Detecting, Mapping and Monitoring of Land Subsidence in Jharia Coalfield
Total Page：16
File Type：pdf, Size：1020Kb
Detecting, mapping and monitoring of land subsidence in Jharia Coalfield, Jharkhand, India by spaceborne differential interferometric SAR, GPS and precision levelling techniques R S Chatterjee1,∗, Shailaja Thapa1, K B Singh2, G Varunakumar3 and E V R Raju4 1Indian Institute of Remote Sensing (Indian Space Research Organization), 4-Kalidas Road, Dehradun 248 001, India. 2CSIR – Central Institute of Mining and Fuel Research, Barwa Road, Dhanbad 826 001, India. 3Geodetic and Research Branch (Survey of India), 17 E.C. Road, Dehradun 248 001, India. 4Bharat Coking Coal Ltd. (Coal India Ltd.), Koyla Nagar, Dhanbad 826 005, India. ∗Corresponding author. e-mail: [email protected] The study aims at detection, mapping and monitoring of land subsidence in Jharia Coalfield, Jhark- hand, India by spaceborne DInSAR, GPS and precision levelling techniques. Using multi-frequency C- and L-band DInSAR, both slowly and rapidly subsiding areas were identified and DInSAR-based sub- sidence maps were prepared. C-band DInSAR was found useful for detection of slowly subsiding areas whereas L-band DInSAR for rapidly subsiding and/or adverse land cover areas. Due to dynamic nature of mining and adverse land cover, temporal decorrelation poses a serious problem particularly in C-band DInSAR. Specially designed InSAR coherence guided adaptive filtering was found useful to highlight the deformation fringes. Collateral GPS and levelling observations were conducted in three test sites to vali- date DInSAR measurements and to determine the net displacement vectors. We observed an appreciable horizontal displacement component of land subsidence in all the test sites. For comparison of results, we calculated InSAR coherence weighted LOS displacement rates from the unwrapped differential inter- ferograms of smaller spatial subsets and LOS projected ground-based displacement rates in three test sites. We found good agreement between DInSAR and ground-based measurements except for C-band observation in Dobari test site primarily due to large difference in observation periods and temporally inconsistent land subsidence. Collateral spaceborne and ground-based observations were also found use- ful for characterization of subsidence phenomena to determine net displacement vector and horizontal displacement component. In coal mining areas with spatially scattered and temporally irregular land subsidence phenomena, the adopted methodology can be used successfully for detection, mapping and monitoring of the subsiding areas vulnerable to future collapse. This will facilitate efficient planning and designing of surface infrastructures and other developmental structures in the mining areas and mitigation management of subsidence induced hazards. 1. Introduction motor roads, railway tracks, power lines and other In a coalfield, land subsidence poses constant developmental structures. The present study was threats to life and surface infrastructures such as carried out in Jharia Coalfield, Jharkhand, India. Keywords. Land subsidence; coal mining area; spaceborne DInSAR; GPS observation; precision levelling; net displacement; Jharia Coalfield; India. J. Earth Syst. Sci. 124, No. 6, August 2015, pp. 1359–1376 c Indian Academy of Sciences 1359 1360 R S Chatterjee et al. This is one of the most important and oldest coal- more sensitive to slow deformation and is therefore fields in the country. This is the only source of better suited for slow velocity subsidence measure- prime coking coal in India with a reserve of about ments using shorter temporal baseline data pairs. 5.3 billion tons (Acharyya 2000) in addition to On the other hand, L-band DInSAR has the advan- large quantities of medium and semi-coking coals. tage for detecting high velocity deformation gradi- Land subsidence and associated roof collapse is one ent due to its longer wavelength. Also, the InSAR of the major environmental hazards in the coalfield. coherence in L-band remains generally high for a Precise information on the spatial extent of sub- longer temporal baseline data pair which enables to siding areas and the rate of subsidence may help produce meaningful differential interferograms for in identifying the areas prone to roof collapse in a longer time span (Yue et al. 2011). In coal mining the near-future and in planning of the rehabilita- areas with unfavourable land use/land covers such tion programme. In this paper, we have studied as vegetation covered areas (Wang et al. 2010) or land subsidence by spaceborne DInSAR, GPS and rural areas with agricultural practices (Cao et al. precision levelling techniques. Spaceborne DInSAR 2008), L-band DInSAR proves to be more suitable provides spatially continuous displacement mea- for land subsidence study. surements at centimetre to sub-centimetre level We carried out multi-frequency DInSAR mea- precision with ground resolution of a few tens of surements using C- and L-band SAR data to study metres. High precision GPS observations provide both slow and rapid deformation areas. In the con- point-based displacement measurements at a pre- text of the present study area, the term ‘slow’ cision comparable to DInSAR technique. Precision means a few centimetres to a few tens of centimetres levelling is a slow and labour-intensive technique, per year and ‘rapid’ means a few tens of centimetres but it provides amazingly high precision of sub- to more than a metre per year. By spaceborne millimetre (height resolution) and millimetre (dis- DInSAR technique, we measured land subsidence tance resolution) levels with the presently available along the radar line of sight (LOS). We conducted digital level (Chatterjee 2009). precision levelling in three test sites during 2007– Many previous researchers conducted land subsi- 2008. Levelling gives point-based measurements on dence studies in coal mining areas by single frequency vertical displacement of the terrain at millimetre DInSAR technique using either C- or L-band level precision. We also conducted geodetic GPS SAR data (Stow and Wright 1997; Perski 1998, survey over the test sites to precisely measure 2000; Strozzi et al. 2001; Perski and Jura 2003; horizontal displacements. GPS observation gives Engelbrecht et al. 2011; Gong 2011). Some con- sub-centimetre level of horizontal precision. We ducted multi-frequency DInSAR using both C- and used levelling and GPS measurements to validate L-band SAR data (Ge et al. 2007; Cao et al. DInSAR-based subsidence rates and to determine 2008; Liu et al. 2009; Yue et al. 2011). Some stud- the net displacement vectors. ies were also carried out using recently available spaceborne X-band SAR data (e.g., TerraSAR-X, Cosmo-Skymed SAR data) along with C- and L- band SAR data (Walter et al. 2009; Ashrafianfar 2. Study area et al. 2011). In coal mining areas, the causes of land subsidence are generally complex and spa- The study area Jharia Coalfield lies between lati- tially varied. This gives rise to spatially scattered, tudes 23◦35′–23◦55′ and longitudes 86◦05′–86◦30′. patchy and irregular subsidence fringes (Stow and It is located in the Dhanbad district of Jharkhand Wright 1997; Perski 1998; Perski and Jura 2003). state, India at a distance of about 250 km Moreover, the rates of subsidence may vary from NW of Kolkata City and covering an area of a few centimetres to more than a metre per year 450 km2 approximately (figure 1). This is one in different parts of the coalfield and many a time among the 54 Permo-Carboniferous Gondwana are temporally inconsistent. In the case of C-band coalfields in India. Gondwana coalfields are known DInSAR using the data from ERS, ENVISAT and for high quality and large reserve of coal in RADARSAT satellites with standard revisit time India. of 35 days and 24 days respectively, the tem- In the study area, land subsidence occurs pri- poral decorrelation of the data pairs appears to marily due to underground mining and subsurface be a serious concern for DInSAR feasibility. In coal fire. The source causes namely different types C-band DInSAR, the data pairs need to be much of underground mining (e.g., bord-and-pillar, long- more restricted in terms of spatial and temporal wall mining, depillaring and caving), water log- baselines than L-band DInSAR (Liu et al. 2009). ging of the abandoned underground mine workings The fringe centres in C-band DInSAR sometimes (or galleries) and subsurface coal fire, are diverse lose information due to temporal decorrelation in nature and spatio-temporally haphazard. This (Yue et al. 2011). However, C-band DInSAR is gives rise to irregular and complex deformation Detecting, mapping and monitoring of land subsidence in Jharia Coalfield 1361 Jharia Coalfield (a) 4 DHANBAD 5 EBF DS 3 JCF 6 2 JRF Localities & Test Sites JCF: Jharia Town 1 1: Pathardih 4: Katras Test Sites 2: Jamadoba 5: Dumda EBF: East Basuriya DS: Dobari 3: Moonidih 6: Mahuda JRF: Joyrampur (b) Figure 1. Location of the study area: Jharia Coalfield in Jharkhand state of India (a) (after Acharyya 2000). The coalfield is seen on PAN-sharpened IRS LISS-3 standard FCC 432 (R-G-B) image product (b). Test sites for ground-based land subsidence measurements by precision levelling and GPS survey are shown in (b). pattern. Depillaring by caving of the existing Moreover, many unknown and unmapped abandoned galleries is generally responsible for rapid land sub- galleries (underground mine workings) exist in the sidence phenomena. Caving is mostly carried out in coalfield as a bi-product of private mining during virgin areas. On the other hand, depillaring accom- pre-nationalization period. Water logging of the panied by sand stowing is done in the settlement abandoned galleries can lead to land subsidence areas. It does not cause significant land subsidence. and roof collapse. Similarly, sub-surface coal fire 1362 R S Chatterjee et al. can also lead to land subsidence and roof collapse. during 2003–2004 and five scenes were acquired The Jharia Coalfield is known for hosting the highest during 2007. InSAR data pairs were selected pri- number of coal fires among all the coalfields in marily based on spatial and temporal baselines India.