渭河流域NDVI与气候因子时空变化及相关性研究
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摘要
NDVI的时空变化可以反映区域生态环境的演变,基于像元尺度的趋势分析法能模拟研究区栅格单元的变化趋势,从而反映NDVI时空分布的变化细节。基于2000—2015年MODIS NDVI月时序数据,结合同期气象资料,利用趋势分析和相关分析的方法研究了渭河流域NDVI、气温和降水的时空变化特征及其相关性。结果表明:(1)近16年来,渭河流域平均NDVI呈增大的趋势,变化率约为0.088/10 a,植被覆盖度有所增加;NDVI增大的区域占流域总面积的97.77%,主要分布在流域西部和北部。(2)时间尺度上,NDVI与气温的相关系数为0.865,偏相关系数为0.664;NDVI与降水的相关系数为0.776,偏相关系数为0.346,表明气温和降水的季节变化对植被生长都具有重要影响,且气温的影响更为显著。(3)空间尺度上,NDVI与气温呈正相关的像元数占像元总数的51.21%,NDVI与降水呈正相关的像元数占像元总数的96.67%,表明就渭河流域而言,气温的变化对植被生长的影响具有空间差异性和不确定性,而降水的增加会促进植被的生长。
The tempo-spatial changes of NDVI can reflect the evolution of regional ecological environment. On the basis of pixel scale, trend analysis method can simulate the trend of each grid cell in the study area, reflecting the detailed information of NDVI changes. Based on monthly data of MODIS NDVI from 2000 to 2015 and meteorological data of the same period, trend analysis method and correlation analysis method were used to study the tempo-spatial variation characteristics and correlation of NDVI, temperature and precipitation in the Weihe Watershed. The results showed that:(1) in the past 16 years, the average NDVI of the Weihe Watershed had increased, the rate of change was about 0.088/decade, and the vegetation coverage had increased; during the 16 years, the area of increasing NDVI accounted for 97.77% of the total watershed, these areas mainly distributed in the west and north of the watershed;(2) in the time series, the correlation coefficient between NDVI and temperature was 0.865, the partial correlation coefficient was 0.664; the correlation coefficient between NDVI and precipitation was 0.776, and the partial correlation coefficient was 0.346; it indicated that the seasonal variation of temperature and precipitation had a remarkable impact on vegetation growth, and the effect of temperature was more significant;(3) on the pixel scale, the area where NDVI was positively correlated with temperature accounted for 51.21%; the area in which NDVI was positively correlated with precipitation accounts for 96.67%. It indicated that there were spatial differences and uncertainty in the effects of temperature on vegetation growth, and the increase of precipitation mainly promoted the growth of vegetation.
The tempo-spatial changes of NDVI can reflect the evolution of regional ecological environment. On the basis of pixel scale, trend analysis method can simulate the trend of each grid cell in the study area, reflecting the detailed information of NDVI changes. Based on monthly data of MODIS NDVI from 2000 to 2015 and meteorological data of the same period, trend analysis method and correlation analysis method were used to study the tempo-spatial variation characteristics and correlation of NDVI, temperature and precipitation in the Weihe Watershed. The results showed that:(1) in the past 16 years, the average NDVI of the Weihe Watershed had increased, the rate of change was about 0.088/decade, and the vegetation coverage had increased; during the 16 years, the area of increasing NDVI accounted for 97.77% of the total watershed, these areas mainly distributed in the west and north of the watershed;(2) in the time series, the correlation coefficient between NDVI and temperature was 0.865, the partial correlation coefficient was 0.664; the correlation coefficient between NDVI and precipitation was 0.776, and the partial correlation coefficient was 0.346; it indicated that the seasonal variation of temperature and precipitation had a remarkable impact on vegetation growth, and the effect of temperature was more significant;(3) on the pixel scale, the area where NDVI was positively correlated with temperature accounted for 51.21%; the area in which NDVI was positively correlated with precipitation accounts for 96.67%. It indicated that there were spatial differences and uncertainty in the effects of temperature on vegetation growth, and the increase of precipitation mainly promoted the growth of vegetation.
引文
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[18]赵安周,朱秀芳,刘宪锋,等.1965—2013年渭河流域降水时空变化分析[J].自然资源学报,2015,30(11):1896-1909.
[19]刘宪锋,任志远,林志慧,等.2000—2011年三江源区植被覆盖时空变化特征[J].地理学报,2013,68(7):897-908.
[20]白建军,白江涛,王磊.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.
[21]何月,樊高峰,张小伟,等.浙江省植被NDVI动态及其对气候的响应[J].生态学报,2012,32(14):4352-4362.
[22]Zhou L M, Tucker C J, Kaufmann R F, et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research, 2001,106(D17):20069-20083.
[23]Myneni R B, Keeling C D, Tucker C J, et al. Increased plant growth in the northern high latitudes from 1981 to 1991[J]. Nature, 1997,386(6626):698-702.
[2]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.
[3]於琍,李克让,陶波,等.植被地理分布对气候变化的适应性研究[J].地理科学进展,2010,29(11):1326-1332.
[4]张景华,李英年.青海气候变化趋势及对植被生产力影响的研究[J].干旱区资源与环境,2008,22(2):97-102.
[5]候静,杜灵通,刘可,等.1982—2012年北半球荒漠草原过渡带植被物候特征及其与气候因子的关系[J].气候变化研究进展,2017,13(5):473-482.
[6]Pettorelli N, Vik J, Mysterud A, et al. Using the satellite-derived NDVI to assess ecological responses to environmental change[J]. Trends in Ecology & Evolution, 2005,20(9):503-510.
[7]Pang G J, Wang X J, Yang M X. Using the NDVI to identify variations in, and responses of, vegetation to climate change on the Tibet Plateau from 1982 to 2012[J]. Quaternary International, 2017,444:87-96.
[8]孟梦,牛铮,马超,等.青藏高原NDVI变化趋势及其对气候的响应[J].水土保持研究,2018,25(3):360-365,372.
[9]Liu Y, Li Y, Li S C, et al. Spatial and temporal patterns of global NDVI trends: Correlations with climate and human factors[J]. Remote Sensing, 2015,7(10):13233-13250.
[10]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):199-125.
[11]Xu G, Zhang H F, Chen B Z, et al. Changes in Vegetation Growth Dynamics and Relations with Climate over China′s Landmass from 1982 to 2011[J]. Remote Sensing, 2014,6(4):3263-3283.
[12]杜加强,贾尔恒·阿哈提,赵晨曦,等.1982—2012年新疆植被NDVI的动态变化及其对气候变化和人类活动的响应[J].应用生态学报,2015,26(12):3567-3578.
[13]Al-Bakri J T, Suleman A S. NDVI response to rainfall in different ecological zones in Jordan[J]. International Journal of Remote Sensing, 2004,25(19):3897-3912.
[14]Keersmaecker W D, Lhermitte S, Hill M, et al. Assessment of regional vegetation response to climate anomalies:A case study for Australia using GIMMS NDVI Time Series between 1982 and 2006[J]. Remote Sensing, 2017,9(1):34-51.
[15]Zhang G, Su X, Singh V P, et al. Modeling NDVI using joint entropy method considering hydro-meteorological driving factors in the middle reaches of Hei River Basin[J]. Entropy, 2017,19(9):502-515.
[16]陈福军,沈彦俊,胡乔利,等.海河流域NDVI对气候变化的响应研究[J].遥感学报,2011,15(2):401-414.
[17]刘少华,严登华,史晓亮,等.中国植被NDVI与气候因子的年际变化及相关性研究[J].干旱区地理,2014,37(3):480-489.
[18]赵安周,朱秀芳,刘宪锋,等.1965—2013年渭河流域降水时空变化分析[J].自然资源学报,2015,30(11):1896-1909.
[19]刘宪锋,任志远,林志慧,等.2000—2011年三江源区植被覆盖时空变化特征[J].地理学报,2013,68(7):897-908.
[20]白建军,白江涛,王磊.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.
[21]何月,樊高峰,张小伟,等.浙江省植被NDVI动态及其对气候的响应[J].生态学报,2012,32(14):4352-4362.
[22]Zhou L M, Tucker C J, Kaufmann R F, et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research, 2001,106(D17):20069-20083.
[23]Myneni R B, Keeling C D, Tucker C J, et al. Increased plant growth in the northern high latitudes from 1981 to 1991[J]. Nature, 1997,386(6626):698-702.
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