A study of the livability of urban environment based on multi-source remote sensing data: A case study of Beijing City

doi:10.6046/gtzyyg.2020.03.22

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Abstract

Based on the remote sensing data, this paper aims to construct an urban environment livability evaluation system on the basis of remote sensing factors and further evaluate the livability of the urban environment. An object-oriented classification method was used to classify urban ecological land into five categories from GF-1 satellite data: water body, vegetation area, road, building land, and bare soil. In addition, the urban surface temperature was retrieved from Landsat8 thermal infrared data and then, the urban thermal environment was calculated. Finally, on the basis of constructing the urban ecological land and urban thermal environment factors, a weight method was used to calculate the ecological quality index (EQI) of the city in order to establish an overall evaluation system of urban environmental livability. Applications in Beijing City showed that, from 2013 to 2014, the urban heat island effect in Beijing was not obvious, and most areas were suitable or basically suitable for human habitation.

Keywords multi-source remote sening urban ecological land urban thermal environment livability evaluation

TP79

Corresponding Authors: REN Huazhong E-mail: dongjiaji@pku.edu.cn;renhuazhong@pku.edu.cn

Issue Date: 09 October 2020

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	Jiaji DONG
	Huazhong REN
	Yitong ZHENG
	Jing NIE
	Jinjie MENG
	Qiming QIN

Cite this article:

Jiaji DONG,Huazhong REN,Yitong ZHENG, et al. A study of the livability of urban environment based on multi-source remote sensing data: A case study of Beijing City[J]. Remote Sensing for Land & Resources, 2020, 32(3): 165-172.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.03.22 OR https://www.gtzyyg.com/EN/Y2020/V32/I3/165

Fig.1 Flowchart for the evaluation of the livability of urban environment

地类	指数	公式	说明
水体	归一化差值水体指数(normalized difference water index, NDWI)	$NDWI = ρ green - ρ NIR ρ green + ρ NIR$	式中 $ρ green$ 和 $ρ NIR$ 分别为绿光和近红外波段的反射率。当NDWI $≥$ 0.12时,为水体^[28]
植被	归一化差值植被指数(normalized difference vegetation index, NDVI)	$NDVI = ρ NIR - ρ red ρ NIR + ρ red$	式中 $ρ red$ 为红光波段的反射率。当NDVI>0.12时,为植被^[29]
道路	长宽比指数(R)	$R = L W$	式中: L为图斑对象长度; W为图斑对象宽度。设置阈值R≥3,L≥170像元为道路^[30]
建筑用地	灰度最大差值与亮度的比值(Diff_max); 形状指数(K); 灰度共生矩阵熵(Ent)	$Dif f max = i, j ∈ K B \| c i (v) - c j (v) \| c (v)$ $K = A P$ $Ent = ∑ i = 1 n ∑ j = 1 n p (i, j) × ln [p (i, j)]$	式中: $c i (v)$ 为对象v在i层的平均亮度值; $c j (v)$ 为对象v在j层的平均值; $K B$ 为所有的对象; c(v)为所有层对象v的平均值^[31]; A与P分别为影像对象的面积和周长; $p (i, j)$ 为像元值i和j出现的概率^[32]
裸土	紧凑度(C)	$C = n × m b$	式中: C为紧凑度; n为影像对象的宽; m为对象的长度; b为对象内的像素数^[31]

Tab.1 Classification rules corresponding to each feature type

Tab.2 Score levels of urban ecological land covers on the livability of urban environment

Tab.3 Score levels of urban NDVI on the livability of urban environment

Tab.4 Score levels of urban water body distance on the livability of urban environment

Tab.5 Score levels of urban road distance on the livability of urban environment

Tab.6 Score levels of summer urban thermal environment on the livability of urban environment

Tab.7 Score levels of winter urban thermal environment on the livability of urban environment

Tab.8 The weights of factors on the livability of urban environment

Tab.9 EQI and the livability levels of urban environment

Fig.2 Urban ecological land covers images in Beijing on three dates

Fig.3 Urban ecological land covers histograms in Beijing

Fig.4 Map of land surface temperature and UHI in Beijing and the histograms

Fig.5 Livability of urban environment in Beijing on three dates

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