CREATION OF QUERY BASED DECISION SUPPORT SYSTEM FOR SELECTION OF PIPELINE CORRIDOR SITE USING RS & GIS: A MODEL STUDY

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 4, April 2017, pp Article ID: IJCIET_08_04_187 Available online at aeme.com/ijciet/issues.asp?jtype=ijciet&vtyp pe=8&itype=4 ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed CREATION OF QUERY BASED DECISION SUPPORT SYSTEM FOR SELECTION OF PIPELINE CORRIDOR SITE USING RS & GIS: A MODEL STUDY Y Ranjith Kumar and M Akhil gopinadh UG - Student, Department of Civil Engineering, KL University, Andhra Pradesh, India B Mohanty Assistant Professor, Department of Civil Engineering, KL University, Andhra Pradesh, India SS Asadi Professor & Associate Dean Academics, Department of Civil Engineering, K L University, Guntur, Andhra Pradesh, India ABSTRACT Application of Remotee sensing (RS) data and Geographic information system (GIS) techniques has been given much emphasis for the pipeline alignment study. The present study is covering an aerial extension of 18 km from Patancheru to Balnagar of Hyderabad district, Telengana. The study area covers a variety of geomorphological features. Interpretation of satellite data I.e. IRS-LISS III of 1:50,000 scales are used in the present study to understand the geomorphological nature of the study area. For suggesting the pipeline alignment in the study area the thematic information used are, the occurrence and distribution of various landforms, mining/industrial belts, densely/sparsely habituated areas (villages, towns etc.. ), forest cover, changing river courses, flood prone areas, erosion prone areas, marshy/water logged areas, stream/canal/railway line/road network etc. LISS III data of spectral resolution of 23.5m and repetitive coverage within 24 days provided an integrated information which is required for pipeline alignment. Finally a pipeline corridor map of 1:50,000 scaleis prepared using the developed query based decision support system for locating a short, safe and cost effective pipeline route. It s a regional appreciation showing a tentative alignment by shortest route with detailed information i.e. actual number of turning point, road/railway line /stream/canal etc. Key words: Information. Geomorphological Features, Pipeline, Landforms, Thematic Cite this Article: Y Ranjith Kumar, M Akhil gopinadh, B Mohanty and SS Asadi Creation of Query Based Decision Support System for Selection of Pipeline Corridor editor@iaeme.com

2 Fabrice Mwizerwa and Anshul Garg Site Using Rs & Gis: A Model Study, International Journal of Civil Engineering and Technology, 8(4), 2017, pp INTRODUCTION: Information on LU/LC is the basic prerequisite for land resources evaluation, environmental assessment, utilization and management. A considerable degree of land transformation is being witnessed as a result of growing population pressure on the finite land resources consummating in deterioration of the environment. As a precursor, it is necessary to understand the cause and effect of the transformations through scientific studies. The present study envisages the use of Remote Sensing and GIS in mapping LU/LC of 18 km Buffer area along the Pipeline route through the Patancheru to Balanagar of state Telengana. Details of urban land, forest cover, agricultural land, wastelands, water bodies, major road etc., were delineated and analysed in this study. The first and foremost objective is to reduce the length of the alignment as laying of the pipe including alignment survey per kilometer. To achieve this a cost effective less time consuming eco-friendly techniques called Remote Sensing and GIS has been used which provides a synoptic view and also updated information about the terrain due to its repetitive Knowing The lay of the land has always been crucial for pipeline routing technology. High accuracy determination using geo-referenced satellite data, cartographic data requires accurate DEM (Digital Elevation Model) and the related database of the area under study is a challenge across the worldwide. Several research organizations like IIT Mumbai, JNTU Hyderabad, GAIL, NRSA and InfoTech have approached to evolve a cost effective, a proper route identifier by user friendly Decision Support System which can replace the conventional methods selection of a possible route for laying a pipeline. Researchers (i.e. Burrough, P.A.,1986; Dalvi et al., 2003; Mahmoud, M.S.A. and Abdalla, S.M.A., 2013) have been proposed models using geo spatial information system in pipeline alignment studies. They highlighted the GIS role in oil and Gas/Petroleum transport and also issues related to the data acquisition and map production requirements to enable the transport system through pipeline routing more efficiently. Hijazi J. and Geomatics P.C.I., (2001) proved the importance of topographical study using DEM an essential requirement before any route planning. He has proposed the high-resolution satellite imagery data study for the evaluation of DEM using Image Processing software to evaluate an accurate data in the required area of interest. In order to generate an integrated solution using the Remote Sensing and GIS a decision support system (DSS) has been proposed by Adelman, L., Therefore, DSS (Decision Support System) a model has been developed to enable an easy solution for selection of a pipeline route using the Remote Sensing and GIS STUDY AREA The area chosen for the present study is extending from Patancheru to Balanagar of State Telengana covering the survey of India Topo-sheets no. 54k/6, 54k/7, 54k/11. The area lies between latitudes N to longitudes E. The pipeline corridor lies close to national highway. The topography of an area also influences the drainage system and the ground water movement. The Nakkavagu basin forms a peneplain surface of the ancient Deccan Peninsula that had undergone several cycles of erosion, deposition and upliftment. Sporadic granite crags and sheets of bedrock are seen in this region. The Lands are rolling plains interspersed with story wastes and open scrubs Isukavagu, Pamulavagu and Nakkavagu mainly drain the basin, the slope is from east to west up to Nakkavagu and it is south to north and north-west up to Manjira river. The land has a slope of 0.5 %. The relief of the basin is about 1450 meters. The lowest contour is 500 meters above mean sea level which lies near editor@iaeme.com

3 Experimental Study on Effects on Properties of Concrete With Different Colours of Glass Powder as A Partial Replacement of Cement Gaudeherla at the confluence point with Manjirariver. The highest contour passing through the Nakkavagu basin is 640 meters above mean sea level. The highest point 648 meters above mean sea level lays in the North of Gumadidala village, located to the eastern part of Patancheru. Figure 1 Location map of study area. 2. OBJECTIVE: The primary objective of this work is to develop a QUERY BASED DECISION SUPPORT SYSTEM for locating a short, safe and cost effective pipeline route using remote sensing and GIS. This model will be an improvement on current two-dimensional (2D) visualization techniques in terms of huge operational and procurement cost. 3. METHODOLOGY: The data used for the present study are: Satellite Data s for the year 1989 (IRS 1D, LISS III and PAN), Survey of India Toposheets (54k/6, k/7, k/11), and Field Data Data used: In developing a RS and GIS based methodology for pipe line alignment, has been carried out by visual interpretation of satellite imagery. Therefore the satellite data such as IRS1D, PAN, LISS III have been collected from National Remote Sensing Agency (NRSA), Balanagar, Hyderabad. In order to georeference the satellite imagery, a number of ground samples have been collected from the ground by using survey of India Toposheets. After georeferencing Digital classification of image is carried out for generation LULC layer and contour map for delineation of pipeline alignment editor@iaeme.com

4 Fabrice Mwizerwa and Anshul Garg 3.2. Step By Step Processing of Methodology: The broad methodology adapted for this pipeline alignment study is Weights Assessment Techniques a popular GIS analysis models present in commercial GIS packages. In this model first, number of criterion (or inputs) which are considered to affect our goal (i.e. pipeline alignment) are identified and are weighted. The purpose of criterion weighing is to express the importance of each criterion relative to other criterion. A number of criterion weighing procedures based on the judgments of decision makers have been proposed and published in the multi-criterion decision literature. Some of the popular procedures are ranking, rating, and pair-comparison and trade-off analysis. Acquisition of Satellite (IRS) Data Preliminary Interpretation of the Image Base Map from Topo sheets Ground Truth Data Collection Collateral Data Final Interpretation of the Pipeline Route on all terrain details Preparation of final route alignment map and report Development of hierarchy Visual interpretation for different thematic layer Development of pair wise comaprision Digitization of different thematic layer Computation of criterion weights Assign weight age to the coverage s Estimation of consistency based Ratio Raster GRID generation Route alignment Map CR>0. CR<0.0 Figure 2 Flow diagram of the Analytical Hierarchy Process editor@iaeme.com

5 Experimental Study on Effects on Properties of Concrete With Different Colours of Glass Powder as A Partial Replacement of Cement 3.3. Analytical Hierarchy Process (AHP): The Analytical Hierarchy Process (AHP) model, developed by saaty (1980), is based on three principals; decomposition, comparative judgment, and synthesis of priorities. The decomposition principle requires that the decision problem be decomposed into a hierarchy that capture the essential elements of the problem. The principal of comparative judgment requires assessment of pair wise comparisons of the elements within a given level of the hierarchical structure with respect to their parent in the next higher level. The AHP procedure involves three major steps: Develop the AHP Hierarchy: The first step in the AHP procedure is to decompose the decision problem into a hierarchy that consist of the most important elements of the decision problem. In developing a hierarchy, the top level is the ultimate goal of the decision at hand (e.g. Select the best site for a nuclear power station). This is the level against which the decision alternatives of the lower level of the hierarchy are evaluated each level must be linked to the next- higher level Compare the decision elements on a pair wise base: Pair wise comparisons are the basic measurement mode employed in the AHP procedure. It involves three steps (a) development of a comparison matrix at each level of the hierarchy, beginning at the top and working down; (b) computation of weights for each element of the hierarchy; and (c) estimation of the consistency ratio. Each time, pair wise comparisons would be generated to estimate the relative importance of each element at a particular level with respect to the higher level components Construction an overall rating: The final step is to aggregate the relative weights of the levels obtained in the second step to procedure composite weights. This is done by means of a sequence of multiplication of the matrices of relative weights at each level of the hierarchy. The sequence is one in which the relative weights matrix for the second level is multiplied by the relative weights matrix for the third level, and then this is resulting matrix is multiplied by the relative weights matrix for the next-lower level. This process is continued until all levels from the second level to the bottom level have been multiplied together, forming a vector of composite weights. The composite weights represent ratings of alternatives with respect to the overall goal. 1. In the spatial AHP procedure the attributes priority ratings serve as the weights of relative importance of the attributes (Map layers).the weights can be incorporated into simple additive weighting model. 2. As per the weights all the maps are converted into grids (raster) in which the values are equivalent to the weights. 3. A model has been created in the ARC/INFO software in which all the parameter grids are added linearly to procedure an output grid Development of pair-wise comparison matrix: A scale with values from 1 to 9 to rate the relative preference for two criteria is used editor@iaeme.com

6 Fabrice Mwizerwa and Anshul Garg Table 1 Relative preference for two criteria SCALE Intensity of importance Definition 1 Equal importance 2 Equal to moderate importance. 3 Moderate importance. 4 Moderate to Strong importance 5 Strong Importance 6 Strong to very strong importance 7 Very strong importance 8 Very strong to extremely strong Importance 9 Extreme Importance Let us consider three criterions, say A, B, C are important for our goal or objective (i.e. pipeline alignment). Our objective is depending on the behaviour of this criterion. Suppose A is moderately to strong prefer over B. i.e. the comparison results in a value 4. Further A is strongly preferred over C, and then this comparison results in a value 7. Finally consider only pair-wise comparison, which is B compared to C and imagine that former is strongly preferred to the later, then it results in a value 5. From this information we can determine the remaining entries. First we make the assumption that comparison matrix is reciprocal i.e. if A is twice preferred to B, then we can conclude that B is preferred only one-half as much as A. Like this we can construct the pair-wise comparison matrix. Example: Goal A B C A B 1/4 1 5 C 1/7 1/ Computation of the criterion weights: This step involves following operations a. Sum the values in each column of the pair-wise comparison matrix. b. Divide each element in the matrix by its column total (results in normalized matrix). c. Compare the average of the elements in each row of the normalized matrix. This average provides an estimate of the relative weights of the criteria being compared Estimation of consistency ratio: a. Determine the weighted sum vector by multiplying the weight for first criterion times the first column of original pair-wise comparison matrix, then seeing weight with second column and so on depending upon the criterion. b. Sum these values over the rows. Determine the consistency vector by dividing the weighted sum vector by criterion weights determined previously. After calculating consistency vector we have to compute values for two more terms, lambda (λ) and consistency index (CI). The calculation of CI is based on the observation that λ is always greater than or equal to number of criterion under editor@iaeme.com

7 Experimental Study on Effects on Properties of Concrete With Different Colours of Glass Powder as A Partial Replacement of Cement consideration (n) for +ve, reciprocal matrices and λ = n if pair-wise comparison matrix is a consistent matrix. Accordingly λ n can be considered as a measure of the degree of inconsistency. This measure can be normalized as follows The CI term, referred to as the consistency index, provides a measure of departure from consistency. The CR (consistency ratio) is defined as CI λ-n CI = n-1 CR = (where Random index RI = 0.58 for n = 15 criteria RI (Adapted from Saaty) If CR< 0.10, the ratio indicates a reasonable level of consistency in the pair-wise comparison. Otherwise if CI > 0.10 the ratio indicates inconsistent judgment. In this case one should reconsider and revise the original values in the pair wise comparison matrix. Once we get the weights, these weights are attached to the criterion and are converted in to GRIDS based on this weightages. Then all these grids are integrated according to this weightages in Grid environment of ARC/INFO to get favourable zone for pipeline alignment. Pipeline alignment = a1 (criteria1) + a2 (criteria 2) + an(criteria n) 4. RESULTS AND DISCUSSIONS: The total geographic area of the present study (fig.1) is distributed in Nine scenes of IRS LISS III data and these dataset s has been acquired from NRSA (National Remote Sensing Agency) Hyderabad. Image processing software namely ERDAS 13 is used for all preprocessing steps to get a composite image, showing the total geographical area which is used for LU/LC assessment. The following (fig.2) LU/LC Layer has been classified as five different categories such as agricultural, Built up, Vegetarian, Waste/Barren and Water bodies. The present work is a utility of remotely sensed data for pipeline alignment study. The LU/LC assessment using satellite imagery LISS III provided reliable, faster, cost and time effective information for the present study area. The pipeline corridors have been selected in such a way to minimize the sensitive areas along the route like reef, vegetated areas etc. Figure 3 Land use map of study area editor@iaeme.com

8 Fabrice Mwizerwa and Anshul Garg Figure 4 Base map of study area Figure 5 Contour map of study Figure 6 Slope map of study area Figure 7 Hydrology map of study area editor@iaeme.com

9 Experimental Study on Effects on Properties of Concrete With Different Colours of Glass Powder as A Partial Replacement of Cement REFERENCES Figure 8 Transport network map of study area [1] Burrough, P.A., Principles of geographical information systems for land resources assessment. [2] Dalvi, N.N., Sanghai, S.K., Roy, P. and Sudarshan, S., Pipelining in multi-query optimization. Journal of Computer and System Sciences, 66(4), pp [3] Hijazi, J. and Geomatics, P.C.I., Elevation extraction from satellite data using PCI software. In First Symposium on Space Observation Technologies for Defense Applications, Abu Dhabi, United Arab Emirates (p. 6). [4] Mahmoud, M.S.A. and Abdalla, S.M.A., Management of Infrastructure For Water and Petroleum Demand in KSA By GIS. Management, 4(14). [5] Adelman, L., Evaluating Decision Support and Expert Systems. John Wiley and Sons, New York editor@iaeme.com