Debashish Chakravarty

Spatial prediction of soil properties in a watershed scale through maximum likelihood approach

Surface map of soil properties plays an important role in various applications in a watershed. Ordinary kriging (OK) and regression kriging (RK) are conventionally used to prepare these surface maps but generally need large number of regularly girded soil samples. In this context, REML-EBLUP (REsidual Maximum Likelihood estimation of semivariogram parameters followed by Empirical Best Linear Unbiased Prediction) shown capable but not fully tested in a watershed scale. In this study, REML-EBLUP approach was applied to prepare surface maps of several soil properties in a hilly watershed of Eastern India and the performance was compared with conventionally used spatial interpolation methods: OK and RK. Evaluation of these three spatial interpolation methods through root-mean-squared residuals (RMSR) and mean squared deviation ratio (MSDR) showed better performance of REML-EBLUP over the other methods. Reduction in sample size through random selection of sampling points from full dataset also resulted in better performance of REML-EBLUP over OK and RK approach. The detailed investigation on effect of sample number on performance of spatial interpolation methods concluded that a minimum sampling density of 4/km2 may successfully be adopted for spatial prediction of soil properties in a watershed scale using the REML-EBLUP approach.

Two-stage stochastic programming problems involving multi-choice parameters

Abstract In this paper, we propose a two-stage stochastic linear programming model considering some of the right hand side parameters of the first stage constraints as multi-choice parameters and rest of the right hand side parameters of the constraints as exponential random variables with known means. Both the randomness and multi-choiceness are simultaneously considered for the model parameters. Randomness is characterized by some random variables with its distribution and multi-choiceness is handled by using interpolating polynomials. To solve the proposed problem, first we remove the fuzziness and then for multi-choice parameters interpolating polynomials are established. After establishing the deterministic equivalent of the model, standard mathematical programming technique is applied to solve the problem. A numerical example is presented to demonstrate the usefulness of the proposed methodology.

Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables

Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.

Stochastic programming problems involving Pareto distribution

Abstract Stochastic programming is a branch of mathematical programming that considers optimization in the presence of uncertainty. In this paper, both single-objective and multi-objective stochastic programming problems are considered, where the right hand side parameters follow Pareto distribution with known mean and variance. Both the stochastic programming methods namely, chance constrained programming and two-stage stochastic programming are used. In order to solve these stochastic programming problems; we convert these problems into some equivalent deterministic models. Then we use standard mathematical programming techniques for solving single-objective deterministic model. We use fuzzy programming technique to solve the multi-objective deterministic model. The solution procedures are illustrated with an example.

Performance analysis of different surface reconstruction algorithms for 3D reconstruction of outdoor objects from their digital images

Abstract3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality.

Support and Information Effect Modeling for Recoverable Reserve Estimation of a Beach Sand Deposit in India

Application of geostatistics in estimating recoverable reserves of beach sand deposit is rare. This paper made an attempt to estimate local recoverable reserves using disjunctive kriging and discrete Gaussian model considering support and information effects for a beach sand deposit located in the eastern part of India. The dependence of different selective mining unit (SMU) sizes and different production sampling strategies on the estimated tonnage, metal quantity, and the ore tonnage versus metal quantity relationships has been examined. The results of the study show that nonlinear geostatistics should be used for more precise assessment of the grade, ore tonnage, and metal quantity and their relationships, which are necessary for recoverable reserve estimation. In selective mining operation, both support and information effects have significant influence on recoverable reserve. Recoverable reserve estimation based on SMU involves estimating grade distributions of mining unit with much bigger support than the available drill core sample data. Information effect comes into picture from the real scenario where the actual grades of the blocks remain unknown even during mining. At the mining stage, discrimination of ore and waste blocks is carried out based on estimated grades of the production samples and it is likely that the blocks might be misclassified as either ore or waste and thus sent to wrong destination. Information effect modeling makes the estimation more reliable by taking care of misclassification.

Detecting risk buffer zone in open-cast mining areas: a case study of Sonepur–Bajari, West Bengal, India

Mapping of land use/land cover (LU/LC) is an important activity of land management and monitoring, but mining activity has an effect on land, environment and local society. The analysis of land changes map is prepared using high resolution imagery and provide mining information. The rate of deforestation and forest fragmentation has also decreased due to mining activity. This has resulted in over exploitation of natural resources due to mining activities like deforestation, cultivation of marginal lands, mining and industrialization in meeting the increasing demand for food, fuel and fiber. Geo-spatial technology has led to the hosts of undesirable effects on the ecosystem. The risk buffer zone is manipulated based on environmental concern and field verification. Mining operations involve in mineral extraction from the earth’s crust, tends to make a notable impact on the environment, landscape and also biological communities of the earth in the mining area. LU/LC change detection and its impact over space and time (2007–2011). Risk buffer zone demarcation in colliery area and finally environmental impact assessment in the mining area.

GIS based Land Information System using Cadastral model: A case study of Tirat and Chalbalpur rural region of Raniganj in Barddhaman district

Cadastral is the method of registering land, designed to ensure the rights of individuals and the state of their property. Every activity in general, and developmental project activity in particular, is in some form or the other associated with land. Therefore, for planning purpose all land-associated information should be available in the form of a computer database, which can be easily accessed, manipulated by decision makers while formulating and executing a work. Such a database system is called Land information system. Cadastral applications will include cadastral index maps and land registration data in a digital format. Automation linkages will be created and developed between textual data (legal land registration data) and parcel maps. The final goal is to generate digital maps which will facilitate land management and planning and in particular land registration and the issuance of land titles in order to promote security of land tenure and reduce land disputes. Therefore land administration systems are not ‘just handling only geographic information’ as they represent a lawfully meaningful relationship amongst people, between people and land. As the land administration activity on the one hand deals with huge amounts of data, which moreover are of a very dynamic in nature, and on the other hand requires a continuous maintenance process, the role of information technology is of strategic importance. So the present study develops a case study of land information system using cadastral techniques of Tirat and Chalbalpur rural region of Raniganj in Barddhaman district which contains cadastral information.

Characterisation of overburden dump materials: a case study from the Wardha valley coal field

Abstract Recently, large-scale opencast mining activities in India have led not only to the increased generation of large volumes of overburden (OB) dump materials, but also to the transportation of huge volumes of loose geo-materials from coal faces to areas specifically designated for storing these materials in the form of external or internal dumps. The preparation of large-sized dumps is becoming a challenging task for the mining administration from two important perspectives, namely the limited availability of surface leasehold land for dumping geo-materials, and the associated problems of managing the increasing heights of these geo-structures. Normally, the assessment of stability, and taking proper steps to stabilise these external OB dumps, is a trivial task, but because of the increased risks involved with geo-hazards, the design and monitoring of such dumps is currently becoming critical for the production/operation of any mining organisation. Thus, a knowledge and awareness of the detailed nature and mechanical properties of the selected geo-materials present at these sites is becoming more important for stability assessment of OB dumps. In this study, the collected geo-materials (which are agglomerates of broken rocks and loose soil) were tested to evaluate their geotechnical parameters such as grain size distribution, soil permeability, compaction parameters, shear and normal strength characteristics, etc. These tests show that testing of geo-materials from one site is not sufficient for complete and proper site characterisation that would allow these values to be used subsequently in numerical modelling to quantify the stability of OB dumps. Therefor, it was decided that a geotechnical database for groups of geo-materials needs to be generated for the complete evaluation of OB dump stability for all mine sites in the areas of interest.

Integration of DInSAR Technique and Conventional Methods through GIS for Verification of Quantified Surface Changes

Any underground excavation or depletion of either solid minerals or liquids may lead to deformation of the surface profile for areas present above these underground zones. The awareness of deformation rate or rate of change of the natural surface is very important for proper planning and utilization of the geo-resources. These often suffer from the limitations of proper methods of data capture in such areas, accessible or in-accessible to the human beings; in terms of the data density, the time involved in the data capturing process and the associated risks in doing so. Once a proper data is captured, it may easily be used to generate the models of the geo-structures present in and around the region of interest. Till date, the conventional methods of surveying, like precise leveling or GPS, were used for the data capture, which are point observations and suffer from disadvantages like limited spatial resolution, large data capture time, easy manipulability of the collected data, high risk for the operators involved, high cost for large areas etc. With the advent of newer and advanced techniques of data capture in geo-information; use of high precision satellite imagery, especially the synthetic aperture radar (SAR) data having the complex information (i.e. the phase as well as amplitude), has been found to provide adequate data for such purposes. Interferometric synthetic aperture radar (InSAR) is a technique used to reconstruct the digital elevation models (DEM) of the observed scenes. Determination of the surface deformation profiles, integrating the surface displacements using the GIS tool (GRASS) and verification of the surface displacement rates become the main objectives of the present paper. It has been observed that the values of the displacement rates computed using the new method match closely with those obtained using the conventional methods of surface data capture techniques. It has also been found that the new method has several advantages over the conventional methods, as discussed later in this paper.