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2000—2017年川渝地区植被NDVI特征及其对极端气候的响应

冯磊,杨东*,黄悦悦   

  1. (西北师范大学地理与环境科学学院, 兰州 730070)
  • 出版日期:2020-07-10 发布日期:2021-01-09

Vegetation NDVI characteristics and response to extreme climate in Sichuan and Chongqing from 2000 to 2017.

FENG Lei, YANG Dong*, HUANG Yue-yue   

  1. (College of Geographyand Environmental Science, Northwest Normal University, Lanzhou 730070, China).
  • Online:2020-07-10 Published:2021-01-09

摘要: 基于2000—2017年MOD13Q1植被指数产品和极端气温、降水指数,分析川渝地区生长季NDVI的时空变化特征,并借助相关分析和Lasso回归模型探讨NDVI与极端指数的关系。结果表明:川渝地区NDVI均值为0.6134,呈现出0.033 (10 a-1)的变化趋势;东部地区NDVI值和变化率均高于西部地区,成都市和重庆市NDVI值及其变化率相较于周边地区明显偏低;川渝地区东西部的交界地带和东部及其偏北区域对极端气候指数的响应表现较为明显,除冷昼日数和单日最大降水量以外,其余极端气温、降水指数均与NDVI呈正相关,其中平均气温与NDVI正相关面积占比最广,为81.79%,而冷昼日数与NDVI的负相关面积占比最大,为76.57%。Lasso回归模型计算得到的预测值与遥感提取的NDVI值具有很好的一致性(R=0.81),模型对相关性结果进行验证的同时还弥补了相关分析仅考虑单个极端指数的不足。川渝地区NDVI受气温的影响比降水更显著,且以正相关关系为主,短期内强降水不利于植被的生长。

关键词: 底栖动物, 芦苇, 优势种, 长江口, 生境价值

Abstract: Based on the MOD13Q1 vegetation index products and extreme temperature and extreme precipitation indices from 2000 to 2017, we examined the temporal and spatial variations of NDVI in Sichuan and Chongqing during the growing season, and analyzed the relationshipbetween NDVI and extreme indices with correlation analysis method and Lasso regression model. The results showed that the average NDVI value of Sichuan and Chongqing was 0.6134, with a change rate of 0.033 (10 a-1). The NDVI values and their change rates in the eastern region were higher than those in the western region. The NDVI value and change rates in Chengdu City and Chongqing City were significantly lower compared with the surrounding areas. The responses of eastwest borders and east of Sichuan and Chongqing and its northerly area to the extreme climate indices were more obvious. Except for the number of cold days and the maximum daily precipitation, other indices were positively correlated with NDVI. Among which, the area with positive correlation between average temperature and NDVI was the largest, accounting for 81.79% of the total, while the area with negative correlation between the number of cold days and NDVI was the largest, accounting for 76.57%. The predicted values calculated by the Lasso regression model were well fitted with the NDVI values extracted by remote sensing (R=0.81), and the model verified the correlation results and also made up the deficiencies of correlation analysis considering only a single extreme index. The NDVI in Sichuan and Chongqing region was more significantly affected by temperature than by precipitation, which were mainly positively correlated. Heavy rainfall was not conducive to the growth of vegetation in the short term.

Key words: habitat value., Yangtze River estuary, Phragmites australis, dominant species, zoobenthos