Please wait a minute...
国土资源遥感  2020, Vol. 32 Issue (1): 247-254    DOI: 10.6046/gtzyyg.2020.01.33
     技术应用 本期目录 | 过刊浏览 | 高级检索 |
城市新区不透水地表盖度与人为热的关系研究——以陕西省西咸新区为例
王茹1,2,张艳芳1,2(),张洪敏1,2,李云1,2
1. 陕西师范大学地理科学与旅游学院,西安 710119
2. 陕西师范大学地理学国家级实验教学示范中心,西安 710119
Study on the relationship between impervious surface coverage and artificial heat in new urban districts: A case study of Xixian New District, Shaanxi Province
Ru WANG1,2,Yanfang ZHANG1,2(),Hongmin ZHANG1,2,Yun LI1,2
1. College of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
2. National Experimental Teaching Demonstration Center of Geography (Shaanxi Normal University), Xi’an 710119, China
全文: PDF(4481 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

基于Landsat数据,采用线性光谱混合模型分解法提取陕西省西咸新区2007年和2016年2景影像的不透水地表盖度,利用地表能量平衡法提取同期人为热信息,并探讨二者间的关系。结果表明: ①2007—2016年间不透水面从294.93 km 2扩张至362.62 km 2,由以自然地表与低覆盖度等级占主导逐渐演变为以中、高覆盖度不透水地表盖度等级占主导; ②2016年研究区人为热在空间上区域差异显著,高值区集中分布于沣东新城中北部和空港新城西安咸阳国际机场周边,在秦汉新城中部、沣西新城北部和泾河新城部分地区有零星分布; ③各土地利用不透水地表盖度均值和人为热均值均呈现建设用地>耕地>林地>水体的特点; ④不透水盖度与人为热呈正相关,相关系数为0.97,各地区的人为热值随不透水地表盖度上升速率呈现空港新城>沣东新城>泾河新城>秦汉新城>沣西新城的规律。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
王茹
张艳芳
张洪敏
李云
关键词 西咸新区不透水地表盖度人为热线性光谱混合模型地表能量平衡法    
Abstract

Based on Landsat data, the authors extracted the impervious surface coverage of the two sceneries in Xixian New District in 2007 and 2016 by the linear spectral mixture model decomposition method, and extracted the artificial thermal information by the surface energy balance method in the same period, and investigated the relationship between them. The results are as follows: ① From 2007 to 2016, the impervious surface expanded from 294.93 km 2 to 362.62 km 2, and gradually changed from natural surface and low coverage to medium and high coverage. ② In 2016, the regional differences of anthropogenic heat in the study area were significant. The high-value areas were concentrated in the north-central part of Fengdong New Town and around Xianyang International Airport of Airport New Town, and were scattered in the central part of Qinhan New Town, northern part of Fengxi New Town and part of Jinghe New Town. ③ The mean values of impervious coverage and anthropogenic thermal mean values of land use showed the tendency of construction land>cultivated land>woodland>water body. ④ There was a positive correlation between impervious coverage and artificial heat, with a correlation coefficient of 0.97. The rate of increase of artificial heat values with impervious coverage had the tendency of Airport New Town>Fengdong New Town>Jinghe New Town>Qinhan New Town>Fengxi New Town.

Key wordsXixian New District    impervious surface coverage    anthropogenic heat    linear spectral mixing model    surface energy balance method
收稿日期: 2019-03-08      出版日期: 2020-03-14
ZTFLH:  TP79  
基金资助:国家社会科学基金项目“中国丝绸之路经济带生态文明建设评价与路径研究”(编号: 14XKS019)
通讯作者: 张艳芳     E-mail: zhangyf@snnu.edu.cn
作者简介: 王 茹(1995-),女,硕士研究生,主要从事专题地图与地理建模和遥感方面的研究。Email: 1774069505@qq.com。
引用本文:   
王茹,张艳芳,张洪敏,李云. 城市新区不透水地表盖度与人为热的关系研究——以陕西省西咸新区为例[J]. 国土资源遥感, 2020, 32(1): 247-254.
Ru WANG,Yanfang ZHANG,Hongmin ZHANG,Yun LI. Study on the relationship between impervious surface coverage and artificial heat in new urban districts: A case study of Xixian New District, Shaanxi Province. Remote Sensing for Land & Resources, 2020, 32(1): 247-254.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2020.01.33      或      http://www.gtzyyg.com/CN/Y2020/V32/I1/247
Fig.1  研究区范围
参数 建设用地 水体 耕地 林地
Zom/m 0.33 0.000 03 0.1 0.3
Zoh/m 0.003 3 0.000 088 0.001 0.000 3
d/m 1.66 0.05 0.1 1.5
Tab.1  不同土地利用类型的Zom,Zohd的值
Fig.2  ISC空间分布
覆盖度类型 2016年
自然地表 低覆盖度 中覆盖度 高覆盖度 极高覆盖度 合计
2007年 自然地表 61.01 77.05 61.76 31.89 17.89 249.60
低覆盖度 113.75 90.39 92.37 57.29 27.02 380.82
中覆盖度 34.87 32.65 44.79 31.93 9.67 153.91
高覆盖度 8.97 10.99 23.57 18.17 4.79 66.49
极高覆盖度 3.82 6.25 16.11 11.08 4.25 41.51
合计 222.42 217.33 238.60 150.36 63.62 892.33
Tab.2  2007—2016年间ISC转移矩阵
Fig.3  2007—2016年各地区不透水面占比分布
Fig.4  人为热空间分布
Fig.5  人为热剖面线分析
Fig.6  各地区ISC与人为热关系对比
Fig.7  2016年研究区土地利用
地表类型 ISC均值 人为热均值/(W·m-2)
水体 0.02 -70.76
林地 0.32 1.79
耕地 0.37 46.06
建筑用地 0.59 140.02
Tab.3  各土地利用ISC与人为热均值统计
Fig.8  各土地利用的ISC与人为热关系散点图
Fig.9  ISC与人为热拟合关系图
地区 拟合方程 R2
泾河新城 y=93.25x+11.76 0.94
空港新城 y=113.49x+11.52 0.97
秦汉新城 y=77.17x+29.18 0.95
沣东新城 y=105.22x+38.04 0.94
沣西新城 y=68.55x+20.28 0.94
全区 y=83.19x+23.56 0.97
Tab.4  2016年研究区ISC和人为热值拟合方程
[1] Weng Q . Remote sensing of impervious surfaces in the urban areas:Requirements,methods,and trends[J]. Remote Sensing of Environment, 2012,117:34-49.
[2] 袁超 . 基于光谱混合分解模型的城市不透水面遥感估算方法研究[D]. 长沙:中南大学, 2008.
Yuan C . Estimation Method of Urban Impervious Surfaces Based on Spectral Mixed Decomposition Model[D]. Changsha:Central South University, 2008.
[3] Torrance K E, Shun J S W . Time-varying energy consumption as a factor in urban climate[J]. Atmospheric Environment, 1976,10(4):329-337.
[4] 肖荣波, 欧阳志云, 李伟峰 , 等. 城市热岛的生态环境效应[J]. 生态学报, 2005,25(8):2055-2060.
Xiao R B, Ouyang Z Y, Li W F , et al. Eco-environmental effects of urban heat island[J]. Journal of Ecology, 2005,25(8):2055-2060.
[5] 王业宁, 孙然好, 陈利顶 . 北京市区车辆热排放及其对小气候的影响[J]. 生态学报, 2017,37(3):953-959.
Wang Y N, Sun R H, Chen L D . Study on the impact of vehicle emissions on microclimate in Beijing metropolis[J]. Acta Ecologica Sinica, 2017,37(3):953-959.
[6] 伶华, 刘辉志, 桑建国 , 等. 城市人为热对北京热环境的影响[J]. 气候与环境研究, 2004. 9(3):409-421.
Ling H, Liu H Z, Sang J G , et al. Effects of urban anthropogenic heat on Beijing’s thermal environment[J]. Climate and Environment Studies, 2004,9(3):409-421.
[7] 姬翠翠, 贾永红, 李晓松 , 等. 线性/非线性光谱混合模型估算白刺灌丛植被覆盖度[J]. 遥感学报, 2016,20(6):1402-1412.
Ji C C, Jia Y H, Li X S , et al. Estimation of vegetation coverage of Nitraria spinosa shrubs by linear/non-linear spectral hybrid model[J]. Journal of Remote Sensing, 2016,20(6):1402-1412.
[8] 王浩, 吴炳方, 李晓松 , 等. 流域尺度的不透水面遥感提取[J]. 遥感学报, 2011,15(2):388-400.
Wang H, Wu B F, Li X S , et al. Remote sensing extraction of impervious surface at watershed scale[J]. Journal of Remote Sensing, 2011,15(2):388-400.
[9] Wu C, Murray A T . Estimating impervious surface distribution by spectral mixture analysis[J]. Remote Sensing of Environment, 2003,84(4):493-505.
[10] 覃志豪, 李文娟, 徐斌 , 等. 陆地卫星TM6波段范围内地表比辐射率的估计[J]. 国土资源遥感, 2004,16(3):28-32.doi: 10.6046/gtzyyg.2004.03.07.
doi: 10.6046/gtzyyg.2004.03.07
Qin Z H, Li W J, Xu B , et al. Estimation of surface emissivity within TM6 band of Landsat[J]. Land and Resources Remote Sensing, 2004,16(3):28-32.doi: 10.6046/gtzyyg.2004.03.07.
doi: 10.6046/gtzyyg.2004.03.07
[11] 宋挺, 段峥, 刘军志 , 等. Landsat 8数据地表温度反演算法对比[J]. 遥感学报, 2015,19(3):451-464.
Song T, Duan Z, Liu J Z , et al. Comparison of land surface temperature inversion algorithms for Landsat8 data[J]. Journal of Remote Sensing, 2015,19(3):451-464.
[12] 徐涵秋 . 新型Landsat8卫星影像的反射率和地表温度反演[J]. 地球物理学报, 2015,58(3):741-747.
Xu H Q . New Landsat 8 satellite image reflectivity and surface temperature inversion[J]. Journal of Geophysics, 2015,58(3):741-747.
[13] 赵英时 . 遥感应用分析原理与方法[M]. 北京: 科学出版社, 2003: 235.
Zhao Y S. Principles and Methods of Remote Sensing Application Analysis[M]. Beijing: Science Press, 2003: 235.
[14] 王煜东, 赵小艳, 徐向华 , 等. 南京地区地表热通量的遥感反演分析[J]. 生态环境学报, 2016,25(4):636-646.
Wang Y D, Zhao X Y, Xu X H , et al. Remote sensing inversion analysis of surface heat flux in Nanjing area[J]. Journal of Ecology and Environment, 2016,25(4):636-646.
[15] Bastiaanssen W G M . SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin,Turkey[J]. Journal of hydrology, 2000,229(1):87-100.
[16] 李宝富, 陈亚宁, 李卫红 , 等. 基于遥感和SEBAL模型的塔里木河干流区蒸散发估算[J]. 地理学报, 2011,66(9):1230-1238.
Li B F, Chen Y N, Li W H , et al. Estimation of evapotranspiration in the main stream of Tarim River based on remote sensing and SEBAL model[J]. Journal of Geography, 2011,66(9):1230-1238.
[17] Zhou Y, Weng Q, Gurney K R , et al. Estimation of the relationship between remotely sensed anthropogenic heat discharge and building energy use[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012,67(none):65-72.
[18] Kato S, Yamaguchi Y . A nalysis of urban heat-island effect using ASTER and ETM+ data:Separation of anthropo-genic heat discharge and natural heat radiation from sensible heat flux[J]. Remote Sensing of Environment, 2005,99(1):44-54.
[19] Nishida K, Nemani R R, Running S W , et al. An operational remote sensing algorithm of land surface evaporation[J]. Journal of Geophysical Research:Atmospheres, 2003,108(D9):1-14.
[1] 朱红雷, 李颖, 刘兆礼, 付波霖. 基于半约束条件下不透水面的遥感提取方法[J]. 国土资源遥感, 2014, 26(2): 48-53.
[2] 单丹丹, 杜培军, 夏俊士, 柳思聪. 基于HJ-1数据和V-I-S模型的城市不透水层变化分析[J]. 国土资源遥感, 2011, 23(4): 92-99.
[3] 周纪, 陈云浩, 张锦水, 李京. 北京城市不透水层覆盖度遥感估算[J]. 国土资源遥感, 2007, 19(3): 13-17.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《国土资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 Email:gtzyyg@agrs.cn; gtzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发