摘要
基于MODIS/TERRA卫星数据,反演洱海2016年8月-2019年12月NDVI值,分析NDVI与气象要素的关系。结果表明,NDVI空间分布具有差异性,高值中心位于中西部边缘及南部出水口附近,低值中心主要位于北部;整体上,洱海NDVI值边缘区的大于中心区的,中部NDVI值呈西高东低分布。洱海NDVI具有明显的年变化,春夏季洱海NDVI值明显高于秋冬季的,年内呈双峰型分布,分别在4月和7月达到峰值;3月、9月洱海NDVI值的明显增加和降低与洱海水温处于增温和降温阶段有密切关系。考虑气象因子对NDVI的累积响应和滞后效应,温度、降雨量等气象因子与NDVI之间的相关性总体呈现“+-+”或“-+-”的分布类型。基于气象因子的NDVI多元线性逐步回归模型复相关系数为0.51,对NDVI值的趋势模拟效果较好,对预测洱海藻类数量趋势有参考价值。
Based on MODIS/TERRA satellite data,the NDVI values of Erhai Lake from August 2016 to December 2019 are inverted and their relationships with meteorological conditions are analyzed.The results show that,NDVI values in Erhai Lake presented uneven spatial distribution.High-value center located near the central and western edge and the southern water outlet of the lake,and the low-value center mainly located in the north.On the whole,the NDVI values in fringe areas of Erhai Lake were larger than the center area.The NDVI values in the center area presented the distribution of higher to the west and lower to the east.The NDVI values in Erhai Lake showed an annual variation with a bimodal change,and they reached the peak in April and July.Obvious higher values appeared in spring and summer,and lower values in autumn and winter.The obvious increase in March and remarkable decrease in September of NDVI values had close relation with the increase and decrease phase of water temperature in Erhai.Considering the cumulative response and hysteresis effects of meteorological factors,the correlation relationships between NDVI values and meteorological factors such as temperature,rainfall and so on showed the symbols of correlation as“+-+”or“-+-”distribution pattern.The established regression model of NDVI with meteorological factors had a multiple correlation coefficient of 0.51 and a good simulation effect on the variation trend of NDVI values,which signified that the model had important reference significance for predicting the change trend of the number of algae in Erhai Lake.
作者
陈彩霞
高志伟
杨坤琳
朱淳源
Chen Caixia;Gao Zhiwei;Yang Kunlin;Zhu Chunyuan(Meteorological Bureau of Dali Prefecture of Yunnan Province,Dali 671000,China)
出处
《气象与环境科学》
2023年第5期1-8,共8页
Meteorological and Environmental Sciences
基金
2022年云南基层台站气象科技创新与能力提升计划项目(STIAP202241)
2018年云南省州(市)区域创新能力提升专项资金项目(2018CA011-02)。
