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Identification of Essential Descriptors in Spatial Socioeconomic Impact Assessment Modeling: a Case Study of Highway Broadening in Sikkim Himalaya

  • Polash BanerjeeEmail author
  • Mrinal Kanti Ghose
  • Ratika Pradhan
Article

Abstract

Identifying the right set of socioeconomic descriptors (SEDs) during the spatial analysis of a socioeconomic impact assessment (SEIA) is pivotal for a reliable impact modeling. For this, methods like factor analysis and sensitivity analysis can be used. As a case study, the spatial socioeconomic impact assessment model (SSEIAM) of the broadening of highway NH 10 in the East district of Sikkim is used to emphasize this issue. Principal component analysis (PCA) is used to identify the most important SEDs contributing to the composite impact estimated by SSEIAM. Furthermore, spatially explicit sensitivity analysis (SESA) is performed to identify the model sensitivity to SED weights. SSEIAM is a GIS-based model that relies on experts’ opinion and peoples’ perception of the impacts of the project on the SEDs. The model uses weighted linear combination (WLC) of kriging-generated SED surfaces to prepare the composite impact map. PCA indicates that farming activities, health facilities, traditional values, demographic profile, tourism, and land use and land value are the major contributors to the variance in the descriptor space. SESA shows that SSEIAM is robust. However, land use and land value and farming activities contribute most to the perturbations of the composite impact value. This suggests that model variable identification is a crucial step towards impact modeling.

Keywords

Analytic hierarchy process Socioeconomic impact assessment Geographic information systems Principal component analysis Spatially explicit sensitivity analysis Highway 

Abbreviations

AHP

Analytic hierarchy process

EIA

Environmental impact assessment

LULV

Land use and land value

MACR

Mean absolute change rate

MCDM

Multi-criteria decision-making

OAT

One factor at a time

PCA

Principal component analysis

PC(s)

Principal component(s)

SED(s)

Socioeconomic descriptor(s)

SSEIAM

Spatial socioeconomic impact assessment model

SEIA

Socioeconomic impact assessment

SESA

Spatially explicit sensitivity analysis

WLC

Weighted linear combination

Notes

Compliance with Ethical Standards

The authors abide by the ethical standards of the journal.

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

The manuscript is in abidance with the academic and publication ethics.

Informed Consent

The authors have taken due consents for the competent authorities for preparation and communication of this study.

Supplementary material

41651_2019_27_MOESM1_ESM.docx (15 kb)
ESM 1 (DOCX 14.5 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Sikkim Manipal Institute of TechnologySikkim Manipal UniversityMajitarIndia
  2. 2.Department of Computer ApplicationsSikkim UniversityGangtokIndia
  3. 3.Department of Computer Applications, Sikkim Manipal Institute of TechnologySikkim Manipal UniversityMajitarIndia

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