基于街景影像的城市道路空间舒适度研究

doi:10.12082/dqxxkx.2021.200353

地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (5): 785-801.doi: 10.12082/dqxxkx.2021.200353

• 地球信息科学理论与方法 • 上一篇下一篇

基于街景影像的城市道路空间舒适度研究

杨灿灿¹^,²(), 许芳年¹, 江岭¹^,²^,^*(), 王瑞璠¹, 尹力¹, 赵明伟¹^,², 张鲜鲜¹

1.滁州学院地理信息与旅游学院,滁州 239000
2.实景地理环境安徽省重点实验室,滁州 239000

收稿日期:2020-07-08 修回日期:2020-09-03 出版日期:2021-05-25 发布日期:2021-07-25
通讯作者: *江岭(1987— ),男,安徽寿县人,博士,副教授,主要研究方向为地形建模及城市雨洪模拟。 E-mail:jiangling_xs@163.com
作者简介:杨灿灿（1988— ）,女,安徽萧县人,硕士,讲师,主要研究方向为城市地形分析、遥感应用。E-mail:yangcancan77@126.com
基金资助:
安徽高校自然科学研究项目重点项目(KJ2020A0721);安徽高校自然科学研究项目重点项目(KJ2020A0722);安徽省高校优秀人才支持一般项目(gxyq2019093);中国博士后科学基金(2018M642146);安徽省自然科学基金项目(1808085QD103);江苏省博士后科研资助计划项目(2018K144C);国家级大学生创新创业训练项目(201910377054)

Approach to Quantify Spatial Comfort of Urban Roads based on Street View Images

YANG Cancan¹^,²(), XU Fangnian¹, JIANG Ling¹^,²^,^*(), WANG Ruifan¹, YIN Li¹, ZHAO Mingwei¹^,², ZHANG Xianxian¹

1. School of Geographical Information and Tourism, Chuzhou University, Chuzhou 239000, China
2. AnHui Province Key Laboratory of Physical Geographic Environment, Chuzhou 239000, China

Received:2020-07-08 Revised:2020-09-03 Online:2021-05-25 Published:2021-07-25
Contact: JIANG Ling
Supported by:
Key Project of Natural Science Research Project of Anhui Universities(KJ2020A0721);Key Project of Natural Science Research Project of Anhui Universities(KJ2020A0722);Anhui Province Universities Outstanding Talented Person Support Project(gxyq2019093);China Postdoctoral Science Foundation(2018M642146);Program of Provincial Natural Science Foundation of Anhui(1808085QD103);Jiangsu Planned Projects for Postdoctoral Research Funds(2018K144C);National Undergraduate Training Program for Innovation and Entrepreneurship(201910377054)

摘要/Abstract

摘要：

城市道路空间舒适度是综合刻画城市道路环境的量化指标之一,可为城市道路规划建设、城市交通优化、城市环境评估等提供参考。本文以街景影像为基础数据,从空间视角阐述了城市道路空间舒适度内涵,构建了城市道路空间舒适度量化指标,建立了以语义分割和等距采样为基础的城市道路空间舒适度测度方法和空间插值方法,最后以南京市局部城区为样区进行了实验,并分析了城市道路空间舒适度特征。实验结果表明：① 语义分割中主要要素的分割精度满足要求,分割总体精度为84.92%, Kappa系数为80.06%;② 综合考虑数据处理时间和舒适度量化表达程度, 200 m采样间距可以综合描述研究区道路空间舒适度状态;③ 本文提出的双向约束插值方法可消除突变点、梯形插值形态、花斑状纹理等异常插值现象,同时可有效保持道路空间舒适度方向特征;④ 本文提出的测度方法可以有效度量城市道路空间舒适度,测度等级精度达80%;⑤ 城市道路空间舒适度等级与道路等级整体上呈现正相关关系,且舒适度在实验区呈现南高北低、建邺区较高、鼓楼及历史老城区低的空间分布状态。

关键词: 城市道路, 空间舒适度, 街景影像, 等距采样, 语义分割, 指标量化, 空间插值, 空间分布

Abstract:

Urban road spatial comfort is an useful indicator to comprehensively quantify urban road environment, which plays an important role in urban-related researches such as construction planning, environment assessment, and traffic optimization. Based on the data of street view images, firstly, the concept of urban road spatial comfort is defined from the perspective of space vision. To represent the concept accurately, five quantitative indexes including road unobstructed degree, road spaciousness, greening degree of vegetation, proportion of sky view, and space openness, and a model to quantify urban road spatial comfort are constructed. Secondly, the urban road spatial comfort measurement method is established. To establish the model, an approach that comprehensively combines the semantic segmentation of street view images, weight assignment based on entropy weight, and analytic hierarchy process and dual-constrained interpolation is designed. Finally, we take the local urban area of Nanjing as the experimental area to assess the performance of the proposed approach. The results show that (1) The segmentation accuracy of the main elements meets the requirements, with an overall segmentation accuracy of 84.92% and a Kappa coefficient of 80.06%; (2) The 200-m sampling distance can comprehensively reflect the road spatial comfort degree in the study area considering the processing time and the quantitative expression; (3) The dual-constrained interpolation method proposed in this paper can eliminate the abnormal interpolation phenomena such as abrupt point, trapezoid shape, and disordered texture, and effectively maintain the directional characteristics of road spatial comfort; (4) The method proposed in this paper can effectively measure the urban road spatial comfort with an accuracy above 80%; (5) There is a positive correlation between the spatial comfort degree and the road grade, that is to say, the higher the road grade, the higher proportion of high-degree spatial comfort in roads. The spatial comfort of urban roads in the experimental area is higher in the south and lower in the north and is higher in Jianye district and lower in Gulou and historical old urban area.

Key words: urban road, spatial comfort, street view image, equidistance sampling, semantic segmentation, index quantification, spatial interpolation, spatial distribution

杨灿灿, 许芳年, 江岭, 王瑞璠, 尹力, 赵明伟, 张鲜鲜. 基于街景影像的城市道路空间舒适度研究[J]. 地球信息科学学报, 2021, 23(5): 785-801.DOI:10.12082/dqxxkx.2021.200353

YANG Cancan, XU Fangnian, JIANG Ling, WANG Ruifan, YIN Li, ZHAO Mingwei, ZHANG Xianxian. Approach to Quantify Spatial Comfort of Urban Roads based on Street View Images[J]. Journal of Geo-information Science, 2021, 23(5): 785-801.DOI:10.12082/dqxxkx.2021.200353

图/表 19

图1

图2

图3

图4

图5

表1

城市道路空间舒适度测度指标权重

舒适度指标	权重/%
道路通畅度（ $RU$ ）	31.09
道路宽广度（ $RS$ ）	23.76
植被绿化度（GD）	18.70
天空呈现度（ $SV$ ）	16.51
空间开敞度（ $SO$ ）	9.94

表1

图6

表2

图7

图8

图9

图10

图11

图12

图13

表3

图14

表4

表5

参考文献 38

[1]	孙守迁, 吴群, 吴剑锋, 等. 一种基于支持向量回归的驾驶座椅舒适度评价方法[J]. 中国机械工程, 2008,19(11):1326-1330.
	[ Sun S Q, Wu Q, Wu J F, et al. An evolution method of driving seat comfort based on support vector regression[J]. China Mechanical Engineering, 2008,19(11):1326-1330. ]
[2]	黄志甲, 余梦琦, 郑良基, 等. 徽州传统民居室内环境及舒适度[J]. 土木建筑与环境工程, 2018,40(1):97-104.
	[ Huang Z J, Yu M Q, Zheng L J, et al. Indoor environment and comfort of Huizhou traditional dwellings[J]. Journal of Chongqing Jianzhu University, 2018,40(1):97-104. ]
[3]	吴菲, 李树华, 刘娇妹. 林下广场、无林广场和草坪的温湿度及人体舒适度[J]. 生态学报, 2007,27(7):2964-2971.
	[ Wu F, Li S H, Liu J M. The effects of greening, none-greening square and lawn on temperature, humidity and human comfore[J]. Acta Ecologica Sinica, 2007,27(7):2964-2971. ]
[4]	景国勋, 李欢, 张坤. 基于多层次模糊综合评判的作业工人整体舒适度研究[J]. 安全与环境学报, 2014,14(3):80-83.
	[ Jing G X, Li H, Zhang K. On the comprehensive evaluation of the worker comfort based on multi-stage fuzzy synthetic judgment[J]. Journal of Safety and Environment, 2014,14(3):80-83. ]
[5]	吴志丰, 陈利顶. 热舒适度评价与城市热环境研究:现状、特点与展望[J]. 生态学杂志, 2016,35(5):1364-1371.
	[ Wu Z F, Chen L D. Thermal comfort assessment and urban thermal environment research: Review and prospective[J]. Chinese Journal of Ecology, 2016,35(5):1364-1371. ]
[6]	王颖, 郁梅, 应宏微, 等. 基于视差重映射的立体图像视觉舒适度提升[J]. 中国图象图形学报, 2017,22(4):452-462.
	[ Wang Y, Yu M, Ying H W, et al. Visual comfort enhancement for stereoscopic images based on disparity remapping[J]. Journal of Image and Graphics, 2017,22(4):452-462. ]
[7]	温婷, 林静, 蔡建明, 等. 城市舒适性:中国城市竞争力评估的新视角及实证研判[J]. 地理研究, 2016,35(2):214-226. doi: 10.11821/dlyj201602002
	[ Wen T, Lin J, Cai J M, et al. Urban amenity: A new perspective and empirical testimony on China's City competitiveness assessment[J]. Geographical Research, 2016,35(2):214-226. ]
[8]	曹云, 孙应龙, 吴门新. 近50年京津冀气候舒适度的区域时空特征分析[J]. 生态学报, 2019,39(20):7567-7582.
	[ Cao Y, Sun Y L, Wu M X. Spatial and temporal characteristics of the periods of climate comfort in the Beijing-Tianjin-Hebei region from 1966 to 2015[J]. Acta Ecologica Sinica, 2019,39(20):7567-7582. ]
[9]	孔锋. 中国人居环境气候舒适度的多时相尺度评价及区域差异研究[J]. 干旱区资源与环境, 2020,34(3):102-111.
	[ Kong F. Multi-temporal scale assessment of climate comfort of habitat environment and spatial differences in China[J]. Journal of Arid Land Resources and Environment, 2020,34(3):102-111. ]
[10]	闫业超, 岳书平, 刘学华, 等. 国内外气候舒适度评价研究进展[J]. 地球科学进展, 2013,28(10):1119-1125.
	[ Yan Y C, Yue S P, Liu X H, et al. Advances in assessment of bioclimatic comfort conditions at home and abroad[J]. Advances in Earth Science, 2013,28(10):1119-1125. ]
[11]	刘俊. 基于模糊数学的环鄱阳湖生态城市群城市舒适度评价[D]. 南昌:东华理工大学, 2019.
	[ Liu J. The evaluation of urban amenities based on fuzzy mathematics method in ecological urban agglomeration around Poyang lake[D]. Nanchang: East China University of Technology, 2019. ]
[12]	高超, 申双和, 蒋烨林, 等. 影响杭州人体舒适度的城市因素分析[J]. 气象, 2019,45(6):854-861.
	[ Gao C, Shen S H, Jiang Y L, et al. Analysis of urban factors impacting human comfort degree in Hangzhou[J]. Meteorological Monthly, 2019,45(6):854-861. ]
[13]	柏秦凤, 霍治国, 贺楠, 等. 中国20座旅游城市人体舒适度指数分析[J]. 生态学杂志, 2009,28(8):1607-1612.
	[ Bai Q F, Huo Z G, He N, et al. Analysis of human body comfort index of 20 tourist cities in China[J]. Chinese Journal of Ecology, 2009,28(8):1607-1612. ]
[14]	张青, 李颖, 骆月珍, 等. 杭州地区人体舒适度对自然死亡人数的影响[J]. 气象与环境学报, 2017,33(3):101-106.
	[ Zhang Q, Li Y, Luo Y Z, et al. Influence of human body comfort degree on natural mortality in Hangzhou[J]. Journal of Meteorology and Environment, 2017,33(3):101-106. ]
[15]	张亚丽, 方齐云. 城市舒适度对劳动力流动的影响[J]. 中国人口·资源与环境, 2019,29(3):118-125.
	[ Zhang Y L, Fang Q Y. The impact of City amenity on labor migration[J]. China Population Resources and Environment, 2019,29(3):118-125. ]
[16]	Long Y, Liu L. How green are the streets- An analysis for central areas of Chinese cities using Tencent street view[J]. Plos One, 2017,12(2):e0171110. doi: 10.1371/journal.pone.0171110
[17]	陈龙, 谢高地, 盖力强, 等. 道路绿地消减噪声服务功能研究——以北京市为例[J]. 自然资源学报, 2011,26(9):1526-1534.
	[ Chen L, Xie G D, Gai L Q, et al. Research on noise reduction service of road green spaces—A case study of Beijing[J]. Journal of Natural Resources, 2011,26(9):1526-1534. ]
[18]	Liang J M, Gong J H, Sun J, et al. Automatic sky view factor estimation from street view photographs- A big data approach[J]. Remote Sensing, 2017,9(5):411-428. doi: 10.3390/rs9050411
[19]	Gong F Y, Zeng Z C, Zhang F, et al. Mapping sky, tree, and building view factors of street canyons in a high-density urban environment[J]. Building & Environment, 2018,134:155-167.
[20]	贾瑞雨. 基于行车舒适性的高速公路沉降评价和扩建纵面设计研究[D]. 杭州:浙江大学, 2016.
	[ Jia R Y. Study on expressway settlement evaluation and profile design of extension project based on driving comfort[D]. Hangzhou: Zhejiang University, 2016. ]
[21]	王海涌, 党建武, 王晓明. 基于舒适度的高速铁路线路设计与优化[J]. 铁道工程学报, 2014,31(11):30-34.
	[ Wang H Y, Dang J W, Wang X M. Design and optimization of high-speed railway lines based on comfort[J]. Journal of Railway Engineering Society, 2014,31(11):30-34. ]
[22]	李晓玲, 张鄂, 陆长德. 人体生物力学模型的驾驶舒适度仿真研究[J]. 西安交通大学学报, 2008,42(5):556-560.
	[ Li X L, Zhang E, Lu C D. Driving comfort simulation based on human biomechanics model under vibration[J]. Journal of Xi'an Jiaotong University, 2008,42(5):556-560. ]
[23]	罗仕鉴. 基于生物学反应的驾驶舒适度研究[D]. 杭州:浙江大学, 2005.
	[ Luo S J. Study on driving comfort based on biological response[D]. Hangzhou: Zhejiang University, 2005. ]
[24]	王海涛, 黄鑫, 陈火根. 公路行车广义舒适度评价指标体系研究[J]. 公路, 2015(10):184-190.
	[ Wang H T, Huang X, Chen H G. Virtual integrated investment estimation method for traffic engineering project[J]. Highway, 2015(10):184-190. ]
[25]	靳增鑫. 人均出行舒适度评定研究[D]. 长沙:长沙理工大学, 2011.
	[ Jin Z X. Assessment of the level of travel comfortable per capita[D]. Changsha: Changsha University of Science & Technology, 2011. ]
[26]	Li X, Ratti C, Seiferling I. Quantifying the shade provision of street trees in urban landscape: A case study in Boston, USA, using Google street view[J]. Landscape & Urban Planning, 2018,169:81-91.
[27]	Zeng L, Lu J, Li W, et al. A fast approach for large-scale sky view factor estimation using street view images[J]. Building & Environment, 2018,135:74-84.
[28]	Cheng L, Chu S S, Zong W W, et al. Use of tencent street view imagery for visual perception of streets[J]. International Journal of Geo-Information, 2017,6(9):265-285.
[29]	Chen L C, Papandreou G, Kokkinos I, et al. DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018,40(4):834-848. doi: 10.1109/TPAMI.2017.2699184
[30]	南京市规划和自然资源局. 南京历史文化名城保护规划(2010-2020) [EB/OL]. http://ghj.nanjing.gov.cn/ghbz/ztgh/201705/t20170509_874088.html, 2019-12-27.
	[ Nanjing Municipal Bureau of planning and natural resources. Nanjing Conservation Plan of Historic City (2010-2020)[EB/OL]. http://ghj.nanjing.gov.cn/ghbz/ztgh/201705/t20170509_874088.html, 2019-12-27. ]
[31]	李威, 王蒙. 基于渐进多源域迁移的无监督跨域目标检测[J/OL]. 自动化学报, 2020,6:1-14.
	[ Li Wei, Wang Meng. Unsupervised cross-domain object detection based on progressive multi-source transfer[J]. Acta Automatica Sinica, 2020,6:1-14. ]
[32]	刘学军, 王美珍, 甄艳, 等. 单幅图像几何量测研究进展[J]. 武汉大学学报·信息科学版, 2011(8):941-947.
	[ Liu X J, Wang M Z, Zhen Y, et al. Geometric measurement based on single image: A survey[J]. Geomatics and Information Science of Wuhan University, 2011(8):941-947. ]
[33]	中华人民共和国住房和城乡建设部, 中华人民共和国国家质量监督检验疫总局. 中华人民共和国国家标准-城市道路交通标志和标线设置规范(GB51038-2015)[S]. 北京: 中国计划出版社, 2015.
	[ Ministry of housing and urban rural development, general administration of quality supervision. Code for layout of urban traffic signs and markings (GB51038-2015)[S]. Beijing: China Planning Press, 2015. ]
[34]	张晨, 王清, 陈剑平, 等. 金沙江流域泥石流的组合赋权法危险度评价[J]. 岩土力学, 2011,32(3):831-836.
	[ Zhang C, Wang Q, Chen J P, et al. Evaluation of debris flow risk in Jinsha River based on combined weight process[J]. Rock and Soil Mechanics, 2011,32(3):831-836. ]
[35]	陈然, 姚小军, 闫超, 等. 基于GIS和组合赋权法的农村生态功能适宜性评价及管制分区[J]. 长江流域资源与环境, 2012,21(6):720-725.
	[ Chen R, Yao X J, Yan C, et al. Ecological function suitability assessment a regulation division based on GIS and combination weighting method[J]. Resources and Environment in Yangtze Basin, 2012,21(6):720-725. ]
[36]	谢晓议, 曾咺, 李军. 基于移动窗口法和栅格数据的重庆市人居环境自然适宜性评价[J]. 长江流域资源与环境, 2014,23(10):1351-1359.
	[ Xie X Y, Zeng X, Li J. Evaluation of nature suitability for human settlement in Chongqing[J]. Resources and Environment in Yangtze Basin, 2014,23(10):1351-1359. ]
[37]	苏巧梅, 赵尚民, 郭建立. 霍西煤矿区地表滑坡灾害敏感性数值建模与等级划分[J]. 地球信息科学学报, 2017,19(12):1613-1622. doi: 10.3724/SP.J.1047.2017.01613
	[ Su Q M, Zhao S M, Guo J L. Numerical modeling and degree division to landslide susceptibility in the ground surface of huoxi coal mine area[J]. Journal of Geo-information Science, 2017,19(12):1613-1622. ]
[38]	姜颖, 洪军, 王崴, 等. 面向VDT显示界面的视觉舒适度客观描述方法[J]. 中南大学学报(自然科学版), 2017,48(1):77-83.
	[ Jiang Y, Hong J, Wang W, et al. An objective description method of visual comfort for VDT display interface[J]. Journal of Central South University (Science and Technology), 2017,48(1):77-83. ]

分类类别	评价指标
分类类别	错分误差/%	漏分误差/%	制图精度/%	用户精度/%	Kappa系数/%	总体精度/%
道路	4.33	14.94	85.06	95.67	80.06	84.92
天空	5.03	4.73	95.27	94.97
建筑	41.96	6.75	93.25	58.04
车辆	26.00	21.93	78.07	74.00
树木	17.92	15.69	84.31	82.08
灌木	39.43	19.20	80.80	60.57
围栏	50.89	59.57	40.43	49.11
附属	44.75	75.95	24.05	55.25

道路等级	空间舒适度等级	等级占比/%	等级平均值
一级	1	10.25	3.52
	2	14.96
	3	18.01
	4	25.76
	5	31.02
二级	1	19.93	2.93
	2	21.77
	3	22.88
	4	16.61
	5	18.82
三级	1	30.98	2.45
	2	22.22
	3	24.92
	4	14.48
	5	7.41

区划	空间舒适度等级	等级占比/%	等级平均值	区划	空间舒适度等级	等级占比/%	等级平均值
鼓楼区	1	27.27	2.63	雨花台区	1	8.12	3.14
	2	22.97			2	24.32
	3	21.77			3	27.03
	4	15.78			4	27.03
	5	12.20			5	13.51
秦淮区	1	22.52	2.82	建邺区	1	9.01	3.55
	2	19.82			2	15.92
	3	23.42			3	18.62
	4	20.72			2	24.32
	5	13.51			5	32.13

基于街景影像的城市道路空间舒适度研究

Approach to Quantify Spatial Comfort of Urban Roads based on Street View Images

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 19

参考文献 38

相关文章 15

Metrics

本文评价

推荐阅读 0

样点序号	本文量化等级	主观评价等级	等级差	样点序号	本文量化等级	主观评价等级	等级差
1	3	3	0	16	1	2	-1
2	3	3	0	17	3	3	0
3	2	2	0	18	4	4	0
4	3	2	1	19	1	1	0
5	5	5	0	20	5	5	0
6	3	3	0	21	5	5	0
7	4	3	1	22	4	4	0
8	5	5	0	23	5	5	0
9	4	4	0	24	4	4	0
10	3	3	0	25	5	5	0
11	1	1	0	26	1	1	0
12	2	2	0	27	4	5	-1
13	4	3	1	28	1	3	-2
14	2	2	0	29	1	1	0
15	2	2	0	30	3	3	0

[1]	柳林, 谢华芳, 岳瀚. 不同街景影像微环境提取方法对街面财产犯罪解释的差异分析[J]. 地球信息科学学报, 2023, 25(7): 1432-1447.
[2]	杨颖频, 吴志峰, 黄启厅, 骆剑承, 吴田军, 董文, 胡晓东, 肖文菊. 协同遥感与统计数据的粤西甘蔗种植分布提取及时空分析[J]. 地球信息科学学报, 2023, 25(5): 1012-1026.
[3]	张宇峥, 鲁岩, 陈晓键. 实体-信息与场景-符号视角下的奶茶消费空间分布特征及影响因素[J]. 地球信息科学学报, 2023, 25(4): 823-837.
[4]	李心雨, 闫浩文, 王卓, 王炳瑄. 街景图像与机器学习相结合的道路环境安全感知评价与影响因素分析[J]. 地球信息科学学报, 2023, 25(4): 852-865.
[5]	衡雪彪, 许捍卫, 唐璐, 汤恒, 许怡蕾. 基于改进全卷积神经网络模型的土地覆盖分类方法研究[J]. 地球信息科学学报, 2023, 25(3): 495-509.
[6]	巫磊, 吴文挺. GEE平台下结合滤波算法和植被物候特征的互花米草遥感提取最优时间窗口确定[J]. 地球信息科学学报, 2023, 25(3): 606-624.
[7]	高建文, 管海燕, 彭代锋, 许正森, 康健, 季雅婷, 翟若雪. 基于局部-全局语义特征增强的遥感影像变化检测网络模型[J]. 地球信息科学学报, 2023, 25(3): 625-637.
[8]	贝祎轩, 陈传法, 王鑫, 孙延宁, 何青鑫, 李坤禹. 机载LiDAR点云密度和插值方法对DEM及地表粗糙度精度影响分析[J]. 地球信息科学学报, 2023, 25(2): 265-276.
[9]	刘洋, 康健, 管海燕, 汪汉云. 基于双注意力残差网络的高分遥感影像道路提取模型[J]. 地球信息科学学报, 2023, 25(2): 396-408.
[10]	焦怀瑾, 陈崇成, 黄洪宇. 结合ICESat-2和GEDI的中国东南丘陵地区ASTER GDEM高程精度评价与修正[J]. 地球信息科学学报, 2023, 25(2): 409-420.
[11]	蒋伟杰, 张春菊, 徐兵, 罗晨晨, 周晗, 周康. AED-Net：滑坡灾害遥感影像语义分割模型[J]. 地球信息科学学报, 2023, 25(10): 2012-2025.
[12]	杨洋, 邵哲平, 赵强, 潘家财, 胡雨, 梅强. 基于厦门港的海上交通事故地理空间分布及风险预测研究[J]. 地球信息科学学报, 2022, 24(9): 1676-1687.
[13]	郭春华, 朱秀芳, 张世喆, 唐明秀, 徐昆. 基于CMIP6的中国未来高温危险性变化评估[J]. 地球信息科学学报, 2022, 24(7): 1391-1405.
[14]	孙银萍, 张兴国, 石新雨, 李奇泽. 顾及视频地理映射的人群密度估计方法[J]. 地球信息科学学报, 2022, 24(6): 1130-1138.
[15]	蒯宇, 王彪, 吴艳兰, 陈搏涛, 陈兴迪, 薛维宝. 基于多尺度特征感知网络的城市植被无人机遥感分类[J]. 地球信息科学学报, 2022, 24(5): 962-980.

样点序号	本文量化等级	主观评价等级	等级差	样点序号	本文量化等级	主观评价等级	等级差
1	3	3	0	16	1	2	-1
2	3	3	0	17	3	3	0
3	2	2	0	18	4	4	0
4	3	2	1	19	1	1	0
5	5	5	0	20	5	5	0
6	3	3	0	21	5	5	0
7	4	3	1	22	4	4	0
8	5	5	0	23	5	5	0
9	4	4	0	24	4	4	0
10	3	3	0	25	5	5	0
11	1	1	0	26	1	1	0
12	2	2	0	27	4	5	-1
13	4	3	1	28	1	3	-2
14	2	2	0	29	1	1	0
15	2	2	0	30	3	3	0

样点序号	本文量化等级	主观评价等级	等级差	样点序号	本文量化等级	主观评价等级	等级差
1	3	3	0	16	1	2	-1
2	3	3	0	17	3	3	0
3	2	2	0	18	4	4	0
4	3	2	1	19	1	1	0
5	5	5	0	20	5	5	0
6	3	3	0	21	5	5	0
7	4	3	1	22	4	4	0
8	5	5	0	23	5	5	0
9	4	4	0	24	4	4	0
10	3	3	0	25	5	5	0
11	1	1	0	26	1	1	0
12	2	2	0	27	4	5	-1
13	4	3	1	28	1	3	-2
14	2	2	0	29	1	1	0
15	2	2	0	30	3	3	0