25a来黑河流域NDVI的时空演变与气候响应
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摘要
黑河流域地处我国西北干旱区,由于地形、气候影响等因素,该区自然景观多样,是气候变化敏感区,但生态环境脆弱。揭示黑河流域植被变化的历史,对维护区域生态平衡,建设西北生态屏障,以及西部大开发有重要意义。
本文基于1982-2006年25年来GIMMS/NDVI数据集以及黑河流域十二个气象站点温度、降水观测资料,通过差值法、均值法、相关分析、多项式曲线拟合等方法对黑河流域25a来植被覆盖变化分别从时间尺度、空间尺度上进行研究,并将NDVI与气象资料做相关分析,揭示植被覆盖变化与气象因子之间的关系,得到了以下主要结论：
(1)25a黑河流域NDVI的时间变化趋势
黑河流域植被覆盖在25a间略有上升,但总体趋势比较微弱。通过对25a来年均NDVI一元线性回归(y=0.004x-0.64,R2=0.223)结果显示,25a来黑河流域NDVI上升约6.2%。NDVI最小是年份是1985年,为0.1485。最高值年份是2002年,值为0.1735。由于气候、地形等引起的植被类型不同,黑河流域植被覆盖上游好于中游,下游最差。25a来黑河流域上、中、下游年平均NDVI值分别是0.1843、0.1634、0.0919。黑河上游与中游地区的变化趋势基本一致,增长幅度分别是4.98%和6.7%,均高于流域整体增幅。黑河下游NDVI增长最为明显,25a来累计增长9.24%。对黑河流域25a间年均NDVI多元曲线拟合发现,25a来黑河流域NDVI的变化大致可以分为两个阶段：1982-1992年,为显著上升时期；1993-2006年,NDVI保持相对高值,稳定时期。黑河流域年内NDVI的变化有很强的季节性规律,即春季萌发,夏季旺盛,秋季下降。黑河下游四季NDVI均低于中上游地区,只有夏季NDVI可达到0.1以上。对比三个时期月均NDVI变化发现,增长幅度最为明显的是5月份,其次是6月和10月。黑河上游地区春季NDVI的增长明显高于其他季节,其增长幅度分别到达15%,主要得益于全球变暖带来的春季升温,促使植被生长季提前。
(2)黑河流域NDVI的空间演变
通过分析NDVI序列与年份相关系数得出,黑河流域增长趋势明显(R>0.39,P<0.05)的像元为231个。而可通过P<0.01与P<0.001显著检验的像元主要集中于野牛沟、托勒、张掖、金塔附近。流域植被覆盖下降的区域主要集中于黑河上游祁连山中西部。将黑河流域NDVI依据亮度值分级,并对比其两期序列的变化情况,发现25a来高植被覆盖像元略有增加,但黑河下游地区其总数仍然很低。无植被像元有相应减少,其他则无明显变化。
(3)黑河流域NDVI与气象因子的响应关系
12个气象站点年均NDVI与温度的响应系数均高于降水,说明在年际尺度上NDVI的变化更加依赖于温度的变化。黑河中游年均NDVI对温度的响应明显高于上、下游。对温度响应最为剧烈的野牛沟与张掖,相关系数分别达到0.692和0.572(P<0.01)。对降水响应最高的点是民乐与山丹,相关系数仅为0.300与0.278,尚未通过P<0.05的显著性检验。黑河中上游地区月NDVI变化与温度、降水变化关系密切,大部分相关系数可以通过P<0.001的显著性检验。黑河下游月NDVI变化与气象因子变化相关系数较低。黑河流域不同区域季节NDVI对气象因子的响应依地域的不同具有差异性。其中,受春季温度影响最大的是黑河中游绿洲地区；对夏季降水响应剧烈的地区是山丹、民乐两远离黑河干流的气象站。秋季植被凋零,进入生长周期的衰退期,与温度、降水的关系均不敏感。黑河中上游地区夏季NDVI受春季温度、降水的滞后影响较大。
Heihe River Basin, located in the arid region of Northwest China, is well recognized for its diversity of natural landscapes and its fragility of ecological environment and is very sensitive to climatic fluctuations due to the effect of multiple landforms and local climate. Thus, it is of significant importance to reveal the history of vegetation variations in Heihe River Basin for the maintenance of ecological equilibrium, the establishment of ecological barrier as well as the development of western regions in China.
Based on the GIMMS/NDVI dataset from1982to2006and temperature and precipitation observation data from12meteorological stations within Heihe River Basin, we focus on the variations of vegetation cover in the past25a temporally and spatially by ways of difference method, averaging method, correlation analysis together with polynomial curve fitting. The correlation analysis between NDVI and meteorological factors shows as follows:
(1)Time variation trends of NDVI in Heihe River Basin
Although the past25a witnessed an upward trend in vegetation cover, the tendency was quite slight. Employing the simple linear regression (y=0.004x-0.64, R2=0.223) to cope with the dataset, we find that values of NDVI went up by nearly6.2%in the25a and the minimum NDVI occurred in1985with a value of0.1485, while the maximum NDVI happened in2002with a value of0.1735. The annual average values of NDVI in the upper, middle and down streams was0.1843,0.1634and0.0919. The variation tendency of the upper stream kept in step with that of the middle stream, increasing by4.98%and6.7%, respectively, which was higher than the growth of the entire basin. The growth of NDVI in the downstream of Heihe River Basin was highest, and the cumulative increase was9.24%during this period. Using the multivariate curve fitting for the yearly average NDVI, we find this period can be roughly divided into two stages:a) NDVI maintained a significant rise over the period1982-1992; b) NDVI leveled off and kept relatively high. The variations of NDVI in the basin exhibited a seasonal rhythm apparently, e.g. the growth of vegetation starts in spring, reaches a peak in summer and declined gradually in autumn. NDVI of four seasons in the downstream was lower than that of the upper and middle stream. The NDVI in summer simply reaches above0.1. By comparing the variations of monthly NDVI over the three periods, we claim that May see the most dramatic growth, followed by June and October. Moreover, the growth of NDVI in spring in the upper stream was higher than that of other seasons remarkably, indicating that quick warming in spring resulting from global change has advanced the dates of the growing season.
(2) Spatial evolutions of NDVI in Heihe River Basin
By analyzing the correlation coefficient between NDVI sequence and years, NDVI went up evidently (R>0.39, P<0.05) in231pixels, among which the pixels around Yeliugou, Tuole, Zhangye and Jinta could pass the significant test of P<0.01and P<0.001. The areas where the vegetation cover declined mainly concentrated in the middle and western part of Qilian Mountains. After classifications of NDVI during the two periods, we find that the number of those pixels representing high vegetation covers increased slightly, but the absolute number in the downstream was still quite low. Additionally, the number of the pixels standing for non-vegetation zones declined accordingly. There were no other significant changes anyway.
(3) Response relationship between NDVI and meteorological factors in Heihe River Basin
The response relationships between annual average NDVI and temperature are higher than precipitation in the12meteorological stations, indicating that temperature plays a more important role in the variations of NDVI for the interannual variability. The response relationship between annual average NDVI and temperature in the middle stream is higher significantly than that in the upper and down stream. The most dramatic response to temperature happened in Yeliugou (0.692) and Zhangye (0.572), while the highest response coefficients were simply0.300in Minle and0.278in Shandan, not even passing the significant test (P<0.05). The meteorological factors had no effect on the variation of monthly NDVI in the downstream. The relationships between monthly NDVI and meteorological factors varied accompanied by different regions and different seasons. The results point out that spring temperature has the most significant effect to the oases area in the middle stream and precipitation plays a relatively important role in Minle and Shandan, which are far away from the oases. In autumn, at the end of the growing season, there is no relationship between the variation of NDVI and temperature and precipitation. Likewise, we find that lags between the variations of NDVI in summer and precipitation and temperature in spring are evident.
本文基于1982-2006年25年来GIMMS/NDVI数据集以及黑河流域十二个气象站点温度、降水观测资料,通过差值法、均值法、相关分析、多项式曲线拟合等方法对黑河流域25a来植被覆盖变化分别从时间尺度、空间尺度上进行研究,并将NDVI与气象资料做相关分析,揭示植被覆盖变化与气象因子之间的关系,得到了以下主要结论：
(1)25a黑河流域NDVI的时间变化趋势
黑河流域植被覆盖在25a间略有上升,但总体趋势比较微弱。通过对25a来年均NDVI一元线性回归(y=0.004x-0.64,R2=0.223)结果显示,25a来黑河流域NDVI上升约6.2%。NDVI最小是年份是1985年,为0.1485。最高值年份是2002年,值为0.1735。由于气候、地形等引起的植被类型不同,黑河流域植被覆盖上游好于中游,下游最差。25a来黑河流域上、中、下游年平均NDVI值分别是0.1843、0.1634、0.0919。黑河上游与中游地区的变化趋势基本一致,增长幅度分别是4.98%和6.7%,均高于流域整体增幅。黑河下游NDVI增长最为明显,25a来累计增长9.24%。对黑河流域25a间年均NDVI多元曲线拟合发现,25a来黑河流域NDVI的变化大致可以分为两个阶段：1982-1992年,为显著上升时期；1993-2006年,NDVI保持相对高值,稳定时期。黑河流域年内NDVI的变化有很强的季节性规律,即春季萌发,夏季旺盛,秋季下降。黑河下游四季NDVI均低于中上游地区,只有夏季NDVI可达到0.1以上。对比三个时期月均NDVI变化发现,增长幅度最为明显的是5月份,其次是6月和10月。黑河上游地区春季NDVI的增长明显高于其他季节,其增长幅度分别到达15%,主要得益于全球变暖带来的春季升温,促使植被生长季提前。
(2)黑河流域NDVI的空间演变
通过分析NDVI序列与年份相关系数得出,黑河流域增长趋势明显(R>0.39,P<0.05)的像元为231个。而可通过P<0.01与P<0.001显著检验的像元主要集中于野牛沟、托勒、张掖、金塔附近。流域植被覆盖下降的区域主要集中于黑河上游祁连山中西部。将黑河流域NDVI依据亮度值分级,并对比其两期序列的变化情况,发现25a来高植被覆盖像元略有增加,但黑河下游地区其总数仍然很低。无植被像元有相应减少,其他则无明显变化。
(3)黑河流域NDVI与气象因子的响应关系
12个气象站点年均NDVI与温度的响应系数均高于降水,说明在年际尺度上NDVI的变化更加依赖于温度的变化。黑河中游年均NDVI对温度的响应明显高于上、下游。对温度响应最为剧烈的野牛沟与张掖,相关系数分别达到0.692和0.572(P<0.01)。对降水响应最高的点是民乐与山丹,相关系数仅为0.300与0.278,尚未通过P<0.05的显著性检验。黑河中上游地区月NDVI变化与温度、降水变化关系密切,大部分相关系数可以通过P<0.001的显著性检验。黑河下游月NDVI变化与气象因子变化相关系数较低。黑河流域不同区域季节NDVI对气象因子的响应依地域的不同具有差异性。其中,受春季温度影响最大的是黑河中游绿洲地区；对夏季降水响应剧烈的地区是山丹、民乐两远离黑河干流的气象站。秋季植被凋零,进入生长周期的衰退期,与温度、降水的关系均不敏感。黑河中上游地区夏季NDVI受春季温度、降水的滞后影响较大。
Heihe River Basin, located in the arid region of Northwest China, is well recognized for its diversity of natural landscapes and its fragility of ecological environment and is very sensitive to climatic fluctuations due to the effect of multiple landforms and local climate. Thus, it is of significant importance to reveal the history of vegetation variations in Heihe River Basin for the maintenance of ecological equilibrium, the establishment of ecological barrier as well as the development of western regions in China.
Based on the GIMMS/NDVI dataset from1982to2006and temperature and precipitation observation data from12meteorological stations within Heihe River Basin, we focus on the variations of vegetation cover in the past25a temporally and spatially by ways of difference method, averaging method, correlation analysis together with polynomial curve fitting. The correlation analysis between NDVI and meteorological factors shows as follows:
(1)Time variation trends of NDVI in Heihe River Basin
Although the past25a witnessed an upward trend in vegetation cover, the tendency was quite slight. Employing the simple linear regression (y=0.004x-0.64, R2=0.223) to cope with the dataset, we find that values of NDVI went up by nearly6.2%in the25a and the minimum NDVI occurred in1985with a value of0.1485, while the maximum NDVI happened in2002with a value of0.1735. The annual average values of NDVI in the upper, middle and down streams was0.1843,0.1634and0.0919. The variation tendency of the upper stream kept in step with that of the middle stream, increasing by4.98%and6.7%, respectively, which was higher than the growth of the entire basin. The growth of NDVI in the downstream of Heihe River Basin was highest, and the cumulative increase was9.24%during this period. Using the multivariate curve fitting for the yearly average NDVI, we find this period can be roughly divided into two stages:a) NDVI maintained a significant rise over the period1982-1992; b) NDVI leveled off and kept relatively high. The variations of NDVI in the basin exhibited a seasonal rhythm apparently, e.g. the growth of vegetation starts in spring, reaches a peak in summer and declined gradually in autumn. NDVI of four seasons in the downstream was lower than that of the upper and middle stream. The NDVI in summer simply reaches above0.1. By comparing the variations of monthly NDVI over the three periods, we claim that May see the most dramatic growth, followed by June and October. Moreover, the growth of NDVI in spring in the upper stream was higher than that of other seasons remarkably, indicating that quick warming in spring resulting from global change has advanced the dates of the growing season.
(2) Spatial evolutions of NDVI in Heihe River Basin
By analyzing the correlation coefficient between NDVI sequence and years, NDVI went up evidently (R>0.39, P<0.05) in231pixels, among which the pixels around Yeliugou, Tuole, Zhangye and Jinta could pass the significant test of P<0.01and P<0.001. The areas where the vegetation cover declined mainly concentrated in the middle and western part of Qilian Mountains. After classifications of NDVI during the two periods, we find that the number of those pixels representing high vegetation covers increased slightly, but the absolute number in the downstream was still quite low. Additionally, the number of the pixels standing for non-vegetation zones declined accordingly. There were no other significant changes anyway.
(3) Response relationship between NDVI and meteorological factors in Heihe River Basin
The response relationships between annual average NDVI and temperature are higher than precipitation in the12meteorological stations, indicating that temperature plays a more important role in the variations of NDVI for the interannual variability. The response relationship between annual average NDVI and temperature in the middle stream is higher significantly than that in the upper and down stream. The most dramatic response to temperature happened in Yeliugou (0.692) and Zhangye (0.572), while the highest response coefficients were simply0.300in Minle and0.278in Shandan, not even passing the significant test (P<0.05). The meteorological factors had no effect on the variation of monthly NDVI in the downstream. The relationships between monthly NDVI and meteorological factors varied accompanied by different regions and different seasons. The results point out that spring temperature has the most significant effect to the oases area in the middle stream and precipitation plays a relatively important role in Minle and Shandan, which are far away from the oases. In autumn, at the end of the growing season, there is no relationship between the variation of NDVI and temperature and precipitation. Likewise, we find that lags between the variations of NDVI in summer and precipitation and temperature in spring are evident.
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