A.S.Vasileisky, R.I.Shuvalov Monitoring of railroad infrastructure with the use of differential interferometric techniques of SAR data processing From Imagery to Map Digital Photogrammetric Technologies
JSC «NIIAS» is the affiliated company of the JSC Russian Railroads responsible for application of space technologies: satellite navigation systems; Earth remote sensing; satellite telecommunication systems. Provides the common scientific and technical strategy and coordinates activities of the JSC Russian Railways subdivisions, branches, private institutes, affiliated and related organizations in the field of space technologies application in the railway transport. Space Technology Application Center of NIIAS was founded in 2008.
Satellite monitoring for the railroad transport Before explosion Quick-Bird, 0,6 m After explosion Quick-Bird, 0,6 m Benefits of ERS data Unbiased objective data Operative imaging Metric measurements Clear visual representation Broad swath of survey High information content (different spectral bands) High detailed Relatively low cost Digital representation Possibility for direct integration with GIS systems Observation of the effect of explosion at railroad station in Korea by optical remote sensing system
Progress in satellite radar Earth remote sensing sistems ERS-2 C, 30m, VV ENVISAT С, 30-150m, HH,VV,HV,VH Deployment of multi-satellite SAR systems started Huge archives of SAR data, experience of processing and application are collected RADARSAT-1 C, 8-100m, HH Spatial resolution of SAR imagery became equal to optical ERS data Modern SAR systems may change by request imaging mode (polarization combination, spatial resolution) ALOS L, 7-100m, HH,VV,HV,VH RADARSAT-2 C, 3-100м, HH,VV,HV,VH COSMO-SkyMed X, 1-100m, HH,VV,HV,VH TerraSAR-X X, 1-16m, HH,VV,HV,VH...... 1995 2002 2006 2007
Features of data, collected by satellite radar remote sensing systems Diagram of active imaging of the Earth surface by satellite radar with synthetic aperture Benefits of data, collected by satellite radar remote sensing systems Independence form the illumination conditions (day or night) Independence from cloud coverage Presence of both amplitude and phase information makes it possible DEM generation and direct accurate estimation of shifts of the ground surface Capability of imaging in different polarization combinations Possibility to select spatial resolution by demand Broad swath
Capability of the radar data application for railroad transport system TerraSAR-X, 1 m Quick-Bird, 0,6 m Spatial resolution of the modern SAR satellite systems TerraSAR-X and COSMO-SkyMed is compatible with the resolution provided by traditional optical Earth remote sensing systems. Railroad tracks, trains, locomotives and infrastructure objects are excellent reflectors of radar signal and are stable recognized at SAR images.
Areas of SAR data application for railway transport system Benefits of SAR data Independence of image quality form illumination conditions and cloud coverage Presence of both amplitude and phase information DEM generation and direct estimation of the ground surface displacements with high accuracy Operative imaging of areas affected by emergency cases and disasters for evaluation of damage and work out correct means to minimize consequences Direct generation of precise digital terrain models (DTM) and digital elevation models (DEM) Accurate estimation of the ground surface displacements for detection of potentially dangerous railroad parts and for monitoring of natural and artificial impacts on the railway infrastructure: - monitoring of railroad lines in karst areas; - monitoring of railroad lines affected by landslides, rockfalls, slip erosion; - monitoring of railroad lines in permafrost areas.
Evaluation of emergency cases and disaster effect on railway transport objects Example of flooding observation and evaluation of caused damages by SAR data
Monotoring of karst areas Berezniaki, July 2007 Karst downfall resulted by accident at potash mine lead to destruction of the railroad infrastructure objects
Мonitoring of karst areas Evolution of downfall in Berezniaki Август 2007 г. Size of cone - 50х70х15 m track subsidence - 44 mm January 2008 Size of cone - 337х202 m complete destruction of the railroad track and infrastructure objects
Monitoring of karst processes in Dzershinsk area Influence of karst events on railroad track and infrastructure objects near Dzerzhinsk town February 1995 railroad track subsidence at Seima-Zholnono February 2007 karst cone formation with the 18 m diameter at Dzerzhinsk- Igumnovo track 2007 downfalls of ground surface near Kalininskaya station, sink lakes formation, river Chernaya disappear
Monitoring of karst processes in Dzerzhynsk area SAR imagery of the Dzerzhinsk town area obtained by TerraSAR-X in 2008 and acceptable for differential inteferometric processing - 05.03.2008, StripMap, VV, 3 m - 16.03.2008, StripMap, VV, 3 m - 23.03.2008, StripMap, VV, 3 m - 27.03.2008, StripMap, VV, 3 m - 06.06.2008, StripMap, VV, 3 m - 09.07.2008, StripMap, VV, 3 m - 11.08.2008, StripMap, VV, 3 m
Monitoring of termokarst events, landslides, railroad track downfalls Deformation of bridge at Norilskaya river Destruction of railroad track and roadbed caused by landslide process as a result of drainage damage Torrent attack the railway track Tuapse-Adler Deformation of railroad Kharp-Labytnangi caused by cryogenic processes
Monitoring of cryogenic processes influence on railway infrastructure Shimanovskaya 12.06.2008 Derail of train: - 13 carriages derailed, - 60 passengers affected - 5 passengers hospitalized Seletkan
Pilot project of railroad monitoring Tuapse-Adler Analysis of archive SAR data: ERS-1/2, 10 past years WebGIS Displacement Evolution Mean Velocity
Technology of monitoring of potentially dangerous railroad tracks SAR data Detection of the ground surface displacements map of the ground surface displacements optical images railroad events information map of railroad infrastructure Detection of potentially dangerous impacts Collection and processing of coordinate and supplement information on the railroad infrastructure map of potentially dangerous influences objects GIS-system with the limited access through the internal network Maintenance and reparation instructions Traffic limitation instructions
Характеристика участка Туапсе-Адлер Северо-Кавказской ж.д. В 2007 году международным олимпийским комитетом г.сочи был выбран столицей зимних Олимпийских Игр 2014 г. Основные транспортные потоки, связанные со строительством олимпийских объектов пройдут по участку Туапсе-Адлер Северо-Кавказской ж.д.
Dangerous natural influences at Tuapse-Adler railroad
Results of Tuapse-Adler railroad inspection Database of impacts of natural processes caused damage of the railway infrastructure objects for the last 50 years. Map of potentially dangerous natural and artificial impacts on railway infrastructure From Imagery to objects. Map Digital Photogrammetric Technologies
Detection of potentially-dangerous processes and events Thematic interpretation of optical imagery. Recognition of potentially dangerous for railroad lines natural and artificial processes and impacts Quick-Bird, 0,6 m
Map of potentially-dangerous natural and artificial processes
Retrospective analysis of SAR data - selection of characteristic features of dangerous events ENVISAT Study of archive data -ERS1/2 - ENVISAT Order new images - ALOS PalSAR - TerraSAR-X - COSMO-SkyMed Detailed interferogram study in the areas of landslide events ENVISAT
PHOTOMOD-Radar software package for advanced processing of SAR imagery Applications: DEM generation Ground subsubsidence monitoring Land use characterization Oil spill and ship detection Ice situation monitoring Cartography Emergency situation control and others
PHOTOMOD-Radar large number of supported SAR missions Almaz-1 ERS-1/2 JERS-1 SIR-C/X Radarsat-1/2 Envisat ALOS TerraSAR-X COSMO-SkyMed
PHOTOMOD-Radar structure of modules Classification Texture analysis Viewer Viewer Features Features Extraction Extraction Import/ Import/ Export Export Raster data presented in internal format Raster data presented in internal format Utilities Utilities Image Image Enhancement Enhancement Save subset Speckle-noise Image Mirror suppression Edge detection Insert subset Wavelet filtering Rotate image File calculator Create new file Resample image Change data type Complex operations Radargrammetry Radargrammetry InSAR/DInSAR processor InSAR simulation Geocoding processor Stereo processor Sea Sea Applications Applications Oil slicks detection Ship detection Sea waves analysis
PHOTOMOD-Radar InSAR/DinSAR processor Digital elevation models using SAR interferometric technique Digital displacement maps using SAR differential interferometric technique Features: Orbit correction tool Baseline correction tool: - based on baseline components values - based on ground control points Sub-pixel co-registration accuracy Set of phase filters Rich collection of phase unwrapping methods
PHOTOMOD-Radar DinSAR processing Evaluation of the Earth surface displacements interferometric pair of images Input DEM Two-pass differential interferometric technique Interferometric processing Interferogram simulation PHOTOMOD-Radar supports also three-pass and four-pass differential interferometric processing real phase difference simulated phase difference differential interferogram Digital map of the Earth surface displacements
PHOTOMOD-Radar Two-pass DinSAR processing example Two SAR images of volcano Kluchevskoy (Russia, Kamchatka region) Master SIR-C image Input SRTM DEM Slave SIR-C image
PHOTOMOD-Radar Two-pass DinSAR processing example Coherence Interferogram
PHOTOMOD-Radar Two-pass DinSAR processing example Master image DEM in Master s coordinates Simulated interferogram
PHOTOMOD-Radar Two-pass DinSAR processing example Real interferogram Simulated interferogram
PHOTOMOD-Radar Two-pass DinSAR processing example Differential interferogram Unwrapped differential interferogram
PHOTOMOD-Radar Two-pass DinSAR processing example Geocoded master image Digital displacement map +0.21 m +0.16 m +0.10 m +0.05 m -0.01 m -0.06 m -0.12 m -0.17 m
PHOTOMOD-Radar Two-pass DinSAR processing example Glacier Zulchenok Erman Glacier m. Ploskaya Dalnaya (vlc. Ushkovsky) Glacier Sopochny Volcano Kluchevskaya Sopka m. Kamen Bogdanovich Glacier Result interpretation: glaciers motion has been approved by in-site observations
PHOTOMOD-Radar InSAR processing Precise DEM generation Subset of TerraSAR-X interferometric pair Saratov, Russia, 2008
PHOTOMOD-Radar InSAR processing Precise DEM generation Interferogram Coherence map
PHOTOMOD-Radar InSAR processing Precise DEM generation Geocoded image Generated DEM 75 m 295 m
Alexander S. Vasileisky NIIAS Design & Research Institute for Information Technology, Signaling and Telecommunications on Railway Transport Thank you for attention! Roman I. Shuvalov Racurs 5 Orlikov per., 107996 Moscow, 13-A Yaroslavskaya st., 129366 Moscow, Russia Russia +7 (495) 967-77-02 +7 (495) 720-51-27 A.Vasileisky @ gismps.ru info @ racurs.ru From Imagery to Map Digital Photogrammetric Technologies