphic processes such as landslides, or coastal erosion for example

Assessment of the CORONA series of satellite imagery for landscape archaeology: a case study from the Orontes valley, Syria

In 1995, a large database of satellite imagery with worldwide coverage taken from 1960 until 1972 was declassified. The main advantages of this imagery known as CORONA that made it attractive for archaeology were its moderate cost and its historical value. The main disadvantages were its unknown quality, format, geometry and the limited base of known applications. This thesis has sought to explore the properties and potential of CORONA imagery and thus enhance its value for applications in landscape archaeology. In order to ground these investigations in a real dataset, the properties and characteristics of CORONA imagery were explored through the case study of a landscape archaeology project working in the Orontes Valley, Syria. Present-day high-resolution IKONOS imagery was integrated within the study and assessed alongside CORONA imagery. The combination of these two image datasets was shown to provide a powerful set of tools for investigating past archaeological landscape in the Middle East. The imagery was assessed qualitatively through photointerpretation for its ability to detect archaeological remains, and quantitatively through the extraction of height information after the creation of stereomodels. The imagery was also assessed spectrally through fieldwork and spectroradiometric analysis, and for its Multiple View Angle (MVA) capability through visual and statistical analysis. Landscape archaeology requires a variety of data to be gathered from a large area, in an effective and inexpensive way. This study demonstrates an effective methodology for the deployment of CORONA and IKONOS imagery and raises a number of technical points of which the archaeological researcher community need to be aware of. Simultaneously, it identified certain limitations of the data and suggested solutions for the more effective exploitation of the strengths of CORONA imagery

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Geo-rectification and cloud-cover correction of multi-temporal Earth observation imagery

Over the past decades, improvements in remote sensing technology have led to mass proliferation of aerial imagery. This, in turn, opened vast new possibilities relating to land cover classification, cartography, and so forth. As applications in these fields became increasingly more complex, the amount of data required also rose accordingly and so, to satisfy these new needs, automated systems had to be developed. Geometric distortions in raw imagery must be rectified, otherwise the high accuracy requirements of the newest applications will not be attained. This dissertation proposes an automated solution for the pre-stages of multi-spectral satellite imagery classification, focusing on Fast Fourier Shift theorem based geo-rectification and multi-temporal cloud-cover correction. By automatizing the first stages of image processing, automatic classifiers can take advantage of a larger supply of image data, eventually allowing for the creation of semi-real-time mapping applications

The SUMER Data in the SOHO Archive

We have released an archive of all observational data of the VUV spectrometer Solar Ultraviolet Measurements of Emitted Radiation (SUMER) on SOHO that has been acquired until now. The operational phase started with 'first light' observations on 27 January 1996 and will end in 2014. Future data will be added to the archive when they become available. The archive consists of a set of raw data (Level 0) and a set of data that are processed and calibrated to the best knowledge we have today (Level 1). This communication describes step by step the data acquisition and processing that has been applied in an automated manner to build the archive. It summarizes the expertise and insights into the scientific use of SUMER spectra that has accumulated over the years. It also indicates possibilities for further enhancement of the data quality. With this article we intend to convey our own understanding of the instrument performance to the scientific community and to introduce the new, standard-FITS-format database.Comment: 38 pages, 9 figures, accepted for publication by Solar Physic

High resolution radargrammetry with COSMO-SkyMed, TerraSAR-X and RADARSAT-2 imagery: development and implementation of an image orientation model for Digital Surface Model generation

Digital Surface and Terrain Models (DSM/DTM) have large relevance in several territorial applications, such as topographic mapping, monitoring engineering, geology, security, land planning and management of Earth's resources. The satellite remote sensing data offer the opportunity to have continuous observation of Earth's surface for territorial application, with short acquisition and revisit times. Meeting these requirements, the SAR (Synthetic Aperture Radar) high resolution satellite imagery could offer night-and-day and all-weather functionality (clouds, haze and rain penetration). Two different methods may be used in order to generate DSMs from SAR data: the interferometric and the radargrammetric approaches. The radargrammetry uses only the intensity information of the SAR images and reconstructs the 3D information starting from a couple of images similarly to photogrammetry. Radargrammetric DSM extraction procedure consists of two basic steps: the stereo pair orientation and the image matching for the automatic detection of homologous points. The goal of this work is the definition and the implementation of a geometric model in order to orientate SAR imagery in zero Doppler geometry. The radargrammetric model implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione - developed at the Geodesy and Geomatic Division - University of Rome "La Sapienza") is based on the equation of radar target acquisition and zero Doppler focalization Moreover a tool for the SAR Rational Polynomial Coefficients (RPCs) generation has been implemented in SISAR software, similarly to the one already developed for the optical sensors. The possibility to generate SAR RPCs starting from a radargrammetric model sounds of particular interest since, at present, the most part of SAR imagery is not supplied with RPCs, although the RPFs model is available in several commercial software. Only RADARSAT-2 data are supplied with vendors RPCs. To test the effectiveness of the implemented RPCs generation tool and the SISAR radargrammetric orientation model the reference results were computed: the stereo pairs were orientated with the two model. The tests were carried out on several test site using COSMO-SkyMed, TerraSAR-X and RADARSAT-2 data. Moreover, to evaluate the advantages and the different accuracy between the orientation models computed without GCPs and the orientation model with GCPs a Monte Carlo test was computed. At last, to define the real effectiveness of radargrammetric technique for DSM extraction and to compare the radrgrammetric tool implemented in a commercial software PCI-Geomatica v. 2012 and SISAR software, the images acquired on Beauport test site were used for DSM extraction. It is important underline that several test were computed. Part of this tests were carried out under the supervision of Prof. Thierry Toutin at CCRS (Canada Centre of Remote Sensing) where the PCI-Geomatica orientation model was developed, in order to check the better parameters solution to extract radargrammetric DSMs. In conclusion, the results obtained are representative of the geometric potentialities of SAR stereo pairs as regards 3D surface reconstruction