Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India

This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network (ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality of the ANN technique in mapping the liquefaction susceptibility of the area.     

An automated seamless mosaicing system of multi-charge coupled devices of panchromatic data

Panchromatic data of pixel resolution 5.8 m obtained from IRS-1C and IRS-1D satellites proved to be very useful for mapping purposes. One of the popular data product is the 70 km swath mosaic which is covered by a combination of 3 CCD line sensors, each with 4096 pixels. Each CCD-line sensor with different imaging times causes geometric problems of mosaicing three strips data together. In this paper, we propose the details of the design elements of system that caters to the need for accurate and automatic multi strip image registration without any second resampling of the data. The systematic geometric correction grid mapping is improved to facilitate accurate mosaicing by automatic image registration task that makes use of the overlap data within image strips and image registration is achieved up to sub-pixel level.     

An interpretation of wave refraction and its influence on foreshore sediment distribution

To analyze the grain size and depositional environment of the foreshore sediments, a study was undertaken on wave refraction along the wide sandy beaches of central Tamil Nadu coast. The nearshore waves approach the coast at 45° during the northeast(NE) monsoon, at 135° during the southwest(SW) monsoon and at 90° during the non-monsoon or fair-weather period with a predominant wave period of 8 and 10 s. A computer based wave refraction pattern is constructed to evaluate the trajectories of shoreward propagating waves along the coast in different seasons. The convergent wave rays during NE monsoon, leads to high energy wave condition which conveys a continuous erosion at foreshore region while divergent and inept condition of rays during the SW and non-monsoon, leads to moderate and less energy waves that clearly demarcates the rebuilt beach sediments through littoral sediment transport. The role of wave refraction in foreshore deposits was understood by grain size and depositional environment analysis. The presence of fine grains with the mixed population, during the NE monsoon reveals that the high energy wave condition and sediments were derived from beach and river environment. Conversely, the presence of medium grains with uniform population, during SW and non-monsoon attested less turbulence and sediments were derived from prolong propagation of onshore-offshore wave process.These upshots are apparently correlated with the in situ beach condition. On the whole, from this study it is understood that beaches underwent erosion during the NE monsoon and restored its original condition during the SW and non-monsoon seasons that exposed the stability of the beach and nearshore condition.     

Sustainable Development, Climate Change and Tropical Rain Forest Landscape

A potential impact of climate change in the south Asian context in general and the Indian subcontinent in particular is an increase in rainfall, in some areas up to 50%. Using an extensive information base available on the dynamics of landscape structure and function of the northeastern hill areas of India, scenarios on landscape changes, as an adaptation to climate change, have been constructed. Climate change would impose a variety of stresses on sustainable livelihood of the inhabitants of the rain-forested areas through stresses on ecosystem function. It is concluded that appropriate management strategies for natural forests and plantation forestry should go hand in hand with a comprehensive rural ecosystem rehabilitation plan.     

Response of circular bridge decks to moving vehicles

This paper discusses the dynamic response of a curved bridge deck to a moving vehicle. The bridge deck is idealized as a set of annular sector plates and circular rings rigidly jointed together. On the basis of classical plate and ring theories a method has been developed to obtain the response to a moving vehicle idealized as a spring mass system. After obtaining the normal modes and frequencies and establishing the orthogonality conditions, the problem of the forced motion of the deck is solved by the method of spectral representation. Numerical results have been presented to illustrate the effect of several vehicle and bridge parameters on the response.     

Resourcesat (IRS-P6) value added data products

Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.     

Efficient encoding and decoding algorithms for distributed resampling

This paper discusses algorithms for compressing floating point data which is encountered while performing resampling algorithm for rectifying geometric distortions on the images transmitted by the remote sensing satellite on a distributed computing environment. Two efficient algorithms for encoding and decoding floating point data compression, (i) 3-byte packing and (ii) 3-byte + 2-bit packing have been proposed. Both algorithms are tested to execute resampling algorithm on radiometrically corrected for IRS- LISS-III 4 bands data on a distributed system. First algorithm compresses 4-byte floating point data to 3-byte obtaining 25% compression while later one compresses 4-byte floating point data to 3-byte + 2-bit achieving about 18.75% compression. The computational time is reduced by 22% as compared to the distributed resampling algorithms without compression. Further it is found that in lossy compression algorithm only 220 pixels out of 37.4 MB pixels have utmost one Gray count difference, which will not pose any issues for digital classification or any other methods that will be employed in the corrected image by Image Analysts.     

Volume 52

Volume Contents

Volume 52     

Resampling routine on heterogeneous networked-based environment

In this paper, we have described a model to parallelize the resampling routine, which is used in the geometric correction of data provided by remote sensing satellites. Our model is a typical master-slave model consisting of N machines termed as hosts out of which one is designated as the master. The input image data resides on the master. Processing of the input image data is done in parallel on the N machines. Issues related to load-balancing and various error conditions that may occur during execution like one of the machines going down have been studied and are incorporated in the model. It also provides the flexibility to add or delete the hosts during the execution of the resampling routine. The serial version of this routine involves huge amount of computations and takes substantial amount of time even for an image of 473 MB. We have implemented our model with the help of PVM which is most often used in distributed computing environment. Our approach has been tested for geometric correction on LISS-III 4 band data of size 473 MB. It is found that if one uses 2, 3 or 4 hosts the overall execution time is reduced by 33%, 42% and 49%, respectively.