摘要:以中国东北地区的沈阳、长春、哈尔滨3个大城市及其周边的乡村为研究单元，在像元尺度上采用小波变换法对长时间序列中分辨率成像光谱仪（Moderate-resolution Imaging Spectroradiometer，MODIS）增强植被指数（Enhanced Vegetation Index，EVI）数据滤除噪声数据后重建平滑的EVI曲线，基于EVI曲线，采用动态阈值法提取出研究区2009-2016年植被关键物候期参数指标，即植被生长季开始时间（Start of Growing Season，SOS）和结束时间（End of Growing Season，EOS），分析各研究单元植被物候时空变化特征及其对地表温度的响应特征。结果表明：各研究单元SOS和EOS值的空间分布图存在明显的城乡差异。每一个像元所属的实际位置距离城区中心越近，其SOS值越小，EOS值越大，表明植被生长季开始日期早结束日期晚，整个植被生长期时间变长。各研究单元植被物候参数指标的年际变化趋势具有一定的相似性，即SOS随时间均呈现出提前趋势，且城区和乡村的SOS年际变化趋势保持一致，变化速率各不相同。研究区2012年的SOS值是研究时段内的最大值，从植被物候期反映来看，该年是一个最冷年，这与当年受寒潮影响，出现暴雪，低温等极端天气的气候现象相吻合。各研究单元年均地表温度（Land Surface Temperature，LST）与对应的植被关键物候期参数均有显著的相关性，SOS与LST呈显著负相关，EOS与LST呈高度正相关。即植被物候同期的平均温度越高，植被生长季的起始时间越早，结束时间越晚。



Abstract:Three large cities in Northeast China (Shenyang, Changchun and Harbin) and their surrounding rural areas are taken as the study units. The wavelet transform method is used to reduce the noise data of long time series Moderate-resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data and reconstructed smooth EVI curves in pixel scale. Based on EVI curves, the key vegetation phenological parameter indexes from 2009 to 2016, namely the start of growing season (SOS) and the end of growing season (EOS) are extracted by using the dynamic threshold method. The spatio-temporal change of vegetation phenology and their responses to surface temperature in each study unit are analyzed. The results show that the differences in the spatial distribution of the SOS and the EOS in each study unit are significant between urban area and rural area. The area where a smaller value of SOS is taken is consistent with the area where a larger value of EOS is taken, and vice versa. The spatial distribution of vegetation phenology indexes and their geographical locations (either urban or rural) are highly consistent. The closer the actual location of each pixel is to its urban center, the smaller the SOS value is and the larger the EOS value is, which indicates an early start and a late end of the growing season, that is, a longer growing season. From 2009 to 2016, the average annual SOS values in these 3 cities form an early center in the urban areas and show a tendency of gradual delay from the urban area to the rural area, whereas the average annual EOS values form a late center in urban areas and show a tendency of gradual advance from the urban area to the rural area. The SOS is between the 99th and the 112nd day in urban areas, while the SOS is between the 125th day and the 135th day in rural areas. The time difference of urban-rural SOS is about 3 weeks. The EOS is between the 293rd and the 300th day in urban areas, while the EOS is between the 284th and the 286th day in rural areas. The urban EOS is approximately 2 weeks later than that in rural areas. The inter-annual change trend of vegetation phenological parameter indexes in each study unit has some similarities, that is, SOS shows an early trend with time, and the trend of SOS inter-annual change in urban and rural areas is consistent but with different rate. The maximum of the SOS value during the study period occurred in 2012 in the study areas, which was the coldest year in terms of vegetation phonological indexes and this coincided with the climatic phenomena of extreme weather such as blizzard and low temperature, which were affected by the cold wave in the year. The average annual land surface temperature (LST) of each study unit is significantly correlated with the corresponding vegetation phenological indexes. There is a significant negative correlation between SOS and LST, and a high positive correlation between EOS and LST. The higher the average temperature of the same vegetation phenological period, the earlier the start time of vegetation growth season, and the later the end time of vegetation growth season.





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