Detection of underground mining induced land subsidence using Differential Interferometric SAR (D-InSAR) in Jharia coalfields

Mining induced land subsidence is very common in the areas of extensive underground coal mining which affects the overall geo-environmental scenario of the area. Jharia coalfields in Jharkhand has been experiencing land subsidence for several decades essentially due to underground mining and coal fire. Differential interferometric SAR (D-InSAR) technique has been used widely to identify and measure land subsidence. In this study, six ALOS PALSAR data pairs acquired during 2007-2008 were used to study land subsidence phenomenon in the Jharia coalfields. Two-pass D-InSAR was used in this study which uses two SAR images of the same area taken at different times to calculate the Line-of-Sight (LOS) path difference of a target point due to land displacement with the help of an external Digital Elevation Model (DEM). Well defined subsidence fringes were obtained in most of the differential interferogram pairs. The fringe areas were integrated to obtain the total subsidence affected areas during the observation period with rates of subsidence (in cm/year). The maximum subsidence rate calculated from D-InSAR processing is found to be 56.72 cm/yr and the minimum is 7.88 cm/yr. The total affected area in the study area is 7.2 sq kms. Field checks were done for confirmation of D-InSAR based subsidence results

Assessing land-use changes driven by river dynamics in chronically flood affected Upper Brahmaputra plains, India, using RS-GIS techniques

This work documents land-use changes driven by river dynamics along two tributaries in the chronically flood affected Upper Brahmaputra floodplain which supports a population of more than half a million. Planform changes for a period of 40 years are documented using topographical map and Landsat data, and the associated land-use change is assessed by utilising hybrid classification in GIS environment. Quantification of bankline migration shows that the river courses are unstable. A reversal in the rate of erosion and deposition is also observed. Hybrid classification of Landsat images yielded a higher level of accuracy as evident from the confusion matrixes. Overall, the accuracy of land-use classification ranged between 88.5% and 96.25%. Land-use change shows that there is an increase in settlement and agriculture and a decrease in the grassland. The area affected by erosion–deposition and river migration comprises primarily of the agricultural land. Effect of river dynamics on settlements is also evident. Loss of agricultural land and homestead led to the loss of livelihood and internal migration in the floodplains. The observed pattern of river dynamics and the consequent land-use change in the recent decades have thrown newer environmental challenges at a pace and magnitude way beyond the coping capabilities of the dwellers