基于遥感的黄土高原植被物候监测及其对气候变化的响应  

Monitoring vegetation phenology and their response to climate change on Chinese Loess Plateau based on remote sensing

作　　者：谢宝妮[1] 秦占飞[1] 王洋[1] 常庆瑞[1] 

机构地区：[1]西北农林科技大学资源环境学院,杨凌712100

出　　处：《农业工程学报》2015年第15期153-160,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：863计划(2013AA102401-2);博士点基金(20120204110013);国家自然科学基金(30872073)

摘　　要：为了分析黄土高原地区植被物候特征,该文基于AVHRR传感器获取的陆地长期数据记录(land long term data record,LTDR)V4 NDVI数据,对黄土高原1982-2011年间植被物候的时空变化进行分析,并借助偏相关分析方法对物候与气温和降雨的关系进行量化分析。结果表明:黄土高原近30 a间春季物候提前显著(0.54 d/a,P<0.001),主要集中在北部草地和灌木植被;秋季物候推迟显著(0.74 d/a,P<0.001),主要分布在甘肃、陕北、内蒙古和山西北部等地。不同植被的春秋物候稍有差异,稀疏灌木林春季物候提前趋势最多(1.31 d/a),常绿针叶林最小(0.19 d/a);秋季物候推迟最多的为乔木园地(1.18 d/a),最少的是水田(0.17 d/a)。黄土高原植被物候主要受气温影响,降雨的变化也会对物候产生一定影响。冬季和前年秋季气温上升是春季物候提前的主要驱动因子;夏季和秋季降雨则对秋季物候休眠期延迟起着重要作用。该研究可为黄土高原生态环境评价及气候变化预测模型提供一定依据。It is crucial to understand vegetation phenology changes and their relationship with climate change at biome-level when projecting regional ecosystem carbon exchange and climate-biosphere interactions. To further understand the relationship between vegetation growth and climatic factors, in this study, we investigated the variation in vegetation phenology and its linkage with climate change on the Chinese Loess Plateau through analyzing the Land Long Term Data Record（LTDR） NOAA/AVHRR Normalized Difference Vegetation Index（NDVI） and concurrent temperature and precipitation during 1982-2011. Firstly, the maximum value composite（MVC） method was used to composite the 10 d LTDR NDVI dataset in order to reduce effects of atmospheric and cloud noise. The Harmonic Analysis of Time Series（HANTS） method of HANTS software was used to filter points which were still affected by cloud noise after the MVC was used composite and reconstruct the NDVI time series datasets. Secondly, the 30-year average seasonal NDVI curves for the whole study area and each vegetation type were calculated. Pixels with yearly mean values below 0.1 were excluded from the analysis to ensure the inclusion of sparsely vegetated areas in the analysis. The relative change ratio of NDVI was then calculated from the 30-year average NDVI seasonal curves. We then used the maximum and minimum values for relative change ratio of NDVI as the threshold for the onset dates of vegetation green-up（the beginning of growing season, BGS） and dormancy（the end of growing season, EGS）. Finally, linear least square regression was employed to estimate the trends of phenology. Partial correlation analysis was performed between the EGS/ BGS and mean monthly temperature and total monthly precipitation. The results showed that vegetation phenology in the study area generally commenced on Julian day 96-150 for natural vegetation and 72-112 for artificial vegetation. The vegetation dormancy usually began on Julian day 283-305 for natural vegetation and 291

关 键 词：植被 遥感 气候变化 物候 陆地长期数据记录 黄土高原 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] S127[自动化与计算机技术—控制科学与工程]