三维激光空地一体化在城市热岛研究中的应用——以上海延中绿地为例

doi:10.13474/j.cnki.11-2246.2023.0116

测绘通报 ›› 2023, Vol. 0 ›› Issue (4): 128-134.doi: 10.13474/j.cnki.11-2246.2023.0116

• 无人机测绘技术应用推广 • 上一篇下一篇

三维激光空地一体化在城市热岛研究中的应用——以上海延中绿地为例

孟陈¹, 卫炎豪¹, 武彩燕², 欧阳霖柯³, 李俊祥², 朱义⁴, 刘家霖⁴, 魏本胜^5,6, 降瑞娇^5,6

1. 景遥(上海)信息技术有限公司, 上海 200240;
2. 上海交通大学设计学院, 上海 200240;
3. 上海人工智能实验室, 上海 200232;
4. 上海市园林科学规划研究院, 上海 200232;
5. 上海勘测设计研究院有限公司, 上海 200050;
6. 中国长江三峡集团有限公司长江生态环境工程研究中心, 北京 100038

收稿日期:2022-12-19 发布日期:2023-04-25
作者简介:孟陈(1979—),男,博士,研究方向为摄影测量和人工智能遥感应用。E-mail:jingyaoit@126.com
基金资助:
国家自然科学基金青年基金(32001162);国家自然科学基金面上项目(31971485);中国博士后科学基金面上项目(2021M702131);上海市绿化和市容管理局科研项目(G190201);中国长江三峡集团有限公司科硕项目(202103552)

Application of 3D LiDAR air-ground integration technology in urban heat island research:a case study of Yanzhong greenspace in Shanghai

MENG Chen¹, WEI Yanhao¹, WU Caiyan², OUYANG Linke³, LI Junxiang², ZHU Yi⁴, LIU Jialin⁴, WEI Bensheng^5,6, JIANG Ruijiao^5,6

1. JingYao (Shanghai) Information Technology Co., Ltd., Shanghai 200240, China;
2. School of Design, Shanghai Jiao Tong University, Shanghai 200240, China;
3. Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China;
4. Shanghai Academy of Landscape Architecture Science and Planning, Shanghai 200232, China;
5. Shanghai Investigation, Design&Research Institude Co., Ltd., Shanghai 200050, China;
6. YANGTZE Eco-Environment Engineering Research Center, China Three Gorges Corporation, Beijing 100038, China

Received:2022-12-19 Published:2023-04-25

摘要/Abstract

摘要： 城市热岛效应是城市化进程中最显著的生态环境问题之一,城市绿地基础设施作为城市关键的自然要素,能够有效地缓解热岛效应。延中绿地的规划建设是上海市为缓解热岛效应给出的“基于自然解决方案”的重大举措。本文以上海市延中绿地为研究对象,基于无人机及其相应传感器获取的空、地激光雷达数据和Landsat 8 Collection 2 Level 2数据集的地表温度数据,对延中绿地的降温作用及其内部三维绿量分布格局和影响因子进行了研究。结论如下:①延中绿地具有显著的降温效应且具有方向性差异。其最大降温距离在各方向的排序依次是:东南＞西南＞东北＞西北,局部冷岛强度最大为西南方向,最小为东南方向;不同植被类型的降温效应从高到低依次为:乔木>草地>灌木。②延中绿地内三维绿量高值区域基本分布在其西北部靠近公路一侧,其余各处仅有高值零星分布;三维绿量与距道路距离(D_road)呈显著负相关,与距水体距离(D_water)呈显著正相关,与距建筑(D_fw)距离呈负相关,但无显著性;影响三维绿量格局的最优模型为224.35-1.51×D_road×0.41*D_water。研究结果对上海市热岛减缓及绿地规划管理具有重要的理论和实践意义。

关键词: 热岛效应, 延中绿地, 三维绿量, 三维激光

Abstract: Urban heat island effect is one of the most prominent ecological and environmental problems during the process of urbanization. Urban green space infrastructure is one of the key elements of the city, which can effectively alleviate the urban heat island. The planning and construction of Yanzhong greenspace is an important strategy of “natural based solution” given by Shanghai to alleviate the heat island effect. Based on the air-and ground-LiDAR data which are obtained from FEIMA UAV and its corresponding sensors, as well as land surface temperature from Landsat 8 Collection 2 Level 2 dataset, we analyze the cooling effect of Yanzhong green space in Shanghai, and the 3D vegetation volume distribution pattern and its influencing factors. The main conclusions are as the following: ① There is a directional cooling effect of Yanzhong greenspace, due to the influence of the surrounding landscape pattern. The sequence of the directional maximum cooling distance is the southeast, and followed by the southwest, northeast and northwest. While the maximum of the local cool island intensity is southwest, and the minimum is the southeast. The vegetation types greatly influence the cooling effect, with the ranking of their surface temperature from tree, grassland to shrub type. ② The higher 3D vegetation volume areas of Yanzhong greenspace mainly located in the northwest where nearby the highway, and dispersedly distributed across the greenspace. The 3D vegetation volume in Yanzhong greenspace is significantly negatively correlated with the distance from the road (D_road), and significantly positively correlated with the distance from the water body (D_water), while there is no significant correlation with the distance from the building (D_fw). The optimal model of the 3D vegetation volume is V_Yanzhong=224.354 56-1.513 65D_road+0.412 85D_water.Our study provides important theoretical and practical insights for urban heat island mitigation as well as urban greenspace planning and management.

Key words: urbanheat island effect, Yanzhong greenspace, 3D vegetation volume, 3D LiDAR

中图分类号:

P237

孟陈, 卫炎豪, 武彩燕, 欧阳霖柯, 李俊祥, 朱义, 刘家霖, 魏本胜, 降瑞娇. 三维激光空地一体化在城市热岛研究中的应用——以上海延中绿地为例[J]. 测绘通报, 2023, 0(4): 128-134.

MENG Chen, WEI Yanhao, WU Caiyan, OUYANG Linke, LI Junxiang, ZHU Yi, LIU Jialin, WEI Bensheng, JIANG Ruijiao. Application of 3D LiDAR air-ground integration technology in urban heat island research:a case study of Yanzhong greenspace in Shanghai[J]. Bulletin of Surveying and Mapping, 2023, 0(4): 128-134.

参考文献

[1] 蒋子琪,王旭红,冯子豪,等. 西安市热岛效应与污岛效应的相互作用研究[J]. 干旱区研究,2022,39(6):1768-1781.
[2] 伍明飞,林杰. 基于Landsat影像的杭州市主城区地表温度和热岛效应研究[J]. 科学技术与工程,2022,22(24):10812-10817.
[3] 张峥,李杨,问青春,等. 辽中南城市群热岛效应研究[J]. 环境科学与管理,2022,47(8):157-160.
[4] 古丽拜合热姆·艾合麦提,昝梅. 新疆天山北坡经济带主要城市群热岛效应对植被物候的影响[J]. 生态与农村环境学报,2022,38(7):872-881.
[5] 叶昊. 基于遥感影像处理技术的城市热岛效应分析研究[J]. 测绘技术装备,2022,24(2):16-22.
[6] 武彩燕. 蓝色和绿色基础设施对城市地表温度的综合自然缓解效应[D]. 上海:华东师范大学,2019.
[7] 李丹宁,刘东云,王鑫.缓解城市热岛效应的硬质景观设计方法研究综述[J].风景园林,2022,29(8):71-78.
[8] 赵晨晓,刘春卉,魏家星. 缓解城市热岛效应的南京市绿色基础设施网络构建方法[J]. 浙江农林大学学报,2021,38(6):1127-1135.
[9] 许睿,董家华,王凤兰. 城市热岛效应的影响因素、研究方法及缓解对策研究进展[J]. 仲恺农业工程学院学报,2020,33(4):65-70.
[10] 黄秋燕,杨建欣. 缓解热岛效应的园林树木遮荫设计[J]. 黑龙江农业科学,2022(5):69-73.
[11] 刘炜,赵尔平,雒伟群,等. 山地城市绿色廊道生态化建设缓解热岛效应:以拉萨市为例[J]. 西藏科技,2022(1):25-28.
[12] 乔玮洁. 城市绿地的热岛效应缓解作用:以常德市城市公园为例[J]. 广西城镇建设,2021(10):51-53.
[13] 王妍. 夏热冬冷地区城市公园缓解热岛效应影响因素研究[D]. 成都:西南交通大学,2021.
[14] 胡瑶瑶,谭少华,杨春. 山地城市公园冷岛效应的影响研究:以重庆主城区公园为例[J]. 园林,2022,39(7):115-125.
[15] 朱伶俐,丁凤,杨琳,等. 夏冬季城市公园与城市热岛/冷岛空间关系研究[J]. 福建师范大学学报(自然科学版),2020,36(1):87-95.
[16] 肖逸,戴斯竹,赵兵. 小尺度公园对于城市热岛效应的缓解作用:基于南京市中心城区社区公园的实证研究[J]. 景观设计学,2020,8(3):26-43.
[17] GRAFIUS D R,CORSTANJE R,WARREN P H,et al. The impact of land use/land cover scale on modelling urban ecosystem services[J]. Landscape Ecology,2016,31(7):1509-1522.
[18] CASALEGNO S,ANDERSON K,COX D T C,et al. Ecological connectivity in the three-dimensional urban green volume using waveform airborne LiDAR[J]. Scientific Reports,2017,7:45571.
[19] FAHMY M. Influence of urban canopy green coverage and future climate change scenarios on energy consumption of new sub-urban residential developments using coupled simulation techniques:a case study in Alexandria,Egypt[J]. Energy Reports,2020,6:638-645.
[20] 殷明,杨博,郑思俊. 低空消费级无人机三维绿量快速测量技术应用研究[J]. 园林,2020(4):38-43.
[21] 陈小祥,李嘉诚,徐雅莉. 基于LiDAR点云数据的城市三维绿量分层测算方法研究[J]. 测绘工程,2018,27(9):40-45.
[22] ERMIDA S L,SOARES P,MANTAS V,et al. Google earth engine open-source code for land surface temperature estimation from the landsat series[J]. Remote Sensing,2020,12(9):1471.
[23] CHANG Chiru. A preliminary study on the local cool-island intensity of Taipei city parks[J]. Landscape and Urban Planning,2007,80(4):386-395.
[24] CHENG Xiaoyun,WEI Bensheng,CHEN Guojian,et al. Influence of park size and its surrounding urban landscape patterns on the park cooling effect[J]. Journal of Urban Planning and Development,2015,141(3):1-6.
[25] 曹璐,胡瀚文,孟宪磊,等. 城市地表温度与关键景观要素的关系[J]. 生态学杂志,2011,30(10):2329-2334.
[26] 陈朱,陈方敏,朱飞鸽,等. 面积与植物群落结构对城市公园气温的影响[J]. 生态学杂志,2011,30(11):2590-2596.
[27] CHENG Xiaoyun,WEI Bensheng,CHEN Guojian,et al. Influence of park size and its surrounding urban landscape patterns on the park cooling effect[J]. Journal of Urban Planning and Development,2015,141(3):5-11.
[28] 袁帅,张金梦,徐志刚,等. 城市热岛效应对建筑形态的响应及其昼夜变化研究[J]. 地理与地理信息科学,2022,38(5):40-46.
[29] WU Caiyan,LI Junxiang,WANG Chunfang,et al. Estimating the cooling effect of pocket green space in high density urban areas in Shanghai,China[J]. Frontiers in Environmental Science,2021,9:657969.
[30] 熊秀海,代侦勇. 奉化市生态服务与土地利用强度的相关性分析[J]. 地理空间信息,2017,15(4):102-104.
[31] NOR A N M,CORSTANJE R,HARRIS J A,et al. Impact of rapid urban expansion on green space structure[J]. Ecological Indicators,2017,81:274-284.
[32] 刘畅,刘兆刚. 基于AHP哈尔滨城市森林三维绿量规划分析[J]. 东北林业大学学报,2011,39(4):52-55.

三维激光空地一体化在城市热岛研究中的应用——以上海延中绿地为例

Application of 3D LiDAR air-ground integration technology in urban heat island research:a case study of Yanzhong greenspace in Shanghai

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	张庆圆, 邹彦龙, 李金衡. 三维激光扫描技术在自然文物侵蚀剥落监测中的应用研究[J]. 测绘通报, 2023, 0(4): 140-144.
[2]	杨震, 孟祥武, 唐顺均, 王昊, 巩垠熙. 室内移动测量系统在新型基础测绘中的应用[J]. 测绘通报, 2023, 0(1): 149-153.
[3]	丁志广, 饶帅雄, 王田芳, 朱炯翟. 激光扫描与无人机空地一体融合测量应用[J]. 测绘通报, 2023, 0(1): 179-183.
[4]	卢建军, 李文海, 燕樟林, 鲍艳, 吴旭, 倪树新. 螺栓孔特征点云支持下的地铁盾构隧道环缝识别与环间错台量分析[J]. 测绘通报, 2022, 0(9): 6-11,22.
[5]	王宁, 任传斌, 姜伟玲. 城市轨道交通盾构隧道病害空间分布特征量化研究[J]. 测绘通报, 2022, 0(9): 12-17.
[6]	田有良, 樊廷立, 唐超. 面向地铁隧道表面渗漏水的快速检测技术[J]. 测绘通报, 2022, 0(9): 29-33.
[7]	马原放, 李海鹏, 贾光军. 三维激光点云自动化建模思路探索[J]. 测绘通报, 2022, 0(9): 119-122.
[8]	孔令惠, 陆德中, 叶飞. 三维激光扫描技术在历史建筑立面测绘中的应用[J]. 测绘通报, 2022, 0(8): 165-168,172.
[9]	孙振勇, 樊小涛, 叶飞, 陈绪刚. 天宝SX10影像扫描仪在水文泥沙监测中的应用[J]. 测绘通报, 2022, 0(8): 169-172.
[10]	周烨, 刘云波, 郑丽波, 龙泱君. 多平台点云数据的单木参数提取精度分析[J]. 测绘通报, 2022, 0(7): 168-172.
[11]	经皓然, 徐敬海. 异形建筑的无人机点云与地面三维激光扫描点云配准[J]. 测绘通报, 2022, 0(6): 32-39.
[12]	谢元, 董梦, 马新建. 多源数据在复杂场景建筑物三维重建的应用[J]. 测绘通报, 2022, 0(6): 143-147.
[13]	李旭. 三维激光扫描技术在地铁隧道竣工测量中的应用[J]. 测绘通报, 2022, 0(6): 166-169.
[14]	赵立都, 向中富, 周银, 马下平, 张双成, 司梦元, 陈茂霖, 胡川, 潘建平. 利用地面三维激光扫描进行桥梁挠度变形分析[J]. 测绘通报, 2022, 0(5): 95-100.
[15]	张驰, 白志辉, 李亮, 陈冉丽, 吴侃. 利用三维激光扫描技术监测矿区桥梁结构形变[J]. 测绘通报, 2022, 0(4): 122-129.