Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellites

Stresses building up during an earthquake preparation phase also manifest themselves in the form of a so called increased land surface temperature (LST) leading to a thermal precursor prior to the earthquake event. This phenomenon has now been validated by our observations of short-term thermal anomalies detected by infrared satellite sensors for several recent past earthquakes around the world. The rise in infrared radiance temperature was seen to vary between 5 and 12 °C for different earthquakes. We discuss in this paper different explanations for the generation of such anomalies that have been offered. Emission of gases due to the opening and closure of micropores upon induced stresses and also the participation of ground water have been propounded as a possible cause for generation of thermal anomalies. Seismo-ionosphere coupling, by which gases like radon move to the earth–atmosphere interface and cause air ionization thus bringing about a change in air temperature, relative humidity, etc., has been put forth by some workers. A mechanism of low frequency electromagnetic emission was tested and experimented by scientists with rock masses in stressed conditions as those that exist at tectonic locations. The workers proposed the positive hole pair theory, which received support from several scientific groups. Positive holes (sites of electron deficiency) are activated in stressed rocks from pre-existing yet dormant positive hole pairs (PHPs) and their recombination at rock–air interface leads to a LST rise. A combination of remote sensing detection of rock mechanics behavior with a perception of chemistry and geophysics has been applied to propose the remote sensing rock mechanics theory. Remote sensing detections of such anomalies confirm so far proposed lab theories for such a hotly debated field as earthquake precursor study by providing unbiased observations with consistency in time and space distribution.     

Generation and validation of DEM using SAR interferometry and differential GPS supported by multispectral optical data

Digital elevation model (DEM) and the derived terrain parameters e.g. contour, slope, aspect, drainage pattern, etc are required for natural resources management, infrastructure planning and disaster management. The present paper aims at generating DEM from ERS tandem pair using interferometric technique supported by differential GPS measurements (DGPS) and multispectral optical data. Validation of DEM has been carried out by DGPS measurements. Ground Control Points (GCP) established by DGPS measurements have been used to georeference the IRS-1D optical data that has finally been co-registered with SAR amplitude image. Optical data, co-registered with ERS - I SAR data has helped in locating the GCP’s and check points, precisely, for refinement of DEM and its validation.     

Using spectral information from the NIR water absorption features for the retrieval of canopy water content

Canopy water content (CWC) is important for mapping and monitoring the condition of the terrestrial ecosystem. Spectral information related to the water absorption features at 970 nm and 1200 nm offers possibilities for deriving information on CWC. In this study, we compare the use of derivative spectra, spectral indices and continuum removal techniques for these regions. Hyperspectral reflectance data representing a range of canopies were simulated using the combined PROSPECT + SAILH model. Best results in estimating CWC were obtained by using spectral derivatives at the slopes of the 970 nm and 1200 nm water absorption features. Real data from two different test sites were analysed. Spectral information at both test sites was obtained with an ASD FieldSpec spectrometer, whereas at the second site HyMap airborne imaging spectrometer data were also acquired. Best results were obtained for the derivative spectra. In order to avoid the potential influence of atmospheric water vapour absorption bands the derivative of the reflectance on the right slope of the canopy water absorption feature at 970 nm can best be used for estimating CWC.     

Evaluation of the geometric stability and the accuracy potential of digital cameras — Comparing mechanical stabilisation versus parameterisation

Recent tests on the geometric stability of several digital cameras that were not designed for photogrammetric applications have shown that the accomplished accuracies in object space are either limited or that the accuracy potential is not exploited to the fullest extent. A total of 72 calibrations were calculated with four different software products for eleven digital camera models with different hardware setups, some with mechanical fixation of one or more parts. The calibration procedure was chosen in accord to a German guideline for evaluation of optical 3D measuring systems [VDI/VDE, VDI/VDE 2634 Part 1, 2002. Optical 3D Measuring Systems–Imaging Systems with Point-by-point Probing. Beuth Verlag, Berlin]. All images were taken with ringflashes which was considered a standard method for close-range photogrammetry. In cases where the flash was mounted to the lens, the force exerted on the lens tube and the camera mount greatly reduced the accomplished accuracy. Mounting the ringflash to the camera instead resulted in a large improvement of accuracy in object space. For standard calibration best accuracies in object space were accomplished with a Canon EOS 5D and a 35 mm Canon lens where the focusing tube was fixed with epoxy (47  μm maximum absolute length measurement error in object space). The fixation of the Canon lens was fairly easy and inexpensive resulting in a sevenfold increase in accuracy compared with the same lens type without modification. A similar accuracy was accomplished with a Nikon D3 when mounting the ringflash to the camera instead of the lens (52  μm maximum absolute length measurement error in object space). Parameterisation of geometric instabilities by introduction of an image variant interior orientation in the calibration process improved results for most cameras. In this case, a modified Alpa 12 WA yielded the best results (29  μm maximum absolute length measurement error in object space). Extending the parameter model with FiBun software to model not only an image variant interior orientation, but also deformations in the sensor domain of the cameras, showed significant improvements only for a small group of cameras. The Nikon D3 camera yielded the best overall accuracy (25  μm maximum absolute length measurement error in object space) with this calibration procedure indicating at the same time the presence of image invariant error in the sensor domain. Overall, calibration results showed that digital cameras can be applied for an accurate photogrammetric survey and that only a little effort was sufficient to greatly improve the accuracy potential of digital cameras.     

An image engineering system for the inspection of transparent construction materials

This article presents a modular photogrammetric recording and image analysis system for inspecting the material characteristics of transparent foils, in particular Ethylen–TetraFluorEthylen-Copolymer (ETFE) foils. The foils are put under increasing air pressure and are observed by a stereo camera system. Determining the time-variable 3D shape of transparent material imposes a number of challenges: especially the automatic point transfer between stereo images and, in temporal domain, from one image pair to the next. We developed an automatic approach that accommodates for these particular circumstances and allows reconstruction of the 3D shape for each epoch as well as determining 3D translation vectors between epochs by feature tracking. Examples including numerical results and accuracy measures prove the applicability of the system.     

Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard

In this work we have developed a theoretical model that helps the interpretation of the remotely sensed thermal infrared measurements carried out over citrus orchards. A detailed analysis of the different factors which take part in the definition of the effective emissivity and temperature (observation height, viewing angle, type of soil, dimensions and separation between orange trees) is made. The model was validated under vertical observation in a citrus orchard during seven nights. In this situation we have determined that the model performs to an accuracy of about 1%.     

Integrated approach for demarcating the fracture zone for well site location : A case study near Gumla and Lohardaga,Bihar

In recent years satellite remote sensing techniques have greatly aided identification of fractures/joints/faults in connection with groundwater exploration. However, due to some constraints in filtering out the type of fracture i.e. shear fracture, tensional fracture, mineralised fracture etc. as to their “open or closed” nature from groundwater aspects, there is need of adding geophysical survey, particularly resistivity survey to further enhance the accuracy, and hence minimise drilling failures. The area under study is a part of Ranchi plateau and lithologically comprising of granite-gneiss. The present paper lays stress on an integrated approach for localising well sites through satellite data analysis and resistivity profiling along with vertical electrical sounding which is based on fracture patterns. With this combined effort i.e. firstly considering the surfacial features like drainage, geomorpho-logy, lithology and lineaments, and secondly taking into account geophysical survey aspects, i.e. depth and thickness of fracture zone, lateral extent, different layer parameter, etc., fairly accurate results are achieved. In the presnt study this type of an integrated survey has been carried out in Lohardaga and Gumla districts in Bihar, the results of which are highlighted in the paper.     

A comparison of three image-object methods for the multiscale analysis of landscape structure

Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement.     

Land damage assessment - a case study

The paper discusses the land damage assessment and change detection analysis with reference to a mineral bearing zone in Manjhi, Manuni and Churan valleys. The area is located in environmentally sensitive and fragile region of Himalaya and constitutes of nearly 400 small-scale mines of slate, which were operative since last one hundred years and are stopped by court of law since 1995 on account of environment deterioration. The status of land degradation has been studied using IRS-1B satellite data of 1988,1992 and 1995. The geo-coded data on 1:50,000 scale has been interpreted and an increase in land degradation status was noticed. Finally, the management strategy for arresting the further land damage in a broader perspective is suggested.     

Hyperspectral remote sensing of evaporate minerals and associated sediments in Lake Magadi area, Kenya

Pleistocene to present evaporitic lacustrine sediments in Lake Magadi, East African Rift Valley, Kenya were studied and mapped using spectral remote sensing methods. This approach incorporated surface mineral mapping using space-borne hyperspectral Hyperion imagery together with laboratory analysis, including visible, near-infrared diffuse reflectance spectroscopy (VNIR) measurements and X-ray diffraction for selected rock and soil samples of the study area. The spectral signatures of Magadiite and Kenyaite, which have not been previously reported, were established and the spectral signatures of trona, chert series, volcanic tuff and the High Magadi bed were also analyzed.Image processing techniques, MNF (Minimum Noise Fraction) and MTMF (Mixture Tuned Matched Filtering) using a stratified approach (image analysis with and without the lake area), were used to enhance the mapping of evaporates. High Magadi beds, chert series and volcanic tuff were identified from the Hyperion image with an overall mapping accuracy of 84.3%. Even though, the spatial distribution of evaporites and sediments in Lake Magadi area change in response to climate variations, the mineralogy of this area has not been mapped recently. The results of this study shows the usefulness of the hypersspectral remote sensing to map the surface geology of this kind of environment and to locate promising sites for industrial open-pit trona mining in a qualitative and quantitative manner.