GUJARAT TECHNOLOGICAL

UNIVERSITY

BIRLA VISHWAKARMA MAHAVIDHYALAYA

PAPER REVIEWED

1. ENVIROMENTAL IMPACT ASSESSMENT FOR TRANSPORTATIONPROJECTSCASE STUDY USING REMOTE-SENSING TECHNOLOGY,GEOGRAPHIC INFORMATION SYSTEMS, AND SPATIAL MODELING

KUSHALKUMAR G PATEL140080713009

INTRODUCTION

Environmental Impact Assessment (EIA) is a tool to study various impact to beoccurred due to new development actions.

Transportation Project are the projects which provides ease to the movement ofvehicles.

This Paper presents a case study for analysis of EIA for a transportation project. ThisPaper would provide a methodology which will allow transportation planers to make acost effective coordination of environmental information and data management.

The results assess the environmental vulnerability around the road and its impact onenvironment by integration the merits of GIS.

METHODOLOGY

SYSTEM STRUCTURE

ASSESSMENT FACTORS

STEPS FOR USING GIS MODULE

ArcInfo software was used as a GIS platform to prepare the data processing and preparation:

1. File format conversion: the software was used to convert the image data from theGeo tiff format to the img format, which is the ERDAS IMAGINE format of thepicture.

2. Reprojection: gathered spatial (GIS) data layers were collected from differentsources and were projected with different projections. All data layers werereprojected to the same geo- graphic reference to establish an implicit spatialcorrespondence relationship between the layers, which facilitates subsequentdata processing and analysis.

3. Area of interest (AOI) clipping: the satellite image, aerial photographs, and spatial(GIS) data layers covered different area extents. The ArcInfo sub module was usedto clip the area of the internet to be used for further analysis. The AOI wasidentified by the boundary limits of Okaloosa County. For the clipping of theraster data, the Spatial Analyst calculator was used.

DATA BANK USED

The Florida Geographic Data Library (FGDL) was selected as a mechanism fordistributing aerial photographs and spatial (GIS) data. The main reason for choosing it isthat this library has been designed carefully and is well managed. Following table showsthe list of GIS maps used from library.

Partial List of Data Layers Required

Description File name Type Source Extent

2000 Census blocks CENBLK Polygon USCB County

Drastic coverage for the surficial

aquifer system

AQDRSU Polygon FDEP County

FEMA Flood Insurance Rate Maps

1996

FEMA96 Polygon FEMA County

Historic bridges SHPO_BRIDGES Line BAR State

Strategic Habitat and Conservation

Areas 2000

SHCA Polygon FFWCC State

CRITERIA WEIGHTING MODULE

• For the measurement of criteria-related weights, pairwise comparisonswere utilized for practicality, operational efficiency, and reliability, aswell as acceptance by decision makers.

• The experts were asked to compare all criteria, thus creating a matrix ofvalues for each comparison pair. The average of all the experts’ matriceswas used to determine the main comparison matrix. Then the weights ofthe vector were normalized to apply Yager’s methods (1977) forcalculating the required weights.

• Factors’ weights were calculated by the “BLZPACK” software that is animplementation of the block Lanczos algorithm (Marques and Vasco2000).

Pairwise Comparisons Matrix

CRITERIA Population

density

Arch LULC DRASTI

C

Foundation Eco.

model

Wetla

nd

Floo

d

Wildlif

e

Spec.

water

Milita

ry

Population

density

1 0.91 0.45 0.9 0.23 0.46 1.1 0.45 0.7 0.68 0.23

Arch 1.10 1 0.46 0.91 0.22 0.46 1.14 0.46 0.68 0.7 0.22

LULC 2.22 2.17 1 1.82 0.45 0.91 2.27 0.91 1.3 1.4 0.45

DRASTIC 1.11 1.10 0.55 1 0.22 0.45 1.1 0.45 0.6 0.7 0.23

Foundation 4.35 4.55 2.22 4.55 1 1.8 4.5 1.8 2.7 2.7 0.9

Eco. model 2.17 2.17 1.10 2.22 0.56 1 2.25 0.9 1.3 1.4 0.44

Wetland 0.91 0.88 0.44 0.91 0.22 0.44 1 0.4 0.5 0.6 0.17

Flood 2.22 2.17 1.10 2.22 0.56 1.11 2.50 1 1.3 1.4 0.44

Wildlife 1.43 1.47 0.77 1.67 0.37 0.77 2.00 0.77 1 0.9 0.29

Spec. water 1.47 1.43 0.71 1.43 0.37 0.71 1.67 0.71 1.11 1 0.29

Military 4.35 4.55 2.22 4.35 1.11 2.27 5.88 2.27 3.45 3.45 1

ENVIROMENTAL VULNERABLITY GRADE MAP

Developing the environmental vulnerability grade map can be rep- resented by thefollowing:

(1) Reclassifying the GIS layers and the classified maps according to the regional weightswithin the same criteria to develop criteria vulnerability maps;

(2) Rasterizing all the maps and GIS layers using the Spatial Analyst module, which is anextension module within ArcInfo (1 m was chosen as the output cell size for thelayers); and

(3) The ERDAS IMAGINE Model Maker is used to construct a script model to combine thecriteria vulnerability maps and the criteria-related weights to develop theenvironmental vulnerability map.

Figure below illustrates the concept of combining the criteria vulnerability maps andthe criteria-related weights to develop the environmental vulnerability map.

ENVIROMENTAL VULNERABLITY GRADE MAP

CONCLUSION

• Using this methodology a standard analysis approach is formulated based onthe integration between GIS data and the remote sensing data.

• Using inputs by experts and stakeholders, evaluation criteria and the relativeimportance of these criteria is determined and the integrated data & therelative weights and criteria are used to arrive at a measure for theenvironment impact of the project.

• With a focus on sustainable planning, urban and regional planners can betterexplore long-term impacts caused by growth and revitalization of urban,suburban, and rural communities and the regions in which they are located.

• In general, this methodological framework is expected to improve thequality of the decision- making process and planning for built-environmentprojects regarding the concerns for environmental impacts.