Spatial Sensitivity of NDVI Index to Climate Factors
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摘要: 基于全球土地利用类型和覆盖度,利用生长季多年平均(1982~2015年)归一化植被指数(Normalized Difference Vegetation Index,NDVI)和气候平均态(气温、降水量)数据,讨论了全球植被格局与气候因子之间的关系,建立了两者之间的多元回归模型,并分析了植被对气温和降水气候态敏感性的特征。植被与气候因子在气候梯度上存在明显的对应关系,回归模型可较好拟合气候态NDVI的全球分布格局,拟合与观测NDVI的相关系数达0.90。其中,常绿阔叶林、混交林、常绿针叶林、落叶阔叶林、农田和木本稀树草原空间分布的拟合能力较好(r>0.8)。不同土地覆盖类型的NDVI对气温、降水气候态的空间敏感性特征不同。整体而言,植被对气温和降水的敏感性呈现反相关关系(r=−0.6)。不同土地覆盖类型对气温表现出正/负敏感性,寒带灌木对气温的敏感性最强,而农作物、草原、裸地对气温负敏感性较大;植被对降水的敏感性均表现出正敏感性,其中落叶针叶林、草原和稀树草原对降水的空间敏感性较强。Abstract: Based on the global land cover type and coverage, we used the NDVI (Normalized Difference Vegetation Index) and averaged climate state data (temperature, precipitation) of the growing season from 1982 to 2015 in this study. The relationship between global vegetation distribution and climate factors was discussed, and a multiple regression model was developed. The sensitivity of vegetation to climate states (temperature and precipitation) was analyzed. There was an apparent correspondence between vegetation and climate factors on the climate gradient. The regression model has fitted the distribution pattern of climatic NDVI well, and the correlation coefficient between global fitting and the observed NDVI was 0.90. Among them, the fitting ability of spatial distribution of the broadleaf evergreen forests, mixed forests, needleleaf evergreen forests, broadleaf deciduous forests, and cropland and woody savanna were great (r>0.8). The NDVIs of different land cover types demonstrated different spatial sensitivity characteristics to temperature and precipitation climate states. Overall, the sensitivity of vegetation to temperature and precipitation demonstrated an inversed correlation (r=−0.6). Different land cover types showed positive/negative sensitivity to temperature. Boreal shrubs demonstrated the greatest sensitivity to temperature, while crops, grasslands, and bare land proved the high negative sensitivity to temperature than others. The sensitivity of vegetation to precipitation was positive, and the spatial sensitivity of needleleaf deciduous forests, grass, and savanna to precipitation was high.
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图 3 生长季多年平均NDVI随气候要素(a)气温、(b)降水量的变化规律(气温和降水量选取间隔分别为0.5°C和10 mm,点线:间隔内平均值,蓝色虚线:间隔内25%分位数,红色虚线:间隔内75%分位数)
Figure 3. Change in mean annual NDVI (Normalized Difference Vegetation Index) depending on climate factors (a) temperature and (b) precipitation in the growing season (bin interval: 0.5°C and 100 mm; Dot line: mean value within the interval; blue line: 25% quantile within the interval; red line: 75% quantile within the interval)
图 8 拟合NDVI随气候要素(a)气温、(b)降水量的变化规律(气温和降水选取间隔分别为0.5°C和10 mm;点线:间隔内平均值,蓝色虚线:间隔内25%分位数,红色虚线:间隔内75%分位数)
Figure 8. Simulated NDVI in climate factors (a) temperature (b) precipitation in the growing season (bin interval: 0.5°C and 100 mm; dot line: mean value within the interval; blue line: 25% quantile within the interval; red line: 75% quantile within the interval)
图 12 敏感性系数βT、βP随生长季多年平均(a、b)气温、(c、d)月降水量、(e、f)NDVI的变化特征(格点温度、降水、NDVI的变化区间分别为0.5°C、10 mm和0.05
Figure 12. Variation in sensitivity coefficients (βT, βP) with (a, b) temperature, (c, d) precipitation, and (e, f) NDVI (resampled into bins with a temperature interval of 0.5°C, a precipitation interval of 10 mm, an NDVI interval of 0.05, respectively)
图 13 (a)植被对温度敏感性(βT)、(b)植被对降水敏感性(βP)对生长季多年平均气温和月降水量变化的分布 (格点温度和降水的变化区间分别为0.5°C和10 mm)
Figure 13. Mean average sensitivity coefficients compared to temperature and precipitation (a) NDVI sensitivity to temperature, (b) NDVI sensitivity to precipitation (resampled into bins with a temperature interval of 0.5°C and a precipitation interval of 10 mm)
表 1 本文及国际地圈生物圈计划(IGBP)对土地覆盖类型的分类
Table 1. Reclassification of land cover types in this article and the International Geosphere–Biosphere Programme (IGBP) classification
本文分类 国际地圈生物圈计划(IGBP)分类 裸地(Bare) Barren Urban and Built-up lands 常绿针叶林(NEF) Needleleaf Evergreen Forests 落叶针叶林(NDF) Needleleaf Deciduous Forests 常绿阔叶林(BEF) Broadleaf Evergreen Forests 落叶阔叶林(BDF) Broadleaf Deciduous Forests 混交林(MixF) Mixed Forests 寒带灌木(BorS) Open Shrublands/ Closed Shrublands 温带灌木(TemS) Closed Shrublands/ Open Shrublands 木本稀树草原(wSav) Woody Savanna 稀树草原(Sav) Savanna 草原(Grass) Grass 农田(Crop) Cropland Cropland/Natural Vegetation Mosaics 雪(Snow) Snow and Ice / Water Bodies / Permanent Wetlands 表 2 不同土地覆盖类型观测与拟合NDVI的空间相关系数以及拟合NDVI均方根误差
Table 2. The spatial correlation coefficient between observed and simulated NDVI, and root mean square error (RMSE) of observed NDVI of different land cover types
土地覆盖类型 观测NDVI 拟合NDVI 格点数(n) 观测与拟合NDVI空间相关系数 拟合NDVI均方根误差 裸地(Bare) 0.233 0.236 990 0.53 0.092 常绿针叶林(NEF) 0.457 0.427 3989 0.85 0.075 落叶针叶林(NDF) 0.493 0.462 754 0.57 0.058 常绿阔叶林(BEF) 0.741 0.699 6039 0.90 0.101 落叶阔叶林(BDF) 0.602 0.548 533 0.81 0.091 混交林(MixF) 0.531 0.505 3907 0.87 0.065 寒带灌木(BorS) 0.338 0.319 10140 0.73 0.089 温带灌木(TemS) 0.271 0.273 4508 0.75 0.057 木本稀树草原(wSav) 0.570 0.550 3136 0.80 0.077 稀树草原(Sav) 0.532 0.530 3900 0.75 0.079 草原
(Grass)0.322 0.332 4737 0.76 0.074 农田
(Crop)0.458 0.444 8201 0.81 0.070 -
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