Preliminary analysis of InSAR data from south-west part of Upper Silesian Coal Basin
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1 GOSPODARKA SUROWCAMI MINERALNYMI Tom Zeszyt 3 KATARZYNA MIREK*, ZBIGNIEW ISAKOW** Preliminary analysis of InSAR data from south-west part of Upper Silesian Coal Basin Introduction The Upper Silesian Coal Basin (USCB) is characterised by a complicated geological structure, which is affected by the over 200-year hard coal mining. USCB is one of the world s biggest mining centres. The negative aspect of such a magnitude of exploitation is visible on the surface in the form of surface deformation, subsidence and induced seismicity and it necessitate monitoring the USCB area. With the use of an established geodetic network in the first case, and by means of a seismic network in the second case. The availability of satellite data resulted in the development of novel methods, which can significantly affect the monitoring quality of an endangered area. Interferometric synthetic aperture radar is powerful tool for mapping the Earth s land, ice and even the sea surface topography. By bouncing signals from a radar satellite off the ground in successive orbits and looking at the differences between the images, interferometric synthetic aperture radar can detect small differences in the distance between its position and the ground as the land surface moves whether up or down. InSAR shows spatial patterns of deformation and in combination with ground-based monitoring gives unprecedented insight into a wide range of earth science processes (e.g. Zebker, Goldstein 1986; Gabriel et al. 1989; Goldstein et al. 1993; Massonet, Adragna 1993; Weydahl 1996; Rott et al. 1999). * Dr in., AGH University of Science and Technology, Department of Geoinformatics and Applied Computer Science. ** Dr in., EMAG Centre, Katowice.
2 240 A digital SAR image can be seen as a mosaic of pixels. Each pixel gives a complex number that carries amplitude and phase information about the microwave field backscattered by all the scatterers (such as rocks, buildings, vegetation) within the corresponding resolution cell projected on the ground. The amplitude depends on the roughness and typically, exposed rocks and urban areas show strong amplitudes, whereas smooth flat surfaces (like quiet water basins) show low amplitudes. The phase is directly linked to the distance between the observed terrain and the satellite sensor. By calculating the differences in phases (interferogram) between two sets of data, one can determine ground displacements that have occurred in the time between the data acquisitions. Interferogram is measured in radians of phase difference and, due to the cyclic nature of phase, is recorded as repeating fringes which each represent a full 2 cycle. One full 2 cycle corresponds to a change of range of a half a wavelength (for ERS-1/2 and ENVISAT satellites it is about 2,5 cm). InSAR was proposed for monitoring of hard coal mining influence for the first time by Ostaficzuk (Ostaficzuk 1995). This technique was applied for monitoring of mining subsidence in the Selby Coalfield (United Kingdom) for the first time (Stow, Wright 1997). In Poland InSAR for mining monitoring was applied with success in Upper Silesian Coal Basin (Perski 1998; Perski 1999a; Perski 1999b; Perski, Jura 1999) and Legnica-G³ogów Copper Mining District (Krawczyk, Perski 2000; Popio³ek et al. 2002; Popio³ek 2003; Popio³ek et al. 2006). The Permanent Scatterer Interferometry technique (PSInSAR) is an upgrade of InSAR. This technique was developed to resolve problem of geometrical and temporal decorrelation (Ferretti et al. 2000, Ferretti et al. 2001). Furthermore, by using a large amount of data, atmospheric signal is estimated and corrected for. PSInSAR technique uses coherent radar targets (called Permanent Scatterers or PS) that can be clearly distinguished in all images and do not vary in their properties. In Poland for the first time, PSInSAR technique was used in Upper Silesian Coal Basin by Graniczny (Graniczny et al. 2005; Graniczny 2006) and next it was developed by another researchers (Leœniak, Porzycka 2008a; Leœniak, Porzycka 2008b; Mirek, Mirek 2008). 1. Preliminary processing and data analysis The interferogram was processed from two SAR images acquired by ENVISAT satellite (tab. 1.1). SAR images were made on March and April 2008, and covered south-west part of USCB. In the first stage of processing, the whole SAR scene was processed (100 km 100 km). Typical InSAR processing chain consists of several points, such as (Hanssen 2001): data input, pre-processing, co-registration and resampling, products (computation of complex interferogram and coherence image), phase unwrapping, geocoding. However preliminary processing of selected pair of SAR images excluded phase unwrapping and geocoding. The co-registration step is fundamental in interferogram generation, as it ensures that each ground target contributes to the same (range, azimuth) pixel in both the master and the slave image.
3 241 The characteristic of data used for interferometric processing Zestawienie analizowanej pary zdjêæ TABLE 1.1 TABELA 1.1 MASTER SLAVE Baseline Perpendicular Temporal Satellite orbit date orbit date [m] baseline [m] separation ENVISAT days Where co-registration is poor or the maximum baseline is exceeded the pixel phase will become incoherent the phase becomes essentially random from pixel to pixel rather than varying smoothly, and the area appears noisy. Co-registration is usually separated in two steps: coarse and fine co-registration. Additionally, external DEMs (Digital Elevation Model) were used in co registration of selected pair of SAR images to increase precision. Next step in processing chain is resampling and interpolation. The interferometric combination of the two complex images requires evaluation of the complex values in one of the two at the pixel positions of the other. Resampling can be regarded as consisting of two subsequent steps: reconstruction of the continuous signal from its sampled version by convolution with an interpolation kernel, and sampling of the reconstructed signal at the new sampling locations. One of the most important step in processing chain is interferogram formation. A complex interferogram is constructed by a pointwise complex multiplication of corresponding pixels in both datasets (1.1): * y y y exp( j ) y exp( j ) y y exp( j( )) (1.1) where: y 1,y 2 complex values of corresponding pixels, 1, 2 phase, j amplitude. Analysis was started from estimation of coherence. Coherence is a measure for local interferogram quality and it provides valuable information about the scatterer (Bamler, Hartl 1998). There are two main factors which determine image coherence, firstly the perpendicular baseline (Bperp) separation of the image acquisition (a critical baseline is about 1100 m) and secondly changes in ground scattering characteristic between image acquisition (changes in vegetation, freezing, thawing or human activities such as ploughing). Several sources of coherence decorrelation can be distinguished, such as (Hanssen 2001): baseline or geometric decorrelation caused by the difference in the incidence angle between the two acquisitions, system noise caused by the characteristics of the system (e.g. antenna
4 242 characteristics), temporal decorrelation caused by too long time distance between the two acquisitions, processing induced decorrelation caused by chosen algorithms (e.g. for co registration and interpolation). Analysis of coherence demonstrated high value (fig. 1.1), which is connected with short time period and short perpendicular baseline of selected images, as well as highly urbanized area. The coherence value ranges from 0 (the interfeormetric phase is just noise) to 1 (complete absence of phase noise). Figure 1.1 illustrates coherence map, where high coherence value is represented as a white colour and lack of coherence as a black colour. Fig Coherence map Rys Wartoœæ koherencji In the presented work, external SRTM DEMs (Shuttle Radar Topography Mission Digital Elevation Models) were used for interferogram generation to reduce the errors in data processing and remove topographic phase. The interpretation of interferometric data shows distinctive concentric fringe features. The centre of the fringe is an area of maximum of surface downwarp caused by coal mining (Stow 1997; Perski 1999). Figure 1.2 shows excerpt of example interferogram. There is interferogram computed for whole SAR scene on the left side and scale up excerpt of interferogram of Knurów area on the right side. In the area of Knurów two subsidence troughs were located. Both of them consist of two interferometric fringes, correspond with 5 cm subsidence per 35 days.
5 POLAND 50 USCB Track Fig Differential interferogram (explanation in text) Rys Interferogram uzyskany z pary zdjêæ i (opis w tekœcie) Conclusions After preliminary full-scene (100km x 100km) SAR processing it was clearly visible that selected pair of SAR images was suitable for interferogram generation: analysis of coherence demonstrated high value; the interferometric phase image shows areas where subsidence troughs are clearly visible; for example in the area of Knurów two subsidence troughs were located subsidence patterns show 2 cycles of deformation, corresponding with 5 cm subsidence per 35 days; high value of coherence and concentric fringe features are good indicators to limit processing to areas of subsidence troughs and to compare them with areas of mining activity. External DEMs were used both to increase precision in co registration of selected pair of SAR images and to reduce the errors in data processing and remove topographic phase during interferogram formation. The research was partly supported by the AGH University of Science and Technology in Cracow, project no
6 244 REFERENCES B a m l e r R., H a r t l P., 1998 Synthetic Aperture Radar Interferometry. Inverse Problems, vol. 14, F e r r e t t i A., P r a t i C., R o c c a F., 2000 Nonlinear Subsidence Rate Estimation Using Permanent Scatterers in Differential SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing 38 (5), F e r r e t t i A., P r a t i C., R o c c a F., 2001 Permanent Scatterers in SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing 39 (1), G a b r i e l A.K., G o l d s t e i n R.M., Z e b k e r H.A., 1989 Mapping small elevation changes over large areas: differential radar interferometry. Journal of Geophysical Research, 94(B7), G o l d s t e i n R.M., E n g e l h a r d t H., K a m p B., F r o l i c h R.M., 1993 Satellite radar interfermetry for monitoring ice sheet motion: Application to Antarctic ice stream. Science, 262, Graniczny M.,Kowalski Z.,Jureczka J.,Czarnogórska M.,2005 TerraFirmaProject Monitoring of subsidence of Northeastern part of Upper Silesian Coal Basin. Sp. Papers Polish Geological Institute, 20, G r a n i c z n y M., 2006 Wykorzystanie technologii PSInSAR dla obserwacji przemieszczeñ powierzchni terenu na przyk³adzie Górnego Œl¹ska. Materia³y Sympozjum Warsztaty Górnicze H a n s s e n R., 2001 Radar Interferometry. Data Interpretation and Error Analysis. Kluwer Academic Publishers. K r a w c z y k A., P e r s k i Z., 2000 Application of satellite radar interferometry on the areas of udeground exploitation of copper ore in LGOM Poland. First International Congress of the International Society for Mine Surveying, vol. 2, L e œ n i a k A., P o r z y c k a S., 2008a Environment monitoring using satellite radar interferometry technique (PSInSAR). Polish Journal of Environmental Studies, vol. 17, no. 3A, L e œ n i a k A., P o r z y c k a S., 2008b Kompleksowa interpretacja pomiarów satelitarnych i naziemnych w ocenie zagro eñ na terenach górniczych i pogórniczych. Gospodarka Surowcami Mineralnymi t. 24, z. 2/3, M a s s o n e t D., A d r a g n a F., 1993 A full-scale validation of Radar Interferometry with ERS-1: the Landers earthquake. Earth Observation Quarterly, 41. M i r e k K., M i r e k J., 2008 Zastosowanie j¹drowej aproksymacji w procesie interpretacji danych PSInSAR z pó³nocnej czêœci GZW. Komputerowe Wspomaganie Badañ Naukowych, T. 15, Prace Wroc³awskiego Towarzystwa. Seria B, nr 214, O s t a f i c z u k S., 1995 Interferometry and its possibile application in geology. FORGES Remote Sensing Group Meeting. Warsaw P e r s k i Z., 1998 The test of applicability of land subsidence monitoring by InSAR ERS-1 and ERS-2 in the coal mine damaged region (Upper Silesia). International Archives of Photogrammetry and Remote Sensing, vol. XXII part 7, P e r s k i Z., 1999a Zakres interpretowalnoœci osiadañ terenu za pomoc¹ satelitarnej interferometrii radarowej (InSAR). Archiwum Fotogrametrii, Kartografii i Teledetekcji vol. 9, P e r s k i Z., 1999b Osiadania terenu GZW pod wp³ywem eksploatacji podziemnej okreœlane za pomoc¹ satelitarnej interferometrii radarowej (InSAR). Przegl¹d Geologiczny, vol. 47, nr 2, P e r s k i Z., J u r a D., 1999 ERS SAR Interferometry for Land Subsidence Detection in Coal Mining Areas. Earth Observation Quartery 63, P o p i o ³ e k E., 2003 Mo liwoœci wykorzystania nowoczesnych metod monitorowania terenu górniczego w LGOM. Mat. Symp. Warsztaty 2003, P o p i o ³ e k E., H e j m a n o w s k i R., K r a w c z y k A., P e r s k i Z., 2002 Application of Satellite Radar Interferometry to the examination of the areas of mining exploitation. Surface Mining Braunkhole & Other Minerals, vol. 54 no. 1, P o p i o ³ e k E., M a r c a k H., K r a w c z y k A., 2006 Mo liwoœci wykorzystania satelitarnej interferometrii radarowej InSAR w monitorowaniu zagro eñ górniczych. Mat. Symp. Warsztaty 2006, R o t t H., S c h e c h l B., S i e g e l A., G r a s e m a n n B., 1999 Monitoring very slow slope movements by means of SAR Interferometry: A case study from a mass waste above a reservoir in the Ötztal Alps, Austria. Geophysical Research Letters, 26(11),
7 245 S t o w R.J., W r i g h t P., 1997 Mining Subsidence Land Surveying by SAR Interferometry. 3 rd ERS Symposium, Florence. W e y d a h l D.J., 1996 Flood Monitoring in Norway Using ERS-1 SAR Images. Geoscience and Remote Sensing Symposium IGARSS 96. Z e b k e r H.A., G o l d s t e i n R.M., 1986 Topographic Mapping From Interferometric Synthetic Aperture Radar Observations. Journal of Geophysical Research, 91(B5), PRELIMINARY ANALYSIS OF INSAR DATA FROM SOUTH-WEST PART OF UPPER SILESIAN COAL BASIN InSAR, Upper Silesian Coal Basin, subsidence Key words Abstract In recent years, the usage of Synthetic Aperture Radar Interferometry technique became more and more popular and it is used in many scientific field: for creating digital elevation models (DEMs), monitoring of deformation, glacier and ice motion etc. The paper presents preliminary analysis of satellite interferometry data from south-west part of Upper Silesian Coal Basin (USCB). USCB is characterised by a complicated geological structure, which is affected by the over 200-year hard coal mining. USCB is one of the world s biggest mining centres. The negative aspect of such a magnitude of exploitation is visible on the surface in the form of surface deformation, subsidence and induced seismicity and it necessitate monitoring the USCB area. With the use of an established geodetic network in the first case, and by means of a seismic network in the second case. The availability of satellite data resulted in the development of novel methods, which can significantly affect the monitoring quality of an endangered area. Authors used pair of satellite images for interferometric processing, made in March and April In the first stage of processing, the whole SAR scene was processed (100km x 100km). External DEMs were used both to increase precision in co registration of selected pair of SAR images and to reduce the errors in data processing and remove topographic phase during interferogram formation. Analysis of coherence demonstrated high value, which is connected with short time period and short perpendicular baseline of selected images, as well as highly urbanized area. The interpretation of interferometric data shows distinctive concentric fringe features. The centre of the fringe is an area of maximum of surface downwarp caused by coal mining. In the area of Knurów two subsidence troughs were located. Both of them consist of two interferometric fringes, correspond with 5 cm subsidence per 35 days. WSTÊPNA ANALIZA DANYCH SATELITARNEJ INTERFEROMETRII RADAROWEJ Z PO UDNIOWO-ZACHODNIEJ CZÊŒCI GÓRNOŒL SKIEGO ZAG ÊBIA WÊGLOWEGO InSAR, GZW, osiadanie S³owa kluczowe Streszczenie Satelitarna interferometria radarowa staje siê coraz bardziej popularn¹ technik¹ wykorzystywan¹ w ró nych dziedzinach: od tworzenia numerycznych modeli powierzchni terenu (DEM) poprzez monitorowanie osuwisk, lodowców, osiadania terenu a po badanie zjawisk przyrodniczych i wegetacji roœlin. Niniejszy artyku³ przedstawia wstêpne wyniki analizy interferogramów utworzonych z radarowych zdjêæ satelitarnych, obejmuj¹cych po³udniowo-zachodni¹ czêœæ Górnoœl¹skiego Zag³êbia Wêglowego (GZW). GZW charakteryzuje siê skomplikowan¹ budow¹ geologiczn¹, na któr¹ dodatkowo nak³adaj¹ siê wp³ywy ponad 200 lat eksploatacji wêgla
8 246 kamiennego. Z eksploatacj¹ wêgla kamiennego wi¹ ¹ siê zagro enia spowodowane sejsmicznoœci¹ indukowan¹ oraz osiadaniem terenu. Obszar GZW jest silnie zurbanizowany, w zwi¹zku z czym zagro enia wynikaj¹ce z powstawania niecek osiadañ oraz sejsmicznoœci indukowanej wymuszaj¹ monitorowanie rejonów zwi¹zanych z eksploatacj¹ wêgla kamiennego, poprzez rozwijanie sieci geodezyjnej lub sejsmologicznej. Dostêp do danych satelitarnych spowodowa³ rozwój nowych metod, które pozwalaj¹ na objêcie monitoringiem znacznego obszaru. Do przetwarzania wykorzystano parê zdjêæ wykonanych w marcu i kwietniu 2008 roku. Zdjêcia charakteryzuj¹ siê niedu ¹ odleg³oœci¹ bazow¹ i czasow¹. Przetwarzanie zosta³o wykonane dla ca³ej sceny (100 km 100 km). Koherencja uzyskana z przetworzonych obrazów wykazuje wysokie wartoœci. Niew¹tpliwie jest to zwi¹zane z niewielk¹ odleg³oœci¹ czasow¹ i bazow¹ przetwarzanych zdjêæ oraz silnie zurbanizowanym terenem. Na uzyskanych interferogramach widoczne s¹ koncentryczne, eliptyczne pr¹ ki interferencyjne, które wskazuj¹ na tworzenie siê niecek osiadania na badanym obszarze. W okolicy Knurowa widoczne s¹ dwa eliptyczne obszary wskazuj¹ce na osiadanie powsta³e na skutek eksploatacji wêgla kamiennego. Obszary osiadanie sk³adaj¹ siê z oko³o 2 pr¹ ków, co wskazuje na osiadanie rzêdu oko³o 5 cm na 35 dni.
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