摘要:基于GIMMS_3g（1982-2015年）、SOPT VEG（1998-2015年）和MODIS（2000-2017年）3种NDVI数据集，结合气温、降水和DEM数据，利用平均法、线性趋势分析法和相关分析法等方法，分析了秦巴山区植被覆盖的时空变化特征及其与气候因子的相关性，并以秦岭山地（陕西境内）为重点区域，分析了植被覆盖的海拔梯度差异及其与气候因子的垂直响应模式。结果表明：①1982-2017年秦巴山区3种植被NDVI均呈显著增加趋势，其中1982-2015年NDVI-GIMMS_3g增速为1.4%/10a，1982-2000年NDVI-GIMMS_3g较低且波幅较大，增速为1.6%/10a，年际间变异系数（CV）为0.04，2000-2015年NDVI-GIMMS_3g较高且稳定增加，增速为1.7%/10a，CV为0.02；2000-2015年NDVI-SPOT VEG增速为4.1%/10a，CV为0.04；2000-2017年NDVI-MODIS年增速为4.5%/10a，CV为0.04；②2000-2017年（MODIS数据）秦巴山区植被覆盖高值区主要为秦岭、米仓山和神农架等山地，低值区主要为西部高海拔区和东部低海拔区等区域；秦岭山地随海拔升高植被NDVI先升高后降低；③2000-2017年（MODIS数据）秦巴山区植被覆盖增加和减少的区域分别占96.90%和3.10%，低海拔地区较高海拔地区变化剧烈；秦岭山地低海拔带植被覆盖较高海拔带增加显著；④2000-2015年（SOPT VEG数据）秦巴山区增温效应显著，增速为0.49℃/10a，植被覆盖与温度以正相关为主，与降水正负相关并存，与温度的相关性较降水的相关性高；秦岭山地高海拔带植被对温度变化更敏感，低海拔带对降水更敏感。



Abstract:Vegetation and its characteristics are largely controlled by regional landforms and climate. The Qingling-Daba Mountains are located in a transitional zone between the subtropical and the warm temperate climate in China, where a complex relationship between vegetation and climate exits. To explore this relationship, we used GIMMS_3g (1982-2015), SPOT VEGTATION (SPOT VEG) (1998-2015), and MODIS (2000-2017), the DEM, and climate data (temperature and precipitation) to quantify the spatiotemporal changes in vegetation in the Shaanxi Province of the mountains. We found that:(1) NDVI of the GIMMS_3g database increased significantly at a rate of 1.4%/10a from 1982 through 2015. For 1982-2000, NDVI of GIMMS_3g was low but highly variable (linear tendency 1.6%/10a, CV=0.4) by year, whereas a stable increasing trend appeared after 2000 (linear tendency 1.7%/10a, CV=0.2). For 2000-2015, the increasing rate was 4.1%/10a (CV=0.04) for NDVI of the SPOT VEG database. For 2000-2015, the increasing rate was 4.5%/10a (CV=0.04) for NDVI of the MODIS database. (2) High vegetation coverage was found from MODIS for 2000-2017, primarily in the mountainous regions (e.g., Qinling Mountains, Micang Mountains, and Shennongjia), whereas low cover was detected at high altitudes in the west and low altitudes in the east. For the Qinling Mountains, NDVI increased and decreased with elevation. (3) The increase and decrease of vegetation coverage during 2000-2017 accounted for 96.90% and 3.10% of the total land area, respectively. Meanwhile, the vegetation cover at low altitude appeared more protected than that in the high-altitude areas. (4) Annual mean temperature in the study area increased by 0.49℃/10a during 1982-2015, whereas the precipitation showed no significant change. For 2000-2015, we found that vegetation cover (based on SPOT VEG and climate data) was positively correlated with temperature, but not with precipitation. The correlation analysis further demonstrated that vegetation cover was more strongly correlated with temperature in the Qingling-Daba Mountains. In the Qinling Mountains, the correlation was significant between NDVI and temperature in the high-altitude areas, and between NDVI and precipitation in low-altitude areas.





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