京津冀地区植被时空动态及定量归因

doi:10.12082/dqxxkx.2019.180578

摘要/Abstract

摘要：

作为气候变化的敏感指示器,植被的物候、生长、空间分布格局等特征及其动态变化主要取决于气候环境中的水热条件,因此在气候变化背景下,气候-植被关系成为了全球变化研究的前沿和热点问题。本文综合平均温度、降水、水汽压、湿度、日照时数、SPEI等气候因子,坡度、坡向海拔等地形因子及人为活动因子,应用地理探测器方法针对2006-2015年京津冀地区不同季节NDVI、不同地貌类型区、不同植被类型区生长季NDVI的定量归因研究,揭示了过去10年间植被时空分布格局,及植被对气候、非气候因素响应的季节差异与区域差异,以期为生态工程的建设与修复提供参考意义。趋势分析表明：①2006-2015年京津冀地区NDVI呈现增加趋势,但存在显著的空间差异,如山地生长季NDVI的增长速率大于平原、台地、丘陵等地;②基于地理探测器的定量归因结果表明,降水是年尺度上NDVI空间分布的主导因子（解释力39.4%）,土地利用与降水的交互作用对NDVI的影响最为明显（q=58.2%）;③NDVI对气候因子的响应存在季节性及区域性差异,水汽压是春季NDVI空间分布的主导因子,湿度是夏、秋两季的主导因子,土地利用是冬季的主导因子;④影响因子对生长季NDVI的解释力因不同地貌类型区、不同植被类型区而差异显著。

关键词: NDVI, 空间分布, 空间异质性, 定量归因, 地理探测器, 京津冀地区

Abstract:

Vegetation is a sensitive indicator of global climatic changes, and hydrothermal conditions are the main abiotic factors that determine the phenology, spatial pattern, and dynamics of vegetation. Thus, against the background of a changing climate, the climate-vegetation relationship is a hot topic in current global change research. Using geodetector, this study integrated climatic factors (e.g., average temperature, precipitation, water vapor pressure, humidity, sunshine hours, standardized precipitation evapotranspiration index), topographic factors (e.g., slope and elevation), and anthropogenic factors to determine the dominant factors that influenced the normalized difference vegetation index (NDVI) in the Beijing-Tianjin-Hebei region from 2006 to 2015. Different seasons, geomorphological types, and vegetation types were considered during the quantitative attribution analysis. This study revealed the temporal and spatial pattern of vegetation, and the response of vegetation to climate and non-climate factors over the past 10 years, and provided a reference for the construction and restoration of ecological engineering. Trend analysis showed that the NDVI increased during this period, albeit with differences on different spatial scales. In montane regions, the NDVI increased more rapidly than in plains, terraces, and hills. In different vegetation-covered areas, the NDVI increased most rapidly in broadleaf forest, followed by shrubland and coniferous forest. Based on the results of the quantitative distribution analysis, at the temporal scale of one year, precipitation was the dominant factor driving NDVI and explained 39.4% of the spatial distribution, while the interaction of rainfall and land use was the dominant interaction factor, with a q value of 0.582. We observed seasonal and regional differences in the response of NDVI to climatic factors. In the four seasons, vapour pressure was the dominant factor for the spatial distribution of NDVI; humidity is the dominant factor in summer and autumn; and in winter, land use was the dominant factor for NDVI distribution. The explanatory power of the influencing factors on NDVI in the growing season differed in diverse geomorphological types. In montane areas, with increasing elevation, the q value of average temperature decreased. The explanatory power of impacting factors on NDVI of the growing season was different among diverse vegetation types. For different vegetation types, the explanatory power of precipitation on the spatial distribution of NDVI in the growing season was greater than that of mean temperature, with the q value ranked as following grassland > cultivated vegetation > shrubland > broadleaf forest >coniferous forest. In coniferous forest distributed areas, the explanatory power of single factors was insignificant; however, the interaction between two factors can greatly enhance the q value, and the interaction between moisture factors and topographic factors was the dominant factor.

Key words: spatial distribution, NDVI, spatial heterogeneity, quantitative attribution, geodetector, Beijing-Tianjin-Hebei region

阎世杰, 王欢, 焦珂伟. 京津冀地区植被时空动态及定量归因[J]. 地球信息科学学报, 2019, 21(5): 767-780.

Shijie YAN, Huan WANG, Kewei JIAO. Spatiotemporal Dynamics of NDVI in the Beijing-Tianjin-Hebei Region based on MODIS Data and Quantitative Attribution[J]. Journal of Geo-information Science, 2019, 21(5): 767-780.

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参考文献 49

[1]	朴世龙,方精云.1982-1999年我国陆地植被活动对气候变化响应的季节差异[J].地理学报,2003,58(1):119-125.
	[ Piao S L, Fang J Y.Seasonal changes in vegetation activity in response to climate changes in China between 1982 and 1999[J]. Acta Geographica Science, 2003,58(1):119-125. ]
[2]	王永财,孙艳玲,王中良. 1998-2011年海河流域植被覆盖变化及气候因子驱动分析[J].资源科学,2014,36(3):594-602.
	[ Wang Y C, Sun Y L, Wang Z L.Spatial-temperal change in vegetation cover and climate factor drivers of variation in the Haihe River Basin in 1998-2011[J]. Resources Science, 2014,36(3):594-602. ]
[3]	陈效逑,王恒.1982-2003年内蒙古植被带和植被覆盖度的时空变化[J].地理学报,2009,64(1):84-94. doi: 10.3321/j.issn:0375-5444.2009.01.009
	[ Chen X Q, Wang H.Spatial and temporal variation belts and vegetation cover degrees in inner Mongolia from 1982 to 2003[J]. Acta Geographica Science, 2009,64(1):84-94. ] doi: 10.3321/j.issn:0375-5444.2009.01.009
[4]	Piao S, Ciais P, Friedlingstein P, et al.Net carbon dioxide losses of northern ecosystems in response to autumn warming[J]. Nature, 2008,451(7174):49-52.
[5]	Penuelas J, Rutishauser T, Filella I.Phenology feedbacks on climate change[J]. Science,2009,324(5929):887-888.
[6]	Richardson A D, Black T A, Ciais P, et al.Influence of spring and autumn phenological transitions on forest ecosystem productivity[J]. Philosophical Transactions Biological Sciences,2010,365(1555):3227.
[7]	贾宝全. 基于TM卫星影像数据的北京市植被变化及其原因分析[J].生态学报,2013,33(5):1654-1666. doi: 10.5846/stxb201208251199
	[ Jia B Q.Driving factor analysis on the vegetation changes derived from the Landsat TM images in Beijing[J]. Acta Ecologica Sinica, 2013,33(5):1654-1666. ] doi: 10.5846/stxb201208251199
[8]	杜加强,舒俭民,张林波,等.黄河上游不同干湿气候区植被对气候变化的响应[J].植物生态学报,2011,35(11):1192-1201. doi: 10.3724/SP.J.1258.2011.01192
	[ Du J Q, Shu J M, Zhang L B, et al.Responses of vegetation to climate change in the headwaters of China's Yellow River Basin based on zoning of dry and wet climate[J]. Chinese Journal of Plant Ecology, 2011,35(11):1192-1201. ] doi: 10.3724/SP.J.1258.2011.01192
[9]	杨思遥,孟丹,李小娟,等.华北地区2001-2014年植被变化对SPEI气象干旱指数多尺度的响应[J].生态学报,2018,38(3):1028-1039.
	[ Yang S Y, Meng D, Li X J, et al.Multi-scale response of vegetation changes relative to the SPEI meteorological drought in North China in 2001-2014[J]. Acta Ecologica Sinica, 2018,38(3):1028-1039. ]
[10]	Schwartz M D.Green-wave phenology[J]. Nature,1998,394(6696):839-840.
[11]	Menzel A, Fabian P.Growing season extended in Europe[J]. Nature,1999,397(6721): 659.
[12]	Arneth A.Climate science: Uncertain future for vegetation cover[J]. Nature,2015,524(7563): 44-45. doi: 10.1038/524044a
[13]	成方妍,刘世梁,尹艺洁,等.基于MODIS NDVI的广西沿海植被动态及其主要驱动因素[J].生态学报,2017,37(3):788-797.
	[ Cheng F Y, Liu S L, Yin Y J, et al.The dynamics and main driving factors of coastal vegetation in Guangxi based on MODIS NDVI[J]. Acta Ecologica Sinica, 2017,37(3):788-797. ]
[14]	刘军会,高吉喜,王文杰.青藏高原植被覆盖变化及其与气候变化的关系[J].山地学报,2013,31(2):234-242.
	[ Liu J H, Gao J X, Wang W J.Variations of vegetation coverage and its relations to global climate changes on the Tibetan Plateau during 1981—2005[J]. Journal of Mountain Science, 2013,31(2):234-242. ]
[15]	Zhang Y, Song C, Band L E, et al.Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?[J]. Remote Sensing of Environment, 2017,191:145-155.
[16]	Zhu Z, Piao S, Myneni R B, et al.Greening of the Earth and its drivers[J]. Nature Climate Change,2016,6(8):791-795. doi: 10.1016/j.envpol.2017.08.014
[17]	京津冀协同发展领导小组.京津冀协同发展规划纲要[R].北京:中共中央政治局,2015.
	[ Leading group for coordinated development of the Beijing-Tianjin-Hebei region. Outline of the plan for coordinated development of the Beijing-Tianjin-Hebei region[R]. Beijing: Political Bureau of the Central Committee of the Communist Party of China, 2015. ]
[18]	王静,周伟奇,许开鹏,等.京津冀地区城市化对植被覆盖度及景观格局的影响[J].生态学报,2017,37(21):7019-7029.
	[ Wang J, Zhou W Q, Xu K P, et al.Spatiotemporal pattern of vegetation cover and its relationship with urbanization in Beijing-Tianjin-Hebei megaregion from 2000 to 2010[J]. Acta Ecologica Sinica, 2017,37(21):7019-7029. ]
[19]	李卓,孙然好,张继超,等.京津冀城市群地区植被覆盖动态变化时空分析[J].生态学报,2017,37(22):7418-7426. doi: 10.5846/stxb201609231919
	[ Li Z, Sun R H, Zhang J C, et al.Temporal-spatial analysis of vegetation coverage dynamics in Beijing-Tianjin-Hebei metropolitan regions[J]. Acta Ecologica Sinica, 2017,37(22):7418-7426. ] doi: 10.5846/stxb201609231919
[20]	孟丹,李小娟,宫辉力,等.京津冀地区NDVI变化及气候因子驱动分析[J]. 地球信息科学学报,2015,17(8):1001-1007. doi: 10.3724/SP.J.1047.2015.01001
	[ Meng D, Li X J, Gong H L, et al.Analysis of spatial-temporal change of NDVI and its climatic driving factors in Beijing-Tianjin-Hebei metropolis circle from 2001 to 2013[J]. Journal of Geo-Information Science, 2015,17(8):1001-1007. ] doi: 10.3724/SP.J.1047.2015.01001
[21]	晏利斌,刘晓东.1982-2006年京津冀地区植被时空变化及其与降水和地面气温的联系[J].生态环境学报,2011,20(2):226-232.
	[ Yan L B, Liu X D.Spatial-temporal changes in vegetation cover and their relationships with precipitation and surface air temperature over Beijing-Tianjin-Hebei region from 1982-2006[J]. Ecology and Environmental Sciences, 2011,20(2):226-232. ]
[22]	韦振锋,任志远,张翀,等.西北地区植被覆盖变化及其与降水和气温的相关性[J].水土保持通报,2014,34(3):283-289.
	[ Wei Z F, Ren Z Y, Zhang C, et al.Changes of vegetation cover and its correlation with precipitation and temperature in Northwest China[J]. Bulletin of Soil and Water Conservation, 2014,34(3):283-289. ]
[23]	张琪,袁秀亮,陈曦,等. 1982-2012年中亚植被变化及其对气候变化的响应[J].植物生态学报,2016,40(1):13-23. doi: 10.17521/cjpe.2015.0236
	[ Zhang Q, Yuan X L, Chen X, et al.Vegetation change and its response to climate change in Central Asia from 1982 to 2012[J]. Chinese Journal of Plant Ecology, 2016,40(1):13-23. ] doi: 10.17521/cjpe.2015.0236
[24]	王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134.
	[ Wang J F, Xu C D.Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017,72(1):116-134. ]
[25]	焦珂伟,高江波,吴绍洪,等.植被活动对气候变化的响应过程研究进展[J].生态学报,2018,38(6):2229-2238.
	[ Jiao K W, Gao J B, Wu S H et al.Research progress on the response processes of vegetation activity to climate change[J]. Acta Ecologica Sinica, 2018,38(6):2229-2238. ]
[26]	Wang J F, Li X H, Christakos G, et al.Geographical detectors-based health risk assessment and its application in the neural tube defects study of the Heshun region, China[J]. International Journal of Geographical Information Science,2010,24(1):107-127.
[27]	韩冬,乔家君,马玉玲.基于空间界面视角的新时期乡村性空间分异机理——以河南省巩义市为例[J].地理科学进展,2018,37(5):655-666.
	[ Han D, Qiao J J, Ma Y L.Rurality spatial differentiation mechanism in the new era based on the perspective of spatial interface: A case study of Gongyi City, Henan Province[J]. Progress in Geography, 2018,37(5):655-666. ]
[28]	谢帅,刘士彬,段建波,等. OSDS注册用户空间分布特征及影响因素分析[J].地球信息科学学报,2016,18(10):1332-1340. doi: 10.3724/SP.J.1047.2016.01332
	[ Xie S, Liu S B, Duan J B, et al.Spatial distribution characteristics of OSDS registered users and its influencing factors[J]. Journal of Geo-informationScience, 2016,18(10):1332-1340. ] doi: 10.3724/SP.J.1047.2016.01332
[29]	通拉嘎,徐新良,付颖,等.地理环境因子对螺情影响的探测分析[J].地理科学进展,2014,33(5):625-635. doi: 10.11820/dlkxjz.2014.05.004
	[ Tong L G, Xu X L, Fu Y, et al.Impact of environmental factors on snail distribution using geographical detector model[J]. Progress in Geography, 2014,33(5):625-635. ] doi: 10.11820/dlkxjz.2014.05.004
[30]	熊俊楠,赵云亮,程维明,等.四川省山洪灾害时空分布规律及其影响因素研究[J].地球信息科学学报,2018,20(10):1443-1456.
	[ Xiong J N, Zhao Y L, Cheng W M, et al . Temporal-spatial distribution and the influencing factors of mountain-flood disasters in Sichuan Province[J].Journal of Geo-information Science, 2018,20(10):1443-1456. ]
[31]	Wang J F, Xu C D, Tong S L, et al.Spatial dynamic patterns of hand-foot-mouth disease in the People's Republic of China[J]. Geospat Health, 2013,7(2):381-390.
[32]	李媛媛,徐成东,肖革新,等.京津唐地区细菌性痢疾社会经济影响时空分析[J].地球信息科学学报,2016,18(12):1615-1623.
	[ Li Y Y, Xu C D, Xiao G X, et al.Spatial-temporal analysis of social-economic factors of bacillary dysentery in Beijing-Tianjin-Tangshan,China[J]. Journal of Geo-information Science, 2016,18(12):1615-1623. ]
[33]	Zhou C, Chen J, Wang S.Examining the effects of socioeconomic development on fine particulate matter (PM2.5) in China's cities using spatial regression and the geographical detector technique[J]. Science of the Total Environment, 2017,619:436-445.
[34]	肖建勇,王世杰,白晓永,等.喀斯特关键带植被时空变化及其驱动因素[J].生态学报,2018,38(24):8799-8812.
	[ Xiao J Y, Wang S J, Bai X Y, et al.Determinants and spatial-temporal evolution of vegetation coverage in the karst critical zone of South China[J]. Acta Ecologica Sinica, 2018,38(24):8799-8812. ]
[35]	李俊刚,闫庆武,熊集兵,等.贵州省煤矿区植被指数变化及其影响因子分析[J].生态与农村环境学报,2016,32(3):374-378.
	[ Li J G, Yan Q W, Xiong J B, et al.Variation of vegetation index in coal mining areas in Guizhou province and its affecting factors[J]. Journal of Ecology and Rural Environment, 2016,32(3):374-378. ]
[36]	何腾飞,王秀兰,宋亚男.基于高光谱遥感的京津冀地区植被分布规律及影响因素分析[J].林业调查规划,2014,39(5):15-19. doi: 10.3969/j.issn.1671-3168.2014.05.004
	[ He T F, Wang X L, Song Y N.Vegetation distributional pattern and influence factors analysis in Beijing-Tianjin-Hebei area based on hyperspectral remote sensing[J]. Forest Inventory and Planning, 2014,39(5):15-19. ] doi: 10.3969/j.issn.1671-3168.2014.05.004
[37]	刘志红, Li L T, Tim R M, 等.专用气候数据空间插值软件ANUSPLIN及其应用[J].气象,2008,34(2):92-100.
	[ Liu Z H, Li L T, Tim R M, et al.Introduction of the professional interpolation software for meteorology data: Ausplin[J]. Meteorolgical Monthly, 2008,34(2):92-100. ]
[38]	Piao S, Fang J, Zhou L, et al.Variations in satellite-derived phenology in China's temperate vegetation[J]. Global Change Biology, 2006,12(4):672-685.
[39]	Chen X, Hu B, Yu R.Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China[J]. Global Change Biology, 2005,11(7):1118-1130.
[40]	王宏,李晓兵,李霞,等.基于NOAA NDVI和MSAVI研究中国北方植被生长季变化[J].生态学报,2015,27(2):504-515.
	[ Wang H, Li X B, Li X, et al.The variability of vegetation growing season in the Northern China based on NOAA NDVI and MSAVI from 1982 to 1999[J]. Acta Ecologica Sinica, 2007,27(2):504-515. ]
[41]	周成虎,程维明,钱金凯,等.中国陆地1:100万数字地貌分类体系研究[J].地球信息科学学报,2009,11(6):707-724. doi: 10.3969/j.issn.1560-8999.2009.06.006
	[ Zhou C H, Cheng W M, Qian J K, et al.Research on the classification system of digital land geomorphology of 1∶1000000 in China[J]. Journal of Geo-information Science, 2009,11(6):707-724. ] doi: 10.3969/j.issn.1560-8999.2009.06.006
[42]	Beguería S, Vicente-Serrano S M, Reig F, et al. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring[J]. International Journal of Climatology, 2014,34(10):3001-3023.
[43]	陈亮,陈世俭,蔡晓斌,等.基于时序NDVI的三峡库区植被覆盖时空变化特征分析[J].华中师范大学学报(自然科学版), 2017(3):407-415.
	[ Chen L, Chen S J, Cai X B, et al.Analysis on spatial-temporal variation characteristics of vegetation cover in the Three Gorges Reservoir Area based on time series NDVI data[J]. Journal of Central China Normal University, 2017(3):407-415. ]
[44]	毕硕本,计晗,陈昌春,等.地理探测器在史前聚落人地关系研究中的应用与分析[J]. 地理科学进展,2005,34(1):118-127.
	[ Bi S B, Ji H, Chen C C, et al.Application of geographical detector in human-environment relationship study of prehistoric settlements[J]. Progressin Geography, 2005,34(1):118-127. ]
[45]	Liu Y S, Li J T.Geographic detection and optimizing decision of the differentiation mechanism of rural poverty in China[J]. Acta Geographica Sinica, 2017,1(1):161-173.
[46]	Gao J B, Wang H.Temporal analysis on quantitative attribution of Karst soil erosion: A case study of a peak-cluster depression basin in Southwest China[J]. Catena, 2019,172:269-377.
[47]	冯敏,孙艳玲,刘斌,等.华北地区植被NDVI与不同气候指标的相关分析[J]. 水土保持通报,2014,34(1):246-251.
	[ Feng M, Sun Y L, Liu B, et al.Correlation between NDVI and different climate indices in North China[J]. Bulletin of Soil and Water Conservation, 2014,34(1):246-251. ]
[48]	张学珍,戴君虎,葛全胜.1982-2006年中国东部春季植被变化的区域差异[J].地理学报,2012,67(1):53-61.
	[ Zhang X Z, Dai J H, Ge Q S.Spatial differences of changes in spring vegetation activitiesacross Eastern China during 1982-2006[J]. Acta Geographica Sinica, 2012,67(1):53-61. ]
[49]	戈峰. 现代生态学,第2版[M].北京:科学出版社,2008:41-41.
	[ Ge F.Modern Ecology, the second version[M]. Beijing: Science Press, 2008:41-41. ]

需要的数据	数据来源	计算方法
MODIS中国NDVI月合成数据(2006.01-2015.12)	中国科学院计算机网络信息中心国际科学数据镜像网站(http://www.gscloud.cn)
气象数据(降水、平均温度、最高温度、最低温度、风速、日照时数、湿度和水汽压)	国家气象信息中心(http://data.cma.cn)	其中水汽压数据由湿度数据计算得到
标准化降水蒸散指数(SPEI)	由常规气象数据计算得到	SPEI采用Beguería 等^[42]开发的R语言扩展包计算(http://cran.r-project.org/web/packages/SPEI)
30m、1000mDEM数据	中国科学院资源环境科学数据中心(http://www.resdc.cn)
植被类型数据(1:100万)^[41]	中国科学院资源环境科学数据中心(http://www.resdc.cn)
地貌类型数据(1:100万)	中国科学院资源环境科学数据中心(http://www.resdc.cn)
土地利用数据(2005, 2010, 2015)	中国科学院资源环境科学数据中心(http://www.resdc.cn)

判断依据	交互作用类型
q(X1∩X2)<Min(q(X1), q(X2))	非线性减弱
Min(q(X1), q(X2))<q(X1∩X2)<Max(q(X1), q(X2))	单因子非线性减弱
q(X1∩X2)>Max(q(X1), q(X2))	双因子增强
q(X1∩X2)=q(X1)+q(X2)	独立
q(X1∩X2)>q(X1)+q(X2)	非线性增强

	春	夏	秋	冬	年
主导交互作用1	降水∩水汽压	湿度∩土地利用	土地利用∩水汽压	土地利用∩平均温度	土地利用∩降水
q值	0.565	0.634	0.539	0.434	0.582
主导交互作用2	降水∩湿度	湿度∩水汽压	土地利用∩湿度	土地利用∩海拔	降水∩海拔
q值	0.505	0.631	0.535	0.404	0.543
主导交互作用3	土地利用∩水汽压	湿度∩平均温度	土地利用∩海拔	土地利用∩水汽压	降水∩水汽压
q值	0.472	0.627	0.531	0.395	0.532

	平原	台地	丘陵	小起伏山地	中起伏山地	大起伏山地
均值	0.671	0.550	0.591	0.691	0.733	0.750
变率/a	0.0052	0.0069	0.0074	0.0089	0.0087	0.0081
变率显著性	显著	显著	极显著	极显著	极显著	极显著

	平原	台地	丘陵	小起伏山地	中起伏山地	大起伏山地
主导交互作用1	日照时数∩水汽压	湿度∩日照时数	平均温度∩湿度	降水∩土地利用	湿度∩土地利用	土地利用∩降水
q值	0.586	0.755	0.760	0.634	0.587	0.570
主导交互作用2	日照时数∩湿度	湿度∩干旱指数	降水∩土地利用	湿度∩土地利用	降水∩土地利用	土地利用∩湿度
q值	0.575	0.744	0.758	0.606	0.579	0.513
主导交互作用3	降水∩湿度	湿度∩土地利用	日照时数∩湿度	湿度∩平均温度	湿度∩日照时数	降水∩海拔
q值	0.539	0.743	0.750	0.596	0.502	0.485