辽宁省植被生长季NDVI对气候因子的响应

doi:10.11983/CBB17010

摘要/Abstract

摘要： 基于2000-2010年辽宁省内的37个气象站及周边5个气象站的基础数据, 结合MODIS NDVI的遥感影像资料, 运用趋势分析、相关分析和空间分析等方法研究植被生长与气候的关系, 探讨不同气候因子对植被生长的影响与主导作用。结果表明: (1) 辽宁省植被在研究时段内的7-8月生长最为旺盛, 生长季植被NDVI呈显著升高趋势, 2007年后维持在0.73- 0.74之间; (2) 在研究时段内, 整个生长季植被NDVI与降水量和日照时数主要呈正相关, 与气温主要呈负相关, 且在6-8月相关性较为显著, 植被生长对气温的变化最敏感, 对日照的响应最缓慢; (3) 5月辽宁省东部植被生长的主要气候影响因子为气温和日照, 西部为降水, 6-8月东部植被主要气候影响因子则转为降水和日照, 9月再度转为气温和日照; (4) 气温和日照对植被影响的滞后时间由东北向西南逐渐延长, 降水则与之相反。

关键词: NDVI, 气候因子, 响应分析, 滞后期

Abstract: Daily data were obtained from 37 meteorological stations in Liaoning province and 5 meteorological stations in an adjacent area, combined with MODIS NDVI data, during 2000-2010. Vegetation growth response to climate change was analyzed by trend, correlation and spatial analyses to investigate the leading influence of different climate factors on vegetation growth. During the study period, the vegetation of Liaoning province was the most vigorous in July and August. NDVI was significantly increased in the vegetative season and remained between 0.73 and 0.74 after 2007. NDVI and temperature were negatively correlated, especially from June to August; NDVI and precipitation and sunshine hours mainly showed a positive correlation. Vegetation growth was most sensitive to changes of temperature, and the response to sunshine hours was the slowest. The main influencing climatic factors were temperature and sunshine hours in May in the eastern part of Liaoning province but changed to precipitation in the western region. During June to August, the main climatic factors were precipitation and sunshine hours but in September, changed to temperature and sunshine hours. The lag time of temperature and sunshine hours to vegetation was extended from the northeast to southwest Liaoning province, and that for precipitation was opposite.

Key words: NDVI, climatic factors, response analysis, lag period

曹永强, 张亮亮, 袁立婷. 辽宁省植被生长季NDVI对气候因子的响应. 植物学报, 2018, 53(1): 82-93.

Yongqiang Cao, Liangliang Zhang, Liting Yuan. Correlation Analysis of Normalized Difference Vegetation Index (NDVI) and Climatic Factors in the Vegetative Growing Season in Liaoning Province. Chinese Bulletin of Botany, 2018, 53(1): 82-93.

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链接本文: https://www.chinbullbotany.com/CN/10.11983/CBB17010

https://www.chinbullbotany.com/CN/Y2018/V53/I1/82

图/表 10

图1 辽宁省气象站点的空间分布

Figure 1 Distribution of meteorological stations in Liaoning province

图2 植被生长季的月平均NDVI (A)和年际NDVI (B)趋势变化

Figure 2 Monthly average NDVI (A) and interannual NDVI (B) trend changes in vegetation growing season

图3 气候因子的趋势变化(A) 植被生长季的月平均温度; (B) 植被生长季的月平均降雨量; (C) 植被生长季的月平均日照时数

Figure 3 Trend change of climatic factors(A) Monthly average temperature in growing season; (B) Mon- thly average precipitation in growing season; (C) Monthly ave- rage sunshine hours in growing season

表1 气温与植被NDVI的相关系数分级和面积占比

Table 1 The correlation coefficient grade of temperature and NDVI and its area proportion

Month	The correlation coefficient grade
Month	<-0.68 (%)	-0.68- -0.50 (%)	-0.50-0.50 (%)	0.50-0.68 (%)	>0.68 (%)	<0 (%)	>0 (%)
5	0.03	0.59	83.93	14.93	0.52	52.04	47.96
6	0.15	8.83	91.01	0.00	0.00	99.23	0.77
7	10.65	11.12	78.23	0.00	0.00	96.02	3.98
8	6.00	47.38	46.62	0.00	0.00	99.68	0.32
9	0.00	2.10	97.90	0.00	0.00	69.06	30.94

图4 气温与植被NDVI相关性的空间展布

Figure 4 Spatial distribution of correlation between temperature and NDVI

图5 降水量与植被NDVI相关性的空间展布

Figure 5 Spatial distribution of correlation between precipitation and NDVI

表2 降水量与植被NDVI的相关系数分级和面积占比

Table 2 The correlation coefficient grade of precipitation and NDVI and its area proportion

Month	The correlation coefficient grade
Month	<-0.68 (%)	-0.68- -0.50 (%)	-0.50-0.50 (%)	0.50-0.68 (%)	>0.68 (%)	<0 (%)	>0 (%)
5	1.29	9.47	87.70	1.54	0.00	37.08	62.92
6	0.00	0.57	99.42	0.00	0.00	72.72	27.28
7	0.00	0.80	92.92	6.12	0.15	31.15	68.85
8	0.00	0.00	99.52	0.48	0.00	34.24	65.76
9	0.00	0.00	84.54	13.99	1.47	1.83	98.17

图6 日照时数与植被NDVI相关性的空间展布

Figure 6 Spatial distribution of correlation between sunshine hours and NDVI

表3 日照时数与植被NDVI的相关系数分级和面积占比

Table 3 The correlation coefficient grade of sunshine hours and NDVI and its area proportion

Month	The correlation coefficient grade
Month	<-0.68 (%)	-0.68- -0.50 (%)	-0.50-0.50 (%)	0.50-0.68 (%)	>0.68 (%)	<0 (%)	>0 (%)
5	0.00	0.12	96.51	3.04	0.33	39.51	60.49
6	0.00	0.00	99.99	0.01	0.00	27.95	72.05
7	0.05	1.17	97.90	0.88	0.00	60.99	39.01
8	0.00	0.01	99.67	0.32	0.00	21.30	78.70
9	0.00	0.85	99.15	0.00	0.00	73.82	26.18

图7 植被NDVI对气候因子响应滞后期的空间分布(A) 气温; (B) 降水量; (C) 日照时数

Figure 7 The spatial distribution of lag time for NDVI response to climatic factors(A) Temperature; (B) Precipitation; (C) Sunshine hours

参考文献 27

[1]	安佑志 (2014). 基于遥感的中国北部植被NDVI和物候变化研究. 博士论文. 上海: 华东师范大学. pp. 33-36.
[2]	白云俊, 魏雪苹, 秦锋, 李亚蒙, 李金锋, Ranhotra PS, 王宇飞 (2016). 华北上新世-更新世过渡期植被、气候与大气CO2研究进展. 植物学报 51, 257-264.
[3]	崔林丽, 史军, 杨引明, 范文义 (2009). 中国东部植被NDVI对气温和降水的旬响应特征. 地理学报 64, 850-860.
[4]	崔耀平, 刘纪远, 胡云锋, 邴龙飞, 陶福禄, 王军邦 (2012). 中国植被生长的最适温度估算与分析. 自然资源学报 27, 281-292.
[5]	郭敏杰 (2014). 基于NDVI的黄土高原地区植被覆盖度对气候变化响应及定量分析. 硕士论文. 杨凌: 中国科学院研究生院(教育部水土保持与生态环境研究中心). pp. 8.
[6]	何慧娟, 卓静, 王娟, 董金芳, 权文婷 (2016). 陕西省退耕还林植被覆盖度与湿润指数的变化关系. 生态学报 36, 439-447.
[7]	孔云峰, 仝文伟 (2008). 降雨量地面观测数据空间探索与插值方法探讨. 地理研究 27, 1097-1108.
[8]	李辉霞, 刘国华, 傅伯杰 (2011). 基于NDVI的三江源地区植被生长对气候变化和人类活动的响应研究. 生态学报 31, 5495-5504.
[9]	刘玲玲, 刘良云, 胡勇 (2012). 1982-2006年欧亚大陆植被生长季开始时间遥感监测分析. 地理科学进展 31, 1433-1442.
[10]	刘宪锋, 潘耀忠, 朱秀芳, 李双双 (2015a). 2000-2014年秦巴山区植被覆盖时空变化特征及其归因. 地理学报 70, 705-716.
[11]	刘宪锋, 朱秀芳, 潘耀忠, 李宜展, 赵安周 (2015b). 1982- 2012年中国植被覆盖时空变化特征. 生态学报 35, 5331-5342.
[12]	刘正佳, 刘纪远, 邵全琴 (2014). 不同土地覆盖类型上植被生长的最适温度. 地球信息科学学报 16, 1-7.
[13]	毛德华, 王宗明, 罗玲, 宋开山, 刘殿玮, 张柏, 宋长春 (2010). 1982-2008年东北冻土区植被生长季NDVI对气候变化和CO2体积分数增加的响应. 环境科学学报 30, 2332-2343.
[14]	穆少杰, 李建龙, 陈奕兆, 刚成诚, 周伟, 居为民 (2012). 2001-2010年内蒙古植被覆盖度时空变化特征. 地理学报 67, 1255-1268.
[15]	齐述华, 王长耀, 牛铮, 刘正军 (2004). 利用NDVI时间序列数据分析植被长势对气候因子的响应. 地理科学进展 23(3), 91-99.
[16]	魏凤英 (2007).现代气候统计诊断与预测技术(第2版). 北京: 气象出版社. pp. 36-41.
[17]	吴喜芳, 李改欣, 潘学鹏, 王彦芳, 张莎, 刘峰贵, 沈彦俊 (2015). 黄河源区植被覆盖度对气温和降水的响应研究. 资源科学 37, 512-521.
[18]	谢淦, 白加德, 徐景先, 郝慧, 李金锋, 姚轶锋, 张林源, 李承森, 杨健, 王宇飞 (2016). 北京地区全新世植被和气候变化研究进展. 植物学报 51, 872-881.
[19]	薛薇 (2014).基于SPSS的数据分析(第3版). 北京: 中国人民大学出版社. pp. 270-276.
[20]	杨尚武, 张勃 (2014). 基于SPOT NDVI的甘肃河东植被覆盖变化及其对气候因子的响应. 生态学杂志 33, 455-461.
[21]	张景华, 封志明, 姜鲁光, 杨艳昭 (2015). 澜沧江流域植被NDVI与气候因子的相关性分析. 自然资源学报 30, 1425-1435.
[22]	赵舒怡, 宫兆宁, 刘旭颖 (2015). 2001-2013年华北地区植被覆盖度与干旱条件的相关分析. 地理学报 70, 717-729.
[23]	Badeck FW, Bondeau A, Böttcher K, Doktor D, Lucht W, Schaber J, Sitch S (2004). Responses of spring phe- nology to climate change.New Phytol 162, 295-309.
[24]	Blazkova S, Beven K (2004). Flood frequency estimation by continuous simulation of subcatchment rainfalls and discharges with the aim of improving dam safety assessment in a large basin in the Czech Republic.J Hydrol 292, 153-172.
[25]	Pettorelli N, Vik JO, Mysterud A, Gaillard JM, Tucker CJ, Stenseth NC (2005). Using the satellite-derived NDVI to assess ecological responses to environmental change.Trends Ecol Evol 20, 503-510.
[26]	Reed BC, Brown JF (2005). Trend analysis of time-series phenology derived from satellite data. In: Proceedings of the 3rd International Workshop on the analysis of multi- temporal remote sensing images. Biloxi: IEEE. pp. 166-168.
[27]	White MA, De Beurs KM, Didan K, Inouye DW, Richardson AD, Jensen OP, O’Keefe J, Zhang G, Nemani RR, Van Leeuwen WJD, Brown JF, De Wit A, Schaepman M, Lin XM, Dettinger M, Bailey AS, Kimball J, Sch- wartz MD, Baldocchi DD, Lee JT, Lauenroth WK (2009). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006.Glob Chang Biol 15, 2335-2359.