“海上丝绸之路”超大城市环境变化遥感分析

doi:10.12082/dqxxkx.2018.180083

摘要/Abstract

摘要：

随着城市化进程的加快,如何及时、精确地对城市环境的变化做出评价,进而制定出合理的发展方案,对城市可持续发展至关重要。本文综合利用卫星遥感获取的PM_2.5浓度数据、地表温度数据（Land Surface Temperature,LST）、植被指数数据（Normalized Difference Vegetation Index,NDVI）及城市用地辅助信息数据,基于综合评价指标,分析海上丝绸之路沿线12个超大城市地区2000-2013年环境质量的动态变化。研究结果表明,2000-2013年,海上丝绸之路沿线约75%的超大城市呈现出不同程度的环境恶化现象。12个超大城市用地环境恶化及逐步恶化面积占研究区域总面积的31.33%（4732.39 km²）。2000-2013年,城市扩张用地恶化和逐步恶化面积约占总扩张用地的29.48%（3765.83 km²）。平均地表温度的上升、植被覆盖度的急剧下降及PM_2.5浓度的增加均对海上丝绸之路沿线超大城市环境质量变化产生影响。其中,空气中PM_2.5浓度的大幅度增加是2000-2013年海上丝绸之路沿线超大城市扩张用地环境退化的主要原因。

关键词: 城市环境, 超大城市, 城市扩张, 海上丝绸之路, 多源遥感数据

Abstract:

With the rapid process of urbanization, it is very important for sustainable urban development that how to evaluate the changes of urban environmental quality in time and accurately, and thus make reasonable urban developmental plans. In this paper, the fine particulate matter (PM_2.5) concentration data, land surface temperature (LST) data, normalized difference vegetation index (NDVI) data and supplementary information data of urban land use obtained by satellite remote sensing were obtained and synthetically used to assess the urban environment changes in mega cities along the Maritime Silk Road. The dynamic changes of urban environmental quality of 12 mega cities along the Maritime Silk Road were analyzed based on the comprehensive evaluation index (CEI) from 2000 to 2013. The results showed that, from 2000 to 2013, approximately 75 percent of the mega cities along the Maritime Silk Road showed different degrees of environmental deterioration. The area of environmental deterioration and moderately environmental deterioration accounted for 31.33 percent (4732.39 km²) of the total urban areas in the 12 mega cities. And 29.48 percent (3765.83 km²) of the total expanded urban areas from 2000 to 2013 exhibited environmental degradation or moderately environmental degradation. The rise of average land surface temperature, the sharp decrease of vegetation coverage and the increase of the fine particulate matter concentration all had an impact on the urban environmental quality changes of the mega cities along the Maritime Silk Road. Among them, the significant increase of the fine particulate matter (PM_2.5) concentration in the air was one of the main manifestations for the environmental degradation of the expanded urban areas from 2000 to 2013 in mega cities along the Maritime Silk Road. These findings suggested that more attentions should be paid to urban environment issues to ensure sustainable urban development along the Maritime Silk Road.

Key words: urban environment, mega city, urban expansion, Maritime Silk Road, multi-source remote sensing data

冯素云, 张凯选, 鹿琳琳. “海上丝绸之路”超大城市环境变化遥感分析[J]. 地球信息科学学报, 2018, 20(5): 602-612.DOI:10.12082/dqxxkx.2018.180083

FENG Suyun,ZHANG Kaixuan,LU Linlin. Remote Sensing Analysis of Environmental Changes in Mega Cities along the Maritime Silk Road[J]. Journal of Geo-information Science, 2018, 20(5): 602-612.DOI:10.12082/dqxxkx.2018.180083

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城市	开罗	卡拉奇	德里	孟买	班加罗尔	加尔各答
2000年城市人口/千人	13 626	10 032	15 732	16 367	5567	13 058
2016年城市人口/千人	19 128	17 121	26 454	21 357	10 456	14 980
年增长率/%	2.1	3.3	3.2	1.7	3.9	0.9
城市	达卡	金奈	广州	深圳	马尼拉	雅加达
2000年城市人口/千人	10 285	6353	7330	6550	9962	8390
2016年城市人口/千人	18 237	10 163	13 070	10 828	13 131	10 483
年增长率/%	3.6	2.9	3.6	3.1	1.7	1.4

数据	数据信息	空间分辨率	时段	数据来源
PM_2.5浓度分布	MODIS+MISR+Sea WIFS传感器+GEOS-Chem传输模型	1 km	2000-2013	达尔豪西大学大气成分分析组
地表温度数据	MOD11A2	1 km	2000-2013	美国国家航天太空总署
归一化植被指数	SPOT/VGT 10-day composite	1 km	2000-2013	比利时弗拉芒技术研究院
全球建成区分布	Landsat	38 m	2000,2014	欧盟联合研究中心

	类型
	改善	逐步改善	未变	逐步恶化	恶化
分类依据	<u-1.5δ	u-1.5δ~u-0.5δ	u-0.5δ~u+0.5δ	u+0.5δ~u+1.5δ	>u+1.5δ
综合评价指标	<33.93	33.93~42.56	42.56~51.20	51.20~59.83	>59.83

城市	2000年城市用地/km²	扩增面积/km²	恶化		逐步恶化		未变		逐步改善		改善
城市	2000年城市用地/km²	扩增面积/km²	面积/km²	百分比/%	面积/km²	百分比/%	面积/km²	百分比/%	面积/km²	百分比/%	面积/km²	百分比/%
班加罗尔	235.26	368.57	27.53	4.56	361.27	59.83	196.11	32.48	18.92	3.13	0.00	0.00
开罗	228.48	1098.38	0.00	0.00	0.00	0.00	49.11	3.70	1225.70	92.38	52.05	3.92
金奈	44.56	254.85	0.00	0.00	5.23	1.75	184.26	61.54	57.58	19.23	52.34	17.48
德里	249.07	1361.00	0.00	0.00	0.00	0.00	171.73	10.67	1405.58	87.30	32.76	2.03
达卡	131.48	326.65	240.06	52.40	193.33	42.20	23.82	5.20	0.92	0.20	0.00	0.00
广州	710.99	2591.42	237.56	7.19	1804.73	54.65	1110.82	33.64	130.52	3.95	18.78	0.57
雅加达	148.56	2445.84	0.00	0.00	3.52	0.14	775.59	29.90	1565.27	60.33	250.02	9.63
卡拉奇	64.31	410.15	0.00	0.00	0.00	0.00	173.94	36.66	286.99	60.49	13.53	2.85
加尔各答	93.53	824.28	795.08	89.51	93.15	10.49	0.00	0.00	0.00	0.00	0.00	0.00
马尼拉	52.12	888.83	0.00	0.00	40.59	4.31	618.07	65.69	264.76	28.14	17.53	1.86
孟买	32.56	504.72	0.00	0.00	60.23	11.21	388.14	72.24	57.36	10.68	31.55	5.87
深圳	368.57	1698.49	30.92	1.50	839.19	40.60	954.03	46.15	199.64	9.66	43.28	2.09

	CEI	ΔPM_2.5	ΔLST	ΔVC
CEI	1
ΔPM_2.5	0.919^**	1
ΔLST	0.453^**	0.143^**	1
ΔVC	0.290^**	0.202^**	0.006^*	1