| 近十年黄河三角洲NDVI时空动态及其对气温和降水的响应特征 |
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| 引用本文： | 李明杰,侯西勇,应兰兰,路晓,朱明明.近十年黄河三角洲NDVI时空动态及其对气温和降水的响应特征[J].资源科学,2011,33(2):322-327. |
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| 作者姓名： | 李明杰 侯西勇 应兰兰 路晓 朱明明 |
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| 作者单位： | 1. 中国科学院烟台海岸带研究所,烟台,264003;中国科学院研究生院,北京,100049
2. 中国科学院烟台海岸带研究所,烟台,264003 |
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| 基金项目： | 中国科学院知识创新工程重要方向项目(编号：kzcx2-yw-224)；国家自然科学基金项目(编号：40801016)；中国科学院“十一五”e-Science应用示范项目(编号：INFO-115-D01- Z005)。 |
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| 摘 要： | 本文基于SPOT-VGTS10产品(1998年4月-2008年12月)以及相应时段东营站点的气温、降水数据,利用一元线性回归方法、Hurst指数方法分析近10年黄河三角洲NDVI时空动态,并探讨NDVI与气温、降水因子的年际、季节、月际响应特征。研究表明:①NDVI变化以良性发展为主,但NDVI长期无变化区及弱持续性中度改善区值得关注,且NDVI弱、中、强持续性退化区面积较广,理应尤为关注,并探讨和寻找原因;②NDVI变化与气温、降水均有较高的相关性,相关系数分别为0.81、0.63,若考虑1个月的时间延迟,则相关系数分别为0.89、0.75;③延迟1个月的NDVI与气温、降水的相关性研究更具科学性和准确性。.春季(2月-4月)、夏季(5月-7月)气温对植物生长起决定作用,秋季(8月-10月)气温无明显变化趋势,NDVI值变化受降水强度影响较大;不同月份气温、降水对NDVI的影响主导作用不同,延迟程度不同。
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| 关 键 词： | NDVI 时空格局 气候因子 相关性 黄河三角洲 |
Spatial-Temporal Dynamics of NDVI and Its Response to Temperature and Precipitation in the Yellow River Delta during the Period 1998-2008 |
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| LI Mingjie,HOU Xiyong,YING Lanlan,LU Xiao and ZHU Mingming.Spatial-Temporal Dynamics of NDVI and Its Response to Temperature and Precipitation in the Yellow River Delta during the Period 1998-2008[J].Resources Science,2011,33(2):322-327. |
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| Authors: | LI Mingjie HOU Xiyong YING Lanlan LU Xiao and ZHU Mingming |
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| Institution: | Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China; Graduate University of the Chinese Academy of Sciences, Beijing 100049, China;Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China;Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China; Graduate University of the Chinese Academy of Sciences, Beijing 100049, China;Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China; Graduate University of the Chinese Academy of Sciences, Beijing 100049, China;Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China; Graduate University of the Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Satellite remote sensing represents a significant breakthrough in the scientific community, providing critical surface and atmospheric information at a variety of spatial and temporal scales. It has been widely used in the Earth sciences and can also be an effective way to monitor the vegetation dynamics and global changes. Vegetation cover and growth are influenced by climatic changes. Normalized Differential Vegetation Index (NDVI) can essentially reveal the status of vegetation and ecology; however, the relationship between NDVI and the major climatic factors remains still unclear, such as temperature and precipitation. There seems to be few published studies concerned with the use of time series NDVI data investigate the mechanisms of changes in vegetation in response to climatic factors. In this paper, we made use of time series NDVI data to examine the response of vegetation to major climatic factors based on geographic information system (GIS) and statistical methods. We described the evolution and spatial variability of NDVI in Dongying City during the period April 1998-December 2008, and its relationship with temperature and precipitation using satellite products of SPOT-VGT S10 and ground observations of temperature and precipitation. Using linear regression and the Hurst index we determined the spatial-temporal variability of NDVI. Based on the correlation coefficient method, we identified the annual, seasonal, and monthly response of the NDVI to temperature and precipitation to be the most important climatic factors. While most portions of the study area showed generally stable NDVI values over the 10-year period, the NDVI development of some areas might be indicative of loss of vegetation to certain extent, which requires further study to find out the fundamental reasons for the loss. Furthermore, it is found that there existed a marked relationship between temperature and NDVI and precipitation and NDVI with correlation coefficients of 0.81 and 0.63, respectively. These correlation coefficients increased to 0.89 and 0.75 when taking into account a lag of one month between these climatic factors and the vegetation development. There appeared to be different relationships between the temperature and the precipitation in different periods of vegetation growth. The temperature was found to be the dominant factor affecting vegetation growth in spring (February-April) and summer (May-July), whereas precipitation was the dominant factor influencing vegetation in the autumn period (August-October), with indicating less influence of temperature. |
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| Keywords: | NDVI Spatial-temporal patterns Climatic factors Correlation Yellow River Delta |
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