Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches

Monirul Islam; Golam Kabir

doi:10.1007/978-3-032-14078-4_6

Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches

Monirul Islam^*
, Golam Kabir

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This study assesses the climatic vulnerability of Saskatchewan’s road network by examining how six climate-related factors—minimum and maximum temperature, rainfall, wind, snow, and flooding—affect infrastructure sustainability. Using Inverse Distance Weighting (IDW) interpolation and remote sensing, a composite risk index was developed with equal weighting for each factor. The resulting map classified road segments into five risk categories, revealing that approximately 3,800 km (14%) fall within high or very high-risk zones, mainly in southern and central regions. The spatial analysis highlights region-specific exposure and the influence of uniformly weighted variables on identifying vulnerable infrastructure. This framework offers a simplified, transparent approach to climate risk assessment, supporting spatial decision-making for infrastructure planning, asset management, and climate adaptation.

Original language	English
Title of host publication	Lecture Notes in Intelligent Transportation and Infrastructure
Publisher	Springer Nature
Pages	56-65
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-032-14078-4_6
State	Published - 2026
Externally published	Yes

Publication series

Name	Lecture Notes in Intelligent Transportation and Infrastructure
Volume	Part F1340
ISSN (Print)	2523-3440
ISSN (Electronic)	2523-3459

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

Keywords

Climate Risk Assessment
Equal Weighting Method
Inverse Distance Weighting (IDW)
Road Infrastructure
Spatial Analysis
Vulnerability

ASJC Scopus subject areas

Control and Systems Engineering
Automotive Engineering
Transportation
Computer Science Applications

Access to Document

10.1007/978-3-032-14078-4_6

Cite this

Islam, M., & Kabir, G. (2026). Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches. In Lecture Notes in Intelligent Transportation and Infrastructure (pp. 56-65). (Lecture Notes in Intelligent Transportation and Infrastructure; Vol. Part F1340). Springer Nature. https://doi.org/10.1007/978-3-032-14078-4_6

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abstract = "This study assesses the climatic vulnerability of Saskatchewan{\textquoteright}s road network by examining how six climate-related factors{\textemdash}minimum and maximum temperature, rainfall, wind, snow, and flooding{\textemdash}affect infrastructure sustainability. Using Inverse Distance Weighting (IDW) interpolation and remote sensing, a composite risk index was developed with equal weighting for each factor. The resulting map classified road segments into five risk categories, revealing that approximately 3,800 km (14\%) fall within high or very high-risk zones, mainly in southern and central regions. The spatial analysis highlights region-specific exposure and the influence of uniformly weighted variables on identifying vulnerable infrastructure. This framework offers a simplified, transparent approach to climate risk assessment, supporting spatial decision-making for infrastructure planning, asset management, and climate adaptation.",

keywords = "Climate Risk Assessment, Equal Weighting Method, Inverse Distance Weighting (IDW), Road Infrastructure, Spatial Analysis, Vulnerability",

author = "Monirul Islam and Golam Kabir",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.",

year = "2026",

doi = "10.1007/978-3-032-14078-4\_6",

language = "English",

series = "Lecture Notes in Intelligent Transportation and Infrastructure",

publisher = "Springer Nature",

pages = "56--65",

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Islam, M & Kabir, G 2026, Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches. in Lecture Notes in Intelligent Transportation and Infrastructure. Lecture Notes in Intelligent Transportation and Infrastructure, vol. Part F1340, Springer Nature, pp. 56-65. https://doi.org/10.1007/978-3-032-14078-4_6

Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches. / Islam, Monirul; Kabir, Golam.
Lecture Notes in Intelligent Transportation and Infrastructure. Springer Nature, 2026. p. 56-65 (Lecture Notes in Intelligent Transportation and Infrastructure; Vol. Part F1340).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches

AU - Islam, Monirul

AU - Kabir, Golam

PY - 2026

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N2 - This study assesses the climatic vulnerability of Saskatchewan’s road network by examining how six climate-related factors—minimum and maximum temperature, rainfall, wind, snow, and flooding—affect infrastructure sustainability. Using Inverse Distance Weighting (IDW) interpolation and remote sensing, a composite risk index was developed with equal weighting for each factor. The resulting map classified road segments into five risk categories, revealing that approximately 3,800 km (14%) fall within high or very high-risk zones, mainly in southern and central regions. The spatial analysis highlights region-specific exposure and the influence of uniformly weighted variables on identifying vulnerable infrastructure. This framework offers a simplified, transparent approach to climate risk assessment, supporting spatial decision-making for infrastructure planning, asset management, and climate adaptation.

AB - This study assesses the climatic vulnerability of Saskatchewan’s road network by examining how six climate-related factors—minimum and maximum temperature, rainfall, wind, snow, and flooding—affect infrastructure sustainability. Using Inverse Distance Weighting (IDW) interpolation and remote sensing, a composite risk index was developed with equal weighting for each factor. The resulting map classified road segments into five risk categories, revealing that approximately 3,800 km (14%) fall within high or very high-risk zones, mainly in southern and central regions. The spatial analysis highlights region-specific exposure and the influence of uniformly weighted variables on identifying vulnerable infrastructure. This framework offers a simplified, transparent approach to climate risk assessment, supporting spatial decision-making for infrastructure planning, asset management, and climate adaptation.

KW - Climate Risk Assessment

KW - Equal Weighting Method

KW - Inverse Distance Weighting (IDW)

KW - Road Infrastructure

KW - Spatial Analysis

KW - Vulnerability

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M3 - Chapter

AN - SCOPUS:105027901221

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EP - 65

BT - Lecture Notes in Intelligent Transportation and Infrastructure

PB - Springer Nature

ER -

Evaluating Climatic Vulnerability of Saskatchewan’s Road Network Through Inverse Distance Weighting (IDW) and Equal Weighting Approaches

Abstract

Publication series

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this