土地利用
索引(排版)
度量(数据仓库)
土地利用规划
环境经济学
基尼系数
分布(数学)
可行走性
智能增长
计算机科学
环境资源管理
统计
计量经济学
不平等
数学
土木工程
环境科学
建筑环境
数据挖掘
经济
工程类
经济不平等
万维网
数学分析
作者
Hamid Motieyan,Mohammad Azmoodeh
出处
期刊:Land Use Policy
[Elsevier]
日期:2021-09-03
卷期号:109: 105724-105724
被引量:13
标识
DOI:10.1016/j.landusepol.2021.105724
摘要
In land-use planning, the land-use mixed-ness is widely discussed as a pivotal factor that is highly related to smart growth and sustainable development goals, such as improving accessibility, socially-friendly walkable areas, social health outcomes, and quality of life. Despite proposing several indices, measuring land-use mixed-ness has always struggled with complexities such as determining land-use priorities, distance, and attributes, which needs a robust framework to consider for ideal mixed-ness and being improved constantly. By combining both divisional and integral indices, this paper has proposed a multi-component novel measure, which considers quantity, importance, distance, and balance in land-uses mixture along streets as main corridors of the daily commute in Tehran, Iran; named Mixed-use Distribution Index (MUDI). First, the measure calculates indices for land-use combination (LWC) and residential to non-residential land-uses (RR) in equal street sections. Then, the Gini index with some innovative spatial manipulation was applied to capture the evenness of ideal values of each index among streets' sections. Finally, the MUDI of the street was achieved by averaging two Gini indices. Comparing Gini and MUDI values with current characteristics of the case study, accessibility level, and allocation of some land-uses claims for the measure's reliability to employ in land-use planning evaluations.
科研通智能强力驱动
Strongly Powered by AbleSci AI