4.5 Article

A Novel Composite Index to Measure Environmental Benefits in Urban Land Use Optimization Problems

Journal

Publisher

MDPI
DOI: 10.3390/ijgi11040220

Keywords

spatial compactness; land surface temperature; ecosystem service value; carbon storage; environmental benefits index

Funding

  1. Ministry of Foreign Affairs and Trade
  2. Tempus Public Foundation of the Hungarian Government

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This study aims to identify indicators of environmental benefits and propose a novel composite index to measure such benefits in urban land use optimization problems. The research findings show that land surface temperature is the most influential indicator, while carbon storage is the least important factor. The study also demonstrates the potential of using the proposed index in land use allocation to ensure environmental benefits.
In urban land use optimization problems, different conflicting objectives are applied. One of the most significant goals in urban land use optimization problems is to maximize environmental benefits. To quantify environmental benefits in land use optimization, many researchers have employed a variety of methodologies. According to previous studies, there is no standard approach for calculating environmental benefits in urban land use allocation problems. Against this background, this study aims to (a) identify indicators of environmental benefits and (b) propose a novel composite index to measure environmental benefits in urban land use optimization problems. This study identified four indicators as a measure of environmental benefits based on a literature assessment and expert opinion. These are spatial compactness, land surface temperature, carbon storage, and ecosystem service value. In this work, we proposed a novel composite environmental benefits index (EBI) to quantify environmental benefits in urban land use allocation problems using an ordered weighted averaging (OWA) method. The study results showed that land surface temperature (LST) is the most influential indicator of environmental benefit while carbon storage is the least important factor. Finally, the proposed method was applied in Rajshahi city in Bangladesh. This study identified that, in an average-risk decision, most of the land (64.55%) of the study area falls within the low-environmental-benefit zone due to a lack of vegetated land cover. The result suggests the potential of using EBI in the land use allocation problem to ensure environmental benefits.

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