Geometric potential of cartosat-1 stereo imagery

Cartosat-1 satellite, launched by Department of Space (DOS), Government of India, is dedicated to stereo viewing for large scale mapping and terrain modelling applications. This stereo capability fills the limited capacity of very high resolution satellites for three-dimensional point determination and enables the generation of detailed digital elevation models (DEMs) not having gaps in mountainous regions like for example the SRTM height model.The Cartosat-1 sensor offers a resolution of 2.5m GSD in panchromatic mode. One CCD-line sensor camera is looking with a nadir angle of 26' in forward direction, the other 5' aft along the track. The Institute "Area di Geodesia e Geomatica"-Sapienza Università di Roma and the Institute of Photogrammetry and Geoinformation, Leibniz University Hannover participated at the ISPRS-ISRO Cartosat-1 Scientific Assessment Programme (CSAP), in order to investigate the generation of Digital Surface Models (DSMs) from Cartosat-1 stereo scenes. The aim of this work concerns the orientation of Cartosat-1 stereo pairs, using the given RPCs improved by control points and the definition of an innovative model based on geometric reconstruction, that is used also for the RPC extraction utilizing a terrain independent approach. These models are implemented in the scientific software (SISAR-Software per Immagini Satellitari ad Alta Risoluzione) developed at Sapienza Università di Roma. In this paper the SISAR model is applied to different stereo pairs (Castelgandolfo and Rome) and to point out the effectiveness of the new model, SISAR results are compared with the corresponding ones obtained by the software OrthoEngine 10.0 (PCI Geomatica).By the University of Hannover a similar general satellite orientation program has been developed and the good results, achieved by bias corrected sensor oriented RPCs, for the test fields Mausanne (France) and Warsaw (Poland) have been described.For some images, digital height models have been generated by automatic image matching with least squares method, analysed in relation to given reference height models. For the comparison with the reference DEMs the horizontal fit of the height models to each other has been checked by adjustment

High resolution satellite imagery orientation accuracy assessment by leave-one-out method: accuracy index selection and accuracy uncertainty

The Leave-one-out cross-validation (LOOCV) was recently applied to the evaluation of High Resolution Satellite Imagery orientation accuracy and it has proven to be an effective method alternative with respect to the most common Hold-out-validation (HOV), in which ground points are split into two sets, Ground Control Points used for the orientation model estimation and Check Points used for the model accuracy assessment. On the contrary, the LOOCV applied to HRSI implies the iterative application of the orientationmodel using all the known ground points as GCPs except one, different in each iteration, used as a CP. In every iteration the residual between imagery derived coordinates with respect to CP coordinates (prediction error of the model on CP coordinates) is calculated; the overall spatial accuracy achievable from the oriented image may be estimated by computing the usual RMSE or, better, a robust accuracy index like the mAD (median Absolute Deviation) of prediction errors on all the iterations. In this way it is possible to overcome some drawbacks of the HOV: LOOCVis a reliable and robustmethod, not dependent on a particular set of CPs and on possible outliers, and it allows us to use each known ground point both as a GCP and as a CP, capitalising all the available ground information. This is a crucial problem in current situations, when the number of GCPs to be collected must be reduced as much as possible for obvious budget problems. The fundamentalmatter to deal with was to assess howwell LOOCVindexes (mADand RMSE) are able to represent the overall accuracy, that is howmuch they are stable and close to the corresponding HOV RMSE assumed as reference. Anyway, in the first tests the indexes comparison was performed in a qualitative way, neglecting their uncertainty. In this work the analysis has been refined on the basis of Monte Carlo simulations, starting from the actual accuracy of ground points and images coordinates, estimating the desired accuracy indexes (e.g. mAD and RMSE) in several trials, computing their uncertainty (standard deviation) and accounting for them in the comparison. Tests were performed on a QuickBird Basic image implementing an ad hoc procedure within the SISAR software developed by the Geodesy and Geomatics Team at the Sapienza University of Rome. The LOOCV method with accuracy evaluated by mAD seemed promising and useful for practical case

Upgrade of foss date plug-in: Implementation of a new radargrammetric DSM generation capability

Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome "La Sapienza", and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery

Orientation models of optical High Resolution Satellite Imagery: definition, implementation and validation of original algorithms

High resolution satellite imagery became available to civil users in 1999 with the launch of Ikonos, the first civil satellite offering a spatial resolution of 1 m. Since then other high resolution satellites have been launched, among which there are EROS-A (1.8 m), QuickBird (0.61 m), Orbview-3 (1 m), EROS-B (0.7 m), Worldview-1 (0.5 m) and GeoEye-1 (0.41 m), with many others being planned to launch in the near future. High resolution satellite imagery is now available in different formats and processing levels at an affordable price, so that they already represent a possible alternative to aerial imagery, for cartographic applications and orthophoto production, especially for areas where the organization of photogrammetric surveying may be critical. Moreover, an increasing demand for terrain modelling exists so that almost all the satellites have along-track stereo acquisition capability. Many new satellites dedicated to stereo viewing, for example Cartosat-1 (2.5 m), have been launched. This enables the generation of Digital Elevation Models (DEMs) and Digital Surface Models (DSMs), and also for 3D feature extraction (e.g. for city modelling). The geomatic utilizations of satellite imagery for cartographic applications and terrain modelling require a high level geometric correction through image orientation. Some fundamental features related to the sensor models and their parameters estimation, both for single images and stereopairs orientation, were addressed and some real applications were discussed. In details, they were concerned both physical sensor models (also called rigorous models) and generalized sensor models (also called RPC models) for the orientation of basic images (level 1A) and of the image projected onto a specific object surface (usually an expanded ellipsoid derived from the WGS84) (level 1B). As regards the rigorous models, a thorough investigation of the fundamentals of their functional model was developed and the problem of parameters estimability was concerned, proposing a solution based on SVD and QR decomposition. RPC models were discussed not only with respect possible refinements by zero and first order transformations but also (and mainly) with respect the RPCs generation, based on previously established rigorous model; thanks to SVD and QR decomposition, it was showed that many RPCs are not estimable parameters, therefore they are not necessary to obtain the best achievable accuracy level. Real applications demonstrated that rigorous and RPC models both for Level 1A and Level 1B imagery can provide orientation accuracy at 1-1.5 pixel level in the horizontal components, and at 1-2 pixel level in the height for stereopairs (even better with Cartosat-1 and slightly worse with EROS-1)

Orientation models of optical High Resolution Satellite Imagery: definition, implementation and validation of original algorithms

High resolution satellite imagery became available to civil users in 1999 with the launch of Ikonos, the first civil satellite offering a spatial resolution of 1 m. Since then other high resolution satellites have been launched, among which there are EROS-A (1.8 m), QuickBird (0.61 m), Orbview-3 (1 m), EROS-B (0.7 m), Worldview-1 (0.5 m) and GeoEye-1 (0.41 m), with many others being planned to launch in the near future. High resolution satellite imagery is now available in different formats and processing levels at an affordable price, so that they already represent a possible alternative to aerial imagery, for cartographic applications and orthophoto production, especially for areas where the organization of photogrammetric surveying may be critical. Moreover, an increasing demand for terrain modelling exists so that almost all the satellites have along-track stereo acquisition capability. Many new satellites dedicated to stereo viewing, for example Cartosat-1 (2.5 m), have been launched. This enables the generation of Digital Elevation Models (DEMs) and Digital Surface Models (DSMs), and also for 3D feature extraction (e.g. for city modelling). The geomatic utilizations of satellite imagery for cartographic applications and terrain modelling require a high level geometric correction through image orientation. Some fundamental features related to the sensor models and their parameters estimation, both for single images and stereopairs orientation, were addressed and some real applications were discussed. In details, they were concerned both physical sensor models (also called rigorous models) and generalized sensor models (also called RPC models) for the orientation of basic images (level 1A) and of the image projected onto a specific object surface (usually an expanded ellipsoid derived from the WGS84) (level 1B). As regards the rigorous models, a thorough investigation of the fundamentals of their functional model was developed and the problem of parameters estimability was concerned, proposing a solution based on SVD and QR decomposition. RPC models were discussed not only with respect possible refinements by zero and first order transformations but also (and mainly) with respect the RPCs generation, based on previously established rigorous model; thanks to SVD and QR decomposition, it was showed that many RPCs are not estimable parameters, therefore they are not necessary to obtain the best achievable accuracy level. Real applications demonstrated that rigorous and RPC models both for Level 1A and Level 1B imagery can provide orientation accuracy at 1-1.5 pixel level in the horizontal components, and at 1-2 pixel level in the height for stereopairs (even better with Cartosat-1 and slightly worse with EROS-1)

VADASE reliability and accuracy of real-time displacement estimation: Application to the Central Italy 2016 earthquakes

The goal of this article is the illustration of the newfunctionalities of the VADASE (Variometric Approach for Displacements Analysis Stand-alone Engine) processing approach. VADASE was presented in previousworks as an approach able to estimate in real time the velocities and displacements in a global reference frame (ITRF), using high-rate (1 Hz or more) carrier phase observations and broadcast products (orbits, clocks) collected by a stand-alone GNSS receiver, achieving a displacements accuracy within 1-2 cm (usually better) over intervals up to a few minutes. It has been well known since the very first implementation and testing of VADASE that the estimated displacements might be impacted by two different effects: spurious spikes in the velocities due to outliers (consequently, displacements, obtained through velocities integration, are severely corrupted) and trends in the displacements time series, mainly due to broadcast orbit and clock errors. Two strategies are herein introduced, respectively based on Leave-One-Out cross-validation (VADASE-LOO) for a receiver autonomous outlier detection, and on a network augmentation strategy to filter common trends out (A-VADASE); they are combined (first, VADASE-LOO; second, A-VADASE) for a complete solution. Moreover, starting fromthis VADASE improved solution, an additional strategy is proposed to estimate in real time the overall coseismic displacement occurring at each GNSS receiver. New VADASE advances are successfully applied to the GPS data collected during the recent three strong earthquakes that occurred in Central Italy on 24 August and 26 and 30 October 2016, and the results are herein presented and discussed. The VADASE real-time estimated coseismic displacements are compared to the static ones derived from the daily solutions obtained within the standard post-processing procedure by the Istituto Nazionale di Geofisica e Vulcanologia

Development of multi-purposes procedures and service tools for GNSS data processing finalized to monitor a deep-seated earthslide in the Dolomites (Italy)

The Corvara landslide is an active, large-scale, deep-seated and slow moving earthslide of about 30 Mm3 located in the Dolomites (Italy). It is frequently damaging a national road and, occasionally, isolated buildings and recre- ational ski facilities. In this work we present the analysis performed on data acquired thank to the installation of 3 DualFrequency GPS in permanent acquisition installed in the accumulation, track and source zone of the active portion of the landslide. In particular two years (2014 and 2015) of data were processed with several approaches and goals: daily time series were produced through Precise Point Positioning and Differential Positioning using both scientific packages and automatic on line tool based on open source libraries, specifically developed in order to provide a prototypal service. The achievable results based on single frequency (L1) data processing were also investigated in order to pave the way to the deployment of lowcost GPS receiver for this kind of application. Moreover, daily and sub-daily phenomena were analyzed. Different strategies were investigated in order to de- scribe the kinematics on the basis of 0.2 Hz data collected by the 3 permanent receivers. For particular events also the variometric approach, through the recent advances of VADASE, was applied, to detect significant movements. Finally, tropospheric parameters were estimated over the whole period in order to give a contribution to the SAR interferometry techniques. Also for this specific purpose and application, the possibilities of single frequency use were assessed

Protocollo operativo per la validazione geometrica di immagini satellitari ad alta risoluzione

Nel corso degli ultimi anni, la crescente disponibilità di scene acquisite da satelliti ad alta risoluzione spaziale (come GeoEye-1, WorldView-1 e 2 o Pleiades-1A e 1B) ha aperto nuovi scenari di applicazioni realizzabili a scala medio-piccola, avvicinando così il Telerilevamento alla Fotogrammetria

Protocollo operativo per la validazione geometrica di immagini satellitari ad alta risoluzione

Nel corso degli ultimi anni, la crescente disponibilita\u300 di scene acquisite da satelliti ad alta risoluzione spaziale (come GeoEye-1, WorldView-1 e 2 o Pleiades-1A e 1B) ha aperto nuovi scenari di applicazioni realizzabili a scala medio-piccola, avvicinando cosi\u300 il Telerilevamento alla Fotogrammetria