PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 5, 2026Sustainable Development1 citations

Spatial Modeling of Land‐Use Adaptability to Climate Change: An MCDA – GIS Approach for Taiwan

View Full Paper
HTHsueh‐Yang TsengYCYi‐Chang Chiang

Key Points

  • Assess land-use adaptability to climate hazards in Taiwan and establish a framework for climate-resilient planning.
  • Developed a multi-criteria decision analysis (MCDA)–GIS framework.
  • Conducted expert consultations to identify land-use factors' importance.
  • Applied analytic hierarchy process (AHP) and analytic network process (ANP) for weight determination.
  • Employed spatial autocorrelation analysis using Moran's I and LISA.
  • Identified forestry, water-conservation, and transportation as key factors in adaptive capacity.
  • Revealed significant east-west disparities in spatial resilience patterns.
  • Provided a transparent framework for integrating expert judgment and spatial analytics into land-use planning.

Abstract

ABSTRACT Taiwan is highly vulnerable to climate change, facing increasing risks from typhoons, floods, and landslides. This study develops an integrated multi‐criteria decision analysis (MCDA)–GIS framework to evaluate land‐use adaptability to climate hazards at the township scale. Expert consultation was used to determine the relative importance and interdependencies of nine main and fifty‐four sub‐category land‐use factors through the analytic hierarchy process (AHP) and analytic network process (ANP). The resulting weights were incorporated into spatial‐autocorrelation analysis using Moran's I and LISA to examine clustering patterns from macro‐ and micro‐spatial perspectives. The results show that forestry, water‐conservation, and transportation lands are the primary drivers of adaptive capacity, while pronounced east–west disparities persist in spatial resilience patterns. The proposed framework provides a transparent and replicable approach that links expert judgment with spatial analytics, offering a quantitative basis for climate‐resilient land‐use planning and adaptive policy formulation in hazard‐prone regions.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Tseng et al. (2026) studied this question.

synapsesocial.com/papers/698435aaf1d9ada3c1fb4c2dhttps://doi.org/10.1002/sd.70717
Ask AI
Helpful
Bookmark
Share
View Full Paper