Fraunhoffer Diffraction Analysis of Satellite Cloud Imagery

The Fraunhoffer diffraction analysis of cloud-covered satellite imagery has shown that the diffraction pattern follows approximately cosine squared distribution. The overshooting tops of clouds and the shadows cast by them contribute much to the diffraction of light, particularly in the high-frequency range. Indeed, cloud-covered imagery can be distinguished from cloud-free imagery on the basis of rate of decay of the diffracted light power in the high-frequency band.

Modeling of the sea surface for daylight imagery studies

Plastic-coated paper is shown to possess reflectivity characteristics quite similar to those of the surface of water. This correspondence has been used with a conversion factor to model a sea surface by means of plastic-coated paper. Such a paper model is then suitably illuminated and photographed, yielding physically simulated daylight imagery of the sea surface under controlled conditions. A simple example of sinusoidal surface simulation is described.

Pixel based fusion using IKONOS imagery

Pixel based image fusion entails combining geometric details of a high-resolution Panchromatic (PAN) image and spectral information of a low-resolution Multispectral (MS) image to produce images with highest spatial content while preserving the spectral information. This work reviews and implements six fusion techniques – À Trous algorithm based wavelet transform (ATW), Mulitresolution Analysis based Intensity Modulation, Gram Schmidt fusion, CN Spectral, Luminance Chrominance and High pass fusion (HPF) on IKONOS imagery having 1 m PAN and 4 m MS channels. Comparative performance analysis of techniques by various methods reveals that ATW followed by HPF perform best among all the techniques.

Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

GPU-based normalized cuts for road extraction using satellite imagery

This paper presents a GPU implementation of normalized cuts for road extraction problem using panchromatic satellite imagery. The roads have been extracted in three stages namely pre-processing, image segmentation and post-processing. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, vegetation,. and fallow regions). The road regions are then extracted using the normalized cuts algorithm. Normalized cuts algorithm is a graph-based partitioning `approach whose focus lies in extracting the global impression (perceptual grouping) of an image rather than local features. For the segmented image, post-processing is carried out using morphological operations - erosion and dilation. Finally, the road extracted image is overlaid on the original image. Here, a GPGPU (General Purpose Graphical Processing Unit) approach has been adopted to implement the same algorithm on the GPU for fast processing. A performance comparison of this proposed GPU implementation of normalized cuts algorithm with the earlier algorithm (CPU implementation) is presented. From the results, we conclude that the computational improvement in terms of time as the size of image increases for the proposed GPU implementation of normalized cuts. Also, a qualitative and quantitative assessment of the segmentation results has been projected.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

A Generalized Approach to Multiresolution Complex SAR Signal Processing

Multiresolution synthetic aperture radar (SAR) image formation has been proven to be beneficial in a variety of applications such as improved imaging and target detection as well as speckle reduction. SAR signal processing traditionally carried out in the Fourier domain has inherent limitations in the context of image formation at hierarchical scales. We present a generalized approach to the formation of multiresolution SAR images using biorthogonal shift-invariant discrete wavelet transform (SIDWT) in both range and azimuth directions. Particularly in azimuth, the inherent subband decomposition property of wavelet packet transform is introduced to produce multiscale complex matched filtering without involving any approximations. This generalized approach also includes the formulation of multilook processing within the discrete wavelet transform (DWT) paradigm. The efficiency of the algorithm in parallel form of execution to generate hierarchical scale SAR images is shown. Analytical results and sample imagery of diffuse backscatter are presented to validate the method.

Characterisation of Landscape with Forest Fragmentation Dynamics

Land cover (LC) and land use (LU) dynamics induced by human and natural processes play a major role in global as well as regional patterns of landscapes influencing biodiversity, hydrology, ecology and climate. Changes in LC features resulting in forest fragmentations have posed direct threats to biodiversity, endangering the sustainability of ecological goods and services. Habitat fragmentation is of added concern as the residual spatial patterns mitigate or exacerbate edge effects. LU dynamics are obtained by classifying temporal remotely sensed satellite imagery of different spatial and spectral resolutions. This paper reviews five different image classification algorithms using spatio-temporal data of a temperate watershed in Himachal Pradesh, India. Gaussian Maximum Likelihood classifier was found to be apt for analysing spatial pattern at regional scale based on accuracy assessment through error matrix and ROC (receiver operating characteristic) curves. The LU information thus derived was then used to assess spatial changes from temporal data using principal component analysis and correspondence analysis based image differencing. The forest area dynamics was further studied by analysing the different types of fragmentation through forest fragmentation models. The computed forest fragmentation and landscape metrics show a decline of interior intact forests with a substantial increase in patch forest during 1972-2007.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Crevasses detection in Himalayan glaciers using ground-penetrating radar

Identification and mapping of crevasses in glaciated regions is important for safe movement. However, the remote and rugged glacial terrain in the Himalaya poses greater challenges for field data collection. In the present study crevasse signatures were collected from Siachen and Samudra Tapu glaciers in the Indian Himalaya using ground-penetrating radar (GPR). The surveys were conducted using the antennas of 250 MHz frequency in ground mode and 350 MHz in airborne mode. The identified signatures of open and hidden crevasses in GPR profiles collected in ground mode were validated by ground truthing. The crevasse zones and buried boulder areas in a glacier were identified using a combination of airborne GPR profiles and SAR data, and the same have been validated with the high-resolution optical satellite imagery (Cartosat-1) and Survey of India mapsheet. Using multi-sensor data, a crevasse map for Samudra Tapu glacier was prepared. The present methodology can also be used for mapping the crevasse zones in other glaciers in the Himalaya.

A Rodinian suture in western India: New insights on India-Madagascar correlations

We report detailed evidence for a new paleo-suture zone (the Kumta suture) on the western margin of southern India. The c. 15-km-wide, westward dipping suture zone contains garnet-biotite, fuchsite-haematite, chlorite-quartz, quartz-phengite schists, biotite augen gneiss, marble and amphibolite. The isochemical phase diagram estimations and the high-Si phengite composition of quartz-phengite schist suggest a near-peak condition of c. 18 kbar at c. 550 degrees C, followed by near-isothermal decompression. The detrital SHRIMP U-Pb zircon ages from quartz-phengite schist give four age populations ranging from 3280 to 2993 Ma. Phengite from quartz-phengite schist and biotite from garnet-biotite schist have K-Ar metamorphic ages of ca. 1326 and ca. 1385 Ma respectively. Electron microprobe-CHIME ages of in situ zircons in quartz-phengite schist (ca. 3750 Ma and ca. 1697 Ma) are consistent with the above results. The Bondla ultramafic-gabbro complex in the west of the Kumta suture compositionally represents an arc with K-Ar biotite ages from gabbro in the range 1644-1536 Ma. On the eastern side of the suture are weakly deformed and unmetamorphosed shallow westward-dipping sedimentary rocks of the Sirsi shelf, which has the following upward stratigraphy: pebbly quartzite/sandstone, turbidite, magnetite iron formation, and limestone; farther east the lower lying quartzite has an unconformable contact with ca. 2571 Ma quartzo-feldspathic gneisses of the Dharwar block with a ca. 1733 Ma biotite cooling age. To the west of the suture is a c. 60-km-wide Karwar block mainly consisting of tonalite-trondhjemite-granodiorite (TTG) and amphibolite. The TTGs have U-Pb zircon magmatic ages of ca. 3200 Ma with a rare inherited core age of ca. 3601 Ma. The K-Ar biotite cooling age from the TTGs (1746 Ma and 1796 Ma) and amphibolite (ca. 1697 Ma) represents late-stage uplift. Integration of geological, structural and geochronological data from western India and eastern Madagascar suggest diachronous ocean closure during the amalgamation of Rodinia; in the north at around ca. 1380 Ma, and a progression toward the south until ca. 750 Ma. Satellite imagery based regional structural lineaments suggests that the Betsimisaraka suture continues into western India as the Kumta suture and possibly farther south toward a suture in the Coorg area, representing in total a c. 1000 km long Rodinian suture. (C) 2013 Elsevier B.V. All rights reserved.

SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Estimation of ice thickness using surface velocities and slope: case study at Gangotri Glacier, India

We estimate the distribution of ice thickness for a Himalayan glacier using surface velocities, slope and the ice flow law. Surface velocities over Gangotri Glacier were estimated using sub-pixel correlation of Landsat TM and ETM+ imagery. Velocities range from similar to 14-85 m a(-1) in the accumulation region to similar to 20-30 ma(-1) near the snout. Depth profiles were calculated using the equation of laminar flow. Thickness varies from similar to 540 m in the upper reaches to similar to 50-60 m near the snout. The volume of the glacier is estimated to be 23.2 +/- 4.2 km(3).

Seismotectonics of the April-May 2015 Nepal earthquakes: An assessment based on the aftershock patterns, surface effects and deformational characteristics

Occurrence of the April 25, 2015 (Mw 7.8) earthquake near Gorkha, central Nepal, and another one that followed on May 12 (Mw 7.3), located similar to 140 km to its east, provides an exceptional opportunity to understand some new facets of Himalayan earthquakes. Here we attempt to assess the seismotectonics of these earthquakes based on the deformational field generated by these events, along with the spatial and temporal characteristics of their aftershocks. When integrated with some of the post-earthquake field observations, including the localization of damage and surface deformation, it became obvious that although the mainshock slip was mostly limited to the Main Himalayan Thrust (MHT), the rupture did not propagate to the Main Frontal Thrust (MFT). Field evidence, supported by the available InSAR imagery of the deformation field, suggests that a component of slip could have emerged through a previously identified out-of-sequence thrust/active thrust in the region that parallels the Main Central Thrust (MCT), known in the literature as a co-linear physiographic transitional zone called PT2. Termination of the first rupture, triggering of the second large earthquake, and distribution of aftershocks are also spatially constrained by the eastern extremity of PT2. Mechanism of the 2015 sequence demonstrates that the out-of-sequence thrusts may accommodate part of the slip, an aspect that needs to be considered in the current understanding of the mechanism of earthquakes originating on the MHT. (c) 2015 Elsevier Ltd. All rights reserved.

Remotely sensed debris thickness mapping of Bara Shigri Glacier, Indian Himalaya

Despite the important role of supraglacial debris in ablation, knowledge of debris thickness on Himalayan glaciers is sparse. A recently developed method based on reanalysis data and thermal band satellite imagery has proved to be potentially suitable for debris thickness estimation without the need for detailed field data. In this study, we further develop the method and discuss possibilities and limitations arising from its application to a glacier in the Himalaya with scarce in situ data. Surface temperature patterns are consistent for 13 scenes of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 7 imagery and correlate well with incoming shortwave radiation and air temperature. We use an energy-balance approach to subtract these radiation or air temperature effects, in order to estimate debris thickness patterns as a function of surface temperature. Both incoming shortwave and longwave radiation are estimated with reasonable accuracy when applying parameterizations and reanalysis data. However, the model likely underestimates debris thickness, probably due to incorrect representation of vertical debris temperature profiles, the rate of heat storage and turbulent sensible heat flux. Moreover, the uncertainty of the result was found to increase significantly with thicker debris, a promising result since ablation is enhanced by thin debris of 1-2 cm.