关中平原城市群植被覆盖的时空特征与影响因素

doi:10.12118/j.issn.1000-6060.2020.04.19

Abstract

Abstract: Vegetation is an important indicator of environmental changes in global and regional ecosystems,and it is also one of the resources that make an important contribution to human social activities. To study the response of vegetation coverage to natural and human factors in different parts of the Guanzhong Plain urban agglomeration in western China,we divided the region of interest into three vegetation areas for our research. We selected MODIS-NDVI remote-sensing data obtained during 2000-2017. Using trend analysis,exploratory spatial data analysis,and geodetector methods,we studied the evolution and distribution characteristics of vegetation cover during those 18 years from the perspectives of temporal evolution and spatial distribution. We quantitatively analyzed the main factors affecting vegetation coverage. We first processed remote-sensing data by such methods as projection conversion,splicing,and maximum-value synthesis and then applied batch image cropping using Python. The remote-sensing and meteorological data were categorized by applying statistical methods. From the processed data,we drew the following conclusions：（1） During the study period,vegetation coverage of the Guanzhong Plain urban agglomeration showed a significant upward trend. The average NDVI growth rate was 0.077 every 10 years,and the characteristics of periodic changes were obvious. Among them,the 2005-2007 and 2011-2013 periods increased significantly,and the maximum ascent rate reached 0.05 per year. （2） Our spatial data generally confirmed the distribution characterized as “high in the south and low in the north,” and vegetation coverage improved overall in the study area. The high-value areas are mainly distributed on the northern slope of the southern Qinling Mountains,which is more affected by climatic factors. The vegetation coverage is increasing slowly and has slightly improved. The low-value areas are concentrated on the edge of the Loess Plateau,and the vegetation coverage is obviously increasing there,whereas a small portion of the central part of the Guanzhong Plain showed slight to severe degradation,with Xi’an and its neighboring cities being the most typical. （3） Hot spots are mainly distributed in the Qinling Mountains and the central of the Guanzhong Plain,while cold spots are concentrated along the margins of the Loess Plateau,where vegetation coverage is mainly increasing. Hot-spot areas continue to increase,having reached a maximum of 45.07% in 2013,while the number of cold spots continues to decrease,having been reduced to 9.82% in 2017. The hot and cold spots are mainly distributed in the central plains and northern areas,which have changed from continuous to scattered distribution,and the total volume is continuously decreasing. （4） The most-prominent influences on vegetation coverage are natural factors,among which temperature and precipitation are dominant. The determinant q values are 0.955 and 0.931,respectively,the influence of temperature being greater than that of precipitation. The influence of human factors is important but not prominent; the determinant q value of the GDP factor reaches only 0.387. The conclusions of this paper could provide some theoretical basis to improve vegetation-coverage environment in the study area.

Key words: NDVI, trend analysis, ESDA, Geodetector, urban agglomeration of Guanzhong Plain

WANG Zhi-guo, BAI Yong-ping, CHE Lei, CHEN Zhi-jie, QIAO Fu-wei. Spatio-temporal characteristics and influencing factors of vegetation coverage in urban agglomeration of Guanzhong Plain[J].Arid Land Geography, 2020, 43(4): 1041-1050.

References

[1] SONG Xiaopeng,HANSEN M C,STEHMAN S V,et al.Global land change from 1982 to 2016[J]. Nature,2018,560,639–643.
[2] 何兴元,任春颖,陈琳,等. 森林生态系统遥感监测技术研究进展[J]. 地理科学,2018,38(7):997–1011.
[HE Xingyuan,REN Chunyin,CHEN Lin,et al.The progress of forest ecosystems monitoring with remote sensing techniques[J]. Scientia Geographica Sinica, 2018,38(7):997–1011.]
[3] 丁翔,白中科. 黄土区露天煤矿复垦土地植被覆盖度监测及影响因素[J]. 经济地理,2017,37(11):198–204.
[DING Xiang,BAI Zhongke.The calculation method of vegetation coverage and influencing factors in Antaibao open pit coal mine in loess area[J]. Economic Geography,2013,37(11):198–204.]
[4] 钱琛,陈海滨,侯现慧. 生态建设背景下陕西省植被覆盖时空变化及其影响因素研究[J]. 干旱区地理,2020,43(2):425–433.
[QIAN Chen, CHEN Haibin,HOU Xianhui.Temporal and spatial variation of vegetation cover and its influencing factors in Shaanxi Province in the context of ecological construction[J]. Arid Land Geography. 2020,43(2):425–433.]
[5] 刘斌,孙艳玲,王永财,等. 基于SPOT / NDVI华北地区植被变化动态监测与评价[J]. 干旱区资源与环境,2013,27(9):98–103.
[LIU Bin,SUN Yanling,WANG Yongcai,et al.Monitoring and assessment of vegetation variation in north China based on SPOT/NDVI[J]. Journal of Arid Land Resources and Environment,2013,27(9):98–103.]
[6] 白建军,白江涛,王磊,等. 2000—2010年陕北地区植被 NDVI时空变化及其与区域气候的关系[J]. 地理科学,2014,34(7):882–888.
[BAI Jianjun,BAI Jiangtao,WANG Lei,et al.Spatio-temporal change of vegetation NDVI and its relations with regional climate in northern Shaanxi Province in 2000–2010[J]. Scientia Geographica Sinica,2014,34(7):882–888.]
[7] LEVEAU L M,ISLA F I,BELLOCQ M I.Predicting the seasonal dynamics of bird communities along an urban-rural gradient using NDVI[J]. Landscape and Urban Planning,2018,177:103–113.
[8] WANG L,PAN Y,CAO Y,et al.Detecting early signs of environmental degradation in protected areas:An example of Jiuzhaigou Nature Reserve,China[J]. Ecological Indicators,2018,91:287–298.
[9] 苟娇娇,王飞,金凯,等. 黄土高原植被恢复引发区域气温下降[J]. 生态学报,2018,38(11):3970–3978.
[GOU Jiaojiao,WANG Fei,JIN Kai,et al.Cooling effect induced by vegetation restoration on the Loess Plateau[J]. Acta Ecologica Sinica,2018,38(11):3970–3978.]
[10] 周亮,车磊,周成虎. 中国城市绿色发展效率时空演变特征及影响因素[J]. 地理学报,2019,74(10):2027–2044.
[ZHOU Liang,CHE Lei,ZHOU Chenghu.Spatio-temporal evolution and influencing factors of urban green development efficiency in China[J]. Acta Geographica Sinica,2019,74(10):2027–2044.]
[11] 李学梅,任志远,张翀. 气候因子和人类活动对重庆市植被覆盖变化的影响分析[J]. 地理科学,2013,33(11):1390–1394.
[LI Xuemei,REN Zhiyuan,ZHANG Chong,Spatial-temporal variations of vegetation cover in Chongqing City (1999–2010):Impacts of climate factors and human activities[J]. Scientia Geographica Sinica,2013,33(11):1390–1394.]
[12] 赵丽红,王屏,欧阳勋志,等. 南昌市植被覆盖度时空演变及其对非气候因素的响应[J]. 生态学报,2016,36(12):3723–3733.
[ZHAO Lihong,WANG Pin,OUYANG Xunzhi,et al.An analysis of the spatio-temporal variation in fractional vegetation cover and its relationship with non-climate factors in Nanchang City,China[J]. Acta Ecologica Sinica,2016,36(12):3723–3733.]
[13] 赵鸿雁,陈英,周翼,等. 甘肃中东部植被生长季 NDVI时空变化及其对气候因子的响应[J].干旱区地理,2019,42(6):1427–1435.
[ZHAO Hongyan, CHEN Ying,ZHOU Yi,et al.Spatiotemporal variation of NDVI in vegetation growing season and its responses to climatic factors in mid and eastern Gansu Province from 2008 to 2016[J]. Arid Land Geography. 2019,42(6):1427–1435.]
[14] LI Xinhui,LEI Shaogang,CHENG Wei,et al.Spatio-temporal dynamics of vegetation in Jungar Banner of China during 2000–2017[J]. Journal of Arid Land, 2019, 11(6):837–854.
[15] 殷刚,孟现勇,王浩,等. 1982—2012 年中亚地区植被时空变化特征及其与气候变化的相关分析[J]. 生态学报, 2017, 37(9):3149–3163.
[YIN Gang,MENG Xianyong,WANG Hao,et al.Spatial-temporal variation of vegetation and its correlation with climate change in Central Asia during the period of 1982—2012[J]. Acta Ecologica Sinica,2017,37(9):3149–3163.]
[16] 刘宪锋,朱秀芳,潘耀忠,等. 1982—2012年中国植被覆盖时空变化特征[J]. 生态学报,2015,35(16):5331–5342.
[LIU Xianfeng,ZHU Xiufang,PAN Yaozhong,et al.Spatiotemporal changes in vegetation coverage in China during 1982—2012[J].Journal of Arid Environments,2015,35(16):5331–5342.]
[17] 张静静,郑辉,朱连奇,等. 豫西山地植被NDVI及其气候响应的多维变化[J]. 地理研究,2017,36(4):765–778.
[ZHANG Jingjing, ZHENG Hui,ZHU Lianqi,et al.Multi-dimensional changes of vegetation NDVI and its response to climate in Western Henan Mountains[J].Geographical Research,2017,36(4):765–778.]
[18] 刘旻霞,赵瑞东,邵鹏,等. 近15 a黄土高原植被覆盖时空变化及驱动力分析[J]. 干旱区地理,2018,41(1):99–108.
[LIU Minxia, ZHAO Ruidong, SHAO Peng, et al.Temporal and spatial variation of vegetation coverage and its driving forces in the Loess Plateau from 2001 to 2015[J]. Arid Land Geography. 2018,41(1):99–108.]
[19] 韩飞飞,闫俊杰,郭斌. 阿勒泰地区植被覆盖度及ET对气温变化的响应[J]. 干旱区地理,2019,42(6):1436–1444.
[HAN Feifei,YAN Junjie,GUO Bin.Response of vegetation cover and ET to temperature variation in Altay Prefecture[J]. Arid Land Geography. 2019,42(6):1436–1444.]
[20] 李建飞,李小兵,周义. 2000—2015年乌兰察布市生长季NDVI时空变化及其影响因素[J]. 干旱区研究,2019,36(5):1238–1249.
[LI Jianfei,LI Xiaobing,ZHOU Yi.Spatiotemporal variation of NDVI and its affecting factors in Ulanqab City in growing season from 2000 to 2015[J]. Arid Zone Research, 2019,36(5):1238–1249.]
[21] 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.
[LI Zhuo, SUN Ranhao,ZHANG Jichao,et al.Temporal-spatial analysis of vegetation coverage dynamics in Beijing-Tianjin-Hebei metropolitan regions[J]. Journal of Arid Environments,2017,37(22):7418–7426.]
[22] 张清雨,赵东升,吴绍洪,等. 基于生态分区的内蒙古地区植被覆盖变化及其影响因素研究[J]. 地理科学,2013,33(5):594–601.
[ZHANG Qingyu,ZHAO Dongsheng,WU Shaohong,et al.Research on vegetation changes and influence factors based on eco-geographical regions of Inner Mongolia[J]. Scientia Geographica Sinica,2013,33(5):594–601.]
[23] 刘斌,孙艳玲,王中良,等. 华北地区植被覆盖变化及其影响因子的相对作用分析[J]. 自然资源学报,2015,(1):12–23.
[LIU Bin,SUN Yanling,WANG Zhongliang,et al.Analysis of the vegetation cover change and the relative role of its influencing factors in north China[J]. Journal of Natural Resources, 2015,(1):12–23.]
[24] CHANG Xu,KATCCHOVA A L.Predicting soybean yield with NDVI using a flexible fourier transform model[J]. Journal of Agricultural and Applied Economics,2019, 51(3):402–416.
[25] 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 Jungang,YAN Qingwu,XIONG Jibing,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.]
[26] 岳辉,刘英. 近15 a陕西省植被时空变化与影响因素分析[J]. 干旱区地理,2019,42(2):314–323.
[YUE Hui, LIU Ying.Vegetation spatiotemporal variation and its driving factors of Shaanxi Province in recent 15 years[J]. Arid Land Geography, 2019,42(2):314–323.]
[27] 朱军,李益敏,余艳红. 基于GIS的高原湖泊流域生态安全格局构建及优化研究——以星云湖流域为例[J]. 长江流域资源与环境,2017,26(8):1237–1250.
[ZHU Jun,LI Yimin,YU Yanhong.Study of construction and optimization of ecological security pattern of lake basin in plateau based on GIS:A case study of Xingyun Lake Basin[J]. Resources and Environment in the Yangtze Basin,2017,26(8):1237–1250.]
[28] 郑德凤,郝帅,孙才志. 基于DEA-ESDA的农业生态效率评价及时空分异研究[J]. 地理科学,2018,38(3):419–427.
[ZHENG Defeng,HAO Shuai,SUN Caizhi.Evaluation of agricultural ecological efficiency and its spatial-temporal differentiation based on DEA-ESDA[J]. Scientia Geographica Sinica,2018,38(3):419–427.]
[29] 胡碧峰,王佳昱,傅婷婷,等. 空间分析在土壤重金属污染研究中的应用[J]. 土壤通报,2017,48(4):1014–1024.
[HU Bifeng,WNAG Jiayu,FU Tingting,et al.Application of spatial analysis on soil heavy metal contamination:A review[J]. Chinese Journal of Soil Science,2017,48(4):1014–1024.]
[30] 周亮,周成虎,杨帆,等. 2000—2011年中国PM_2.5时空演化特征及驱动因素解析[J]. 地理学报,2017,72(11):2079–2092.
[ZHOU Liang,ZHOU Chenghu,YANG Fan,et al.Spatio-temporal evolution and the influencing factors of PM_2.5 in China between 2000 and 2011[J]. Acta Geographica Sinica,2017,72(11):2079–2092.]
[31] 汪凡,白永平,周亮,等. 中国高校科技创新能力时空格局及影响因素[J]. 经济地理,2017,37(12):49–56.
[WANG Fan,BAI Yongping,ZHOU Liang,et al.Spatio-temporal pattern and influencing factors of scientific and technological innovation capability of universities in China[J]. Economic Geography,2017,37(12):49–56.]
[32] 丁悦,蔡建明,任周鹏,等. 基于地理探测器的国家级经济技术开发区经济增长率空间分异及影响因素[J]. 地理科学进展,2014,33(5):657–666.
[DING Yue,CAI Jianming,REN Zhou- peng,et al. Spatial disparities of economic growth rate of China’s National-level ETDZs and their determinants based on geographical detector analysis[J]. Progress in Geography,2014,33(5):657–666.]
[33] 徐秋蓉,郑新奇. 一种基于地理探测器的城镇扩展影响机理分析法[J]. 测绘学报,2015,44(b12):96–101.
[XU Qiurong,ZHENG Xinqi.Analysis of influencing mechanism of urban geographical detector[J]. Acta Geodaetica et Cartographica Sinica,2015,44(b12):96–101.]
[34] 刘彦随,杨忍. 中国县域城镇化的空间特征与形成机理[J]. 地理学报,2012,67(8):1011–1020.
[ LIU Yansui,YANG Ren.The spatial characteristics and formation mechanism of the county urbanization in China[J]. Acta Geographica Sinica,2012,67(8):1011–1020.]

Spatio-temporal characteristics and influencing factors of vegetation coverage in urban agglomeration of Guanzhong Plain

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0

[1]	YANG Yu, SONG Futie, ZHANG Jie. Spatial structure characteristics and influencing factors of financial network of China based on geodetectors [J]. Arid Land Geography, 2023, 46(9): 1524-1535.
[2]	KONG Deming, HAO Lisha, XIA Siyou, LI Hongbo. Food security in the argo-pastoral ecotone of northern China from the perspective of grain yield [J]. Arid Land Geography, 2023, 46(5): 782-792.
[3]	LUO Jiayan, ZHANG Jing, XU Mengran, MO Yu, TONG Liga. Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land [J]. Arid Land Geography, 2023, 46(4): 614-624.
[4]	YANG Yuhuan,HE Jianxiong,ZHANG Xinhong,RUI Yang. Spatial differentiation characteristics and influencing texture of the coupling coordinated development of agro-culture-tourism in China [J]. Arid Land Geography, 2023, 46(3): 448-459.
[5]	DENG Tiantian, GENG Guangpo, YANG Rui, ZHANG Bao. Temporal and spatial variation characteristics of high temperature and heat wave in the Weihe River Basin from 1980 to 2020 [J]. Arid Land Geography, 2023, 46(2): 211-221.
[6]	YE Wenli,YANG Xinjun,WU Kongsen,WANG Yin. Spatio-temporal characteristics and influencing factors of social-ecological system resilience in the Loess Plateau [J]. Arid Land Geography, 2022, 45(3): 912-924.
[7]	SUN Lirong,ZHOU Dongmei,CEN Guozhang,MA Jing,DANG Rui,NI Fan,ZHANG Jun. Landscape ecological risk assessment and driving factors of the Shule River Basin based on the geographic detector model [J]. Arid Land Geography, 2021, 44(5): 1384-1395.
[8]	WU Guodong,XUE Heru,LIU Tingxi. Change characteristics and trends of precipitation and average temperature in the Xilinhe River Basin from 1961 to 2016 [J]. Arid Land Geography, 2021, 44(3): 769-777.
[9]	WANG Bo,YANG Taibao. Value evaluation and driving force analysis of ecosystem services in Yinchuan City from 1980 to 2018 [J]. Arid Land Geography, 2021, 44(2): 552-564.
[10]	ZHAO Haili,WANG Qiwen,ZHU Lixiang,LI Xiaoqin,TIAN Haoyu. Spatial-temporal evolution and influencing factors of health resources in underdeveloped areas based on geodetectors [J]. Arid Land Geography, 2021, 44(2): 594-603.
[11]	ZHANG Chong,BAI Ziyi,LI Xuemei,RAN Qiqi,WEI Zhenfeng,LEI Tianwang,WANG Na. Spatio-temporal evolution and attribution analysis of human effects of vegetation cover on the Loess Plateau from 2001 to 2018 [J]. Arid Land Geography, 2021, 44(1): 188-196.
[12]	WANG Xiao-meng, YAN Jun-ping, LI Shuang-shuang, YAN De-li, WAN Jia. Spatiotemporal relationship between evaporation and temperature in the south and north of Qinling Mountains and its influential factors [J]. Arid Land Geography, 2020, 43(6): 1435-1445.
[13]	SUN Guo-jun, LI Wei-hong, ZHU Cheng-gang, CUI dong, LIU Hai-jun. Spatial-temporal characteristics of vegetation cover in Ili River Valley from 2000 to 2015 [J]. Arid Land Geography, 2020, 43(6): 1551-1558.
[14]	WANG Hua, YANG Qian-peng, TIAN Yun-jie, GUO Shan-chuan, TANG Peng-fei. Vegetation coverage monitoring in the Central Asian countries using multi-temporal Landsat images [J]. Arid Land Geography, 2020, 43(4): 1023-1032.
[15]	ZHAO Jun-hong, ZHOU Hua-rong, LU Ya-yan, SUN Qing-xiang. Temporal-spatial characteristics and influencing factors of the vegetation net primary production in the National Nature Reserve of Populus euphratica in Tarim from 2000 to 2015 [J]. Arid Land Geography, 2020, 43(1): 190-200.