甘南州草地植被覆盖度与物候期时空变化动态特征
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摘要
植被覆盖度是衡量草地植被生长状况的重要指标,植被物候过程是反映植被对气候变化响应的最直接和最敏感的生态学过程之一。研究草地植被盖度及物候期遥感监测方法,对综合分析草地植被变化状况具有重要意义。
利用2001-2011年每年5-10月的Terra/MODIS逐月归一化差值植被指数(Normalized Difference Vegetation Index, NDVI)和增强型植被指数(Enhanced Vegetation Index, EVI)数据,结合甘南草地外业观测及气象资料,建立了甘南州草地生长季的植被覆盖度遥感反演模型,对比研究了不同草地植被覆盖度模型的精度,模拟分析了甘南州2001-2011年草地生长季期间不同等级的草地植被盖度时空分布特征及面积变化动态；对遥感数据天数据进行10日最大合成后,得到10日合成植被指数,建立了甘南草地植被物候曲线模型,采用最大斜率法研究了甘南草地植被返青起始期、休眠起始期和生长季长度等主要物候现象的发生时间及其变化动态,分析了不同物候阶段的草地植被覆盖度与EVI变化特征,探讨了气象因素对物候期的整体影响。主要研究结论如下：
(1) MODIS-EVI可以最大限度地减少环境因子的影响,在植被覆盖度高的地区使用更具优势,能很好地反映各类植被覆盖度的空间和时间差异性。MODIS-EVI的对数函数(y=33.6581n(x)+112.65)可以较好地模拟甘南州草地植被盖度分布状况,总精度可达93.31%。
(2)近11年甘南州草地植被盖度总体呈波动上升趋势,其中2001年、2003年和2008年草地植被覆盖明显偏低,2005年植被覆盖度最高,平均达78.43%。甘南州中西部及西南部地区的草地植被覆盖度较东部更好。
(3)甘南州近11年草地植被均以高和较高植被覆盖度为主,其余等级的草地植被覆盖度所占比例相对较小(6.98%)且稳定。总体上,甘南草地具有由高植被盖度向较高植被盖度转换的趋势。
(4)利用2001-2011年每年不同物候阶段的草地植被物候曲线公式,按照最大斜率法确定的甘南草地植被物候变化情况表明,甘南州草地植被平均返青起始期的发生时间为一年的第151±9d,黄枯起始期发生时间为一年的第267±17d,生长季长度为115±11d(约为4个月)。
(5)在11年间,甘南州返青起始期的EVI呈波动上升趋势,波动范围为0.23-0.41；黄枯起始期EVI值较返青起始期EVI值变化小,相对稳定,波动范围为0.31-0.43；EVI年最大值的变化趋势与返青起始期一样呈波动上升趋势,变化范围为0.55-0.63；EVI年最大值和其出现天数的变化趋势相似。
(6)随着温度的升高,返青起始期提前,休眠起始期延迟,生长季延长。温度较降水对返青起始期的影响更大,降水对返青起始期和休眠起始期的影响均相对较小。植被的物候现象包含着气候变化的信息,不同草地植被类型对降水响应的机制较复杂,需要做进一步的探索研究。
Vegetation cover is an important indicator for reflecting grassland vegetation growth condition, and vegetation phenology is a sensitive indicator of ecological response to climate change. Vegetation cover and phenology play an important role in evaluation and analyzation of vegetation restoration.
Using Terra/MODIS product of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) from May to October during2001-2011, combined with ground observed data and meteorological data, the inversion models of grassland vegetation cover were established, their precisions were compared, and the characteristics of grassland vegetation cover were analyzed in growing seasons during2001-2011in Gannan prefecture. Using10-day synthetic vegetation index, the inversion models of grassland vegetation phenology were established, by use of the maximum slope method the green-up, dormancy and growing season lengths (GSL), as well as grassland vegetation cover and EVI dynamic changes in different phenological phases were analyzed, and the influence factors of meteorological factors in phenology was also discussed. Results suggested that:
(1)The logarithmic function(y=33.6581n(x)+112.65) of MODIS-EVI is the best model to simulate grassland vegetation cover in Gannan pastoral area, its precision reaches93.31%.
(2)MODIS-EVI has more advantages in high vegetation cover region, which can finely reflect the spatial and temporal difference of vegetation cover, and reduce the effect of environmental factors to maximum extent. In recent11years, grassland vegetation cover in Gannan prefecture has an increasing trend. The grassland vegetation cover was78.43%in2005, which reached a maximum value, and the vegetation cover of2001,2003and2008were obviously lower than those in other years. The vegetation cover in the midwest and southwest areas is better than that in the eastern area.
(3)Grassland vegetation was dominated by high vegetation cover and higher vegetation cover levels, the proportion of other grassland vegetation cover levels was small (6.98%) and stable. Overall, grassland in Gannan prefecture for the eleven years was characterized by transforming from high vegetation cover into higher vegetation cover.
(4)The occurrence time of grassland vegetation green-up is151±9d in Gannan prefecture; the occurrence time of grassland vegetation dormancy is267±17d; the growing season lengths(GSL) is115±11d(about4month).
(5) During2001-2011, the range of EVI in green-up is0.23-0.41with a rising trend. In dormancy, the range of EVI is0.31-0.4and there was a downward trend. The maximum value of EVI is0.55-0.63.
(6)With increasing temperature, green-up was advanced, dormancy and growing season lengths haves prolonged. Meteorological factors have influence on the phenology of Gannan prefecture. The effect of temperature was greater than precipitation. The impact mechanism is complexity in different grassland types, we need to do further study.
利用2001-2011年每年5-10月的Terra/MODIS逐月归一化差值植被指数(Normalized Difference Vegetation Index, NDVI)和增强型植被指数(Enhanced Vegetation Index, EVI)数据,结合甘南草地外业观测及气象资料,建立了甘南州草地生长季的植被覆盖度遥感反演模型,对比研究了不同草地植被覆盖度模型的精度,模拟分析了甘南州2001-2011年草地生长季期间不同等级的草地植被盖度时空分布特征及面积变化动态；对遥感数据天数据进行10日最大合成后,得到10日合成植被指数,建立了甘南草地植被物候曲线模型,采用最大斜率法研究了甘南草地植被返青起始期、休眠起始期和生长季长度等主要物候现象的发生时间及其变化动态,分析了不同物候阶段的草地植被覆盖度与EVI变化特征,探讨了气象因素对物候期的整体影响。主要研究结论如下：
(1) MODIS-EVI可以最大限度地减少环境因子的影响,在植被覆盖度高的地区使用更具优势,能很好地反映各类植被覆盖度的空间和时间差异性。MODIS-EVI的对数函数(y=33.6581n(x)+112.65)可以较好地模拟甘南州草地植被盖度分布状况,总精度可达93.31%。
(2)近11年甘南州草地植被盖度总体呈波动上升趋势,其中2001年、2003年和2008年草地植被覆盖明显偏低,2005年植被覆盖度最高,平均达78.43%。甘南州中西部及西南部地区的草地植被覆盖度较东部更好。
(3)甘南州近11年草地植被均以高和较高植被覆盖度为主,其余等级的草地植被覆盖度所占比例相对较小(6.98%)且稳定。总体上,甘南草地具有由高植被盖度向较高植被盖度转换的趋势。
(4)利用2001-2011年每年不同物候阶段的草地植被物候曲线公式,按照最大斜率法确定的甘南草地植被物候变化情况表明,甘南州草地植被平均返青起始期的发生时间为一年的第151±9d,黄枯起始期发生时间为一年的第267±17d,生长季长度为115±11d(约为4个月)。
(5)在11年间,甘南州返青起始期的EVI呈波动上升趋势,波动范围为0.23-0.41；黄枯起始期EVI值较返青起始期EVI值变化小,相对稳定,波动范围为0.31-0.43；EVI年最大值的变化趋势与返青起始期一样呈波动上升趋势,变化范围为0.55-0.63；EVI年最大值和其出现天数的变化趋势相似。
(6)随着温度的升高,返青起始期提前,休眠起始期延迟,生长季延长。温度较降水对返青起始期的影响更大,降水对返青起始期和休眠起始期的影响均相对较小。植被的物候现象包含着气候变化的信息,不同草地植被类型对降水响应的机制较复杂,需要做进一步的探索研究。
Vegetation cover is an important indicator for reflecting grassland vegetation growth condition, and vegetation phenology is a sensitive indicator of ecological response to climate change. Vegetation cover and phenology play an important role in evaluation and analyzation of vegetation restoration.
Using Terra/MODIS product of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) from May to October during2001-2011, combined with ground observed data and meteorological data, the inversion models of grassland vegetation cover were established, their precisions were compared, and the characteristics of grassland vegetation cover were analyzed in growing seasons during2001-2011in Gannan prefecture. Using10-day synthetic vegetation index, the inversion models of grassland vegetation phenology were established, by use of the maximum slope method the green-up, dormancy and growing season lengths (GSL), as well as grassland vegetation cover and EVI dynamic changes in different phenological phases were analyzed, and the influence factors of meteorological factors in phenology was also discussed. Results suggested that:
(1)The logarithmic function(y=33.6581n(x)+112.65) of MODIS-EVI is the best model to simulate grassland vegetation cover in Gannan pastoral area, its precision reaches93.31%.
(2)MODIS-EVI has more advantages in high vegetation cover region, which can finely reflect the spatial and temporal difference of vegetation cover, and reduce the effect of environmental factors to maximum extent. In recent11years, grassland vegetation cover in Gannan prefecture has an increasing trend. The grassland vegetation cover was78.43%in2005, which reached a maximum value, and the vegetation cover of2001,2003and2008were obviously lower than those in other years. The vegetation cover in the midwest and southwest areas is better than that in the eastern area.
(3)Grassland vegetation was dominated by high vegetation cover and higher vegetation cover levels, the proportion of other grassland vegetation cover levels was small (6.98%) and stable. Overall, grassland in Gannan prefecture for the eleven years was characterized by transforming from high vegetation cover into higher vegetation cover.
(4)The occurrence time of grassland vegetation green-up is151±9d in Gannan prefecture; the occurrence time of grassland vegetation dormancy is267±17d; the growing season lengths(GSL) is115±11d(about4month).
(5) During2001-2011, the range of EVI in green-up is0.23-0.41with a rising trend. In dormancy, the range of EVI is0.31-0.4and there was a downward trend. The maximum value of EVI is0.55-0.63.
(6)With increasing temperature, green-up was advanced, dormancy and growing season lengths haves prolonged. Meteorological factors have influence on the phenology of Gannan prefecture. The effect of temperature was greater than precipitation. The impact mechanism is complexity in different grassland types, we need to do further study.
引文
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