Anupma Prakash

A Landsat TM based comparative study of surface and subsurface fires in the Jharia coalfield, India

Landsat TM data were used to detect surface and subsurface fires in the Jharia coalfield (JCF). TM-6 was useful for mapping subsurface fires and TM-5 and TM-7 were useful for mapping surface fires. The distribution pattern of fires was studied and their temperature and areal extents were estimated. A comparison of the distribution of surface and subsurface coal fires indicated that at some sites fires occur only on the surface or only in the subsurface, while at other sites both surface and subsurface fires occur.

Landsat-TM data for estimating ground temperature and depth of subsurface coal fire in the Jharia coalfield, India

Abstract Coal fires are a ubiquitous problem in coal-mines, the world over. They burn our prime energy resource, lead to atmospheric pollution and render mining of coal hazardous. Processes leading to coal combustion and spread of subsurface fires are briefly examined in this paper and the role of remote sensing in surveillance of coal fires is presented. The present study aims at developing a quick method for estimating the temperature of the ground surface directly above subsurface coal fires. Utility of TM6 and TM7-band data for temperature estimation is briefly reviewed. It is argued that temperature calculations of surface anomalies related to subsurface fires can only be done on the basis of 8–14 μm band data, due to the low temperatures involved. In the Jharia coalfield, it is noted that subsurface fires in various coal-mines are associated with surface thermal anomalies, as has also been confirmed by ground checks. The pattern of TM6 data distribution and ground truth is used to isolate thermal an...

Surface fires in Jharia coalfield, India-their distribution and estimation of area and temperature from TM data

Surface fires occur at a number of places in the Jharia coalfield and are high-temperature phenomena of relatively local extent. The use of Landsat Thematic Mapper (TM) shortwave infrared (SWIR) bands in estimating temperatures of high-temperature objects is briefly reviewed. Study of data of TM7 and TM5 bands indicate the existence of surface fires in the Jharia coalfield at 59 pixels and this was supported by limited field checks. Pixel-integrated temperatures of surface fire areas are estimated to be in the range of 217 C to 410 C. However, as these fires often do not occupy the whole pixel area, the pixelintegrated temperatures are less than the actual fire temperatures. The relation between spectral radiance and temperature is nonlinear. Therefore, radiant temperature in TM5 and TM7 can be used to estimate the subpixel area and temperature of surface fires (provided there is no band saturation). In the Jharia coalfield, the subpixel area of some of the surface fires has been found to range between 0....

Detecting coal fires using remote sensing techniques

This paper gives an overview of the theory and case studies of detecting coal fires by using remote sensing techniques. Coal fires, either man-made or spontaneous combustion, not only cause losses of natural resources, but also cause environmental problems. The surface feature and by-products of coal fires include pyro-metamorphic rocks, fumarolic minerals, burnt pits and trench, subsidence and cracks, and surface thermal anomalies. These features can be detected from visible, near infrared, short-wave infrared, radar and thermal infrared remote sensing images. The ability to detect these features is limited by the spectral, spatial and temporal resolution of the remote sensing data. The advances of new remote sensing systems will enhance the capability to detect coal fire related features.

New mineral occurrences and mineralization processes: Wuda coal-fire gas vents of Inner Mongolia

Abstract Five unique mineral assemblages that include the sulfates millosevichite, alunogen, anhydrite, tschermigite, coquimbite, voltaite, and godovikovite, as well as the halide salammoniac and an unidentified phase, according to X-ray diffraction and EDS data, were found as encrustations on quartzofeldspathic sand and sandstone adjacent to coal-fire gas vents associated with underground coal fires in the Wuda coalfield of Inner Mongolia. The mineral assemblage of alunogen, coquimbite, voltaite, and the unidentified phase collected from the same gas vent, is documented for the first time. Coquimbite also occurs as rosettes secondarily nucleated on a cryptocrystalline mass of alunogen, coquimbite, voltaite, and the unidentified phase during storage in a sealed container at room temperature. Field observations, analyses of vent gases, SEM images, and mineral compositions suggest that the sulfates millosevichite, alunogen, coquimbite, voltaite, godovikovite, and the unidentified phase, crystallized in response to a complex sequence of processes that include condensation, hydrothermal alteration, crystallization from solution, fluctuating vent temperatures, boiling, and dehydration reactions, whereas the halide salammoniac crystallized during the sublimation of coal-fire gas. Tschermigite and anhydrite formed by the reaction of coal-fire gas with quartzofeldspathic rock or by hydrothermal alteration of this rock and crystallization from an acid-rich aqueous solution. Variations in the mineral assemblages found at five gas vents are possibly due to differences in coal-bed chemistry, exchange reactions involving coal-fire gas, and the composition of sediment, rock, and aqueous solutions prior to the exhalation of gas at the surface, as well as the temperature and cooling rate at a vent. Few studies have addressed the interaction of coal-fire gas with sediment, rock, and aqueous solutions and the subsequent mineralization processes. Coal fires present opportunities for discovering rare and new mineral occurrences. These minerals have potentially important environmental significance and may be vectors for the transmission of toxins. Coal fires also provide insight for the recognition in the geologic record of preserved mineral assemblages that are diagnostic of ancient fires.

Gas emissions, minerals, and tars associated with three coal fires, Powder River Basin, USA.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires.

Monitoring coal fires using multi-temporal night-time thermal images in a coalfield in north-west China

China has the largest coal resources in the world but these are seriously endangered by coal fires. Though the problem of coal fires is long standing and not only limited to China, little has been done for regular monitoring of these fires. This Letter proposes the use of multi-temporal night-time thermal images acquired from Landsat Thematic Mapper band 6 for establishing a coal fire monitoring system for a coalfield in north-west China. Other images and map data are fused with the thermal images to provide a comprehensive picture of the fires through the years. Finally the fires are classified into different categories based on multi-temporal changes.

Estimating the depth of buried hot features from thermal IR remote sensing data: a conceptual approach

Abstract Estimating the depth of buried thermal features from remotely sensed data is a difficult problem. The theoretical basis discussed in this letter shows that if the time of initiation of the heat source is known, then utilizing two sets of thermal Infrared ( IR) data of different time instances for the same anomaly area, the depth of the buried heat source can be computed. However, if the thermal IR data are collected at time intervals close to the time of initiation of heat source, the knowledge of initial conditions of heat source is obviated. In this latter case, a double ratioing technique, utilizing three sets of thermal IR remote sensing data, acquired at different times for the same area, can be used for estimating the depth of buried heat source. Respective sample sets of characteristic curves designed for depth estimation are presented along with results of sensitivity analysis tests, performed on simulated data.

Recommendations for Making Geoscience Data Accessible and Usable in Education

Geoscience and planetary science are awash in data. Over the past decade, our field has transformed into one that acquires and uses extensive remote-sensing data. Enabling state-of-the-art models of complex systems, these data focus our understanding of the future impact of our actions by examining the present and past.

Monitoring Large Woody Debris Dynamics in the Unuk River, Alaska Using Digital Aerial Photography

Large Woody Debris (LWD) and changes in its accumulation pattern influence the morphology, flow characteristics, ecological attributes, and physical habitats along a river. Digital aerial photos were acquired for the Unuk River in Alaska during the spring of 2003 and 2004. Digital processing of aerial photos involved high-pass filtering on the second principal component image, followed by a low-pass filtering, thresholding, and color coding to map individual logs and large wood accumulations. This processing technique provided an effective classification of the LWD with an overall classification accuracy of 89%. In the selected test site, the 2004 images show a 23% decrease in LWD, which is attributed to the large-scale wash-over of the wood due to a known flooding event in October 2003. Large shifts in LWD have caused main channel shifts, channel splits, merging of split channels, and changes in locations of sand bars and pools, dislocating and redistributing known fish habitat.