Spatio-temporal distribution of NDVI and its correlation with climatic factors in Eastern China during 1998-2008

Cong Zhou; Runhe Shi; Chao Zhang; Chaoshun Liu; Wei Gao

doi:10.1117/12.2060768

8 October 2014 Spatio-temporal distribution of NDVI and its correlation with climatic factors in eastern China during 1998-2008

Cong Zhou, Runhe Shi, Chao Zhang, Chaoshun Liu, Wei Gao

Author Affiliations +

Proceedings Volume 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI; 92210G (2014) https://doi.org/10.1117/12.2060768
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

The aim of this work was to analyze the distribution of NDVI and its correlation with climatic factors in Eastern China during 1998 - 2008. For this purpose, SPOT-VGT images and 143 meteorological data in Eastern China were collected and analyzed. Results showed that the values of Normalized Difference Vegetation Index (NDVI) were generally higher in the southern part than those in the northern part of Eastern China. The NDVI showed a hidden nonlinear trend after wavelet transform, whereas variations existed in the correlation between NDVI and the four climatic factors (i.e., precipitation and relative humidity, temperature, sunshine hours). NDVI data were positively correlated with temperature and sunshine hours, which was opposite to what was observed in precipitation and relative humidity. Furthermore, the same chan1ge cycle was found for NDVI and precipitation, temperature, and sunshine hours, which were nearly 290 days based on normalized wavelet variance. However, the change cycles of relative humidity showed a different spatial distribution. In the north part of Eastern China, about 30 ten-day were detected, which was not the case for the southern part, where the number increased to 186 ten-day.

Citation Download Citation

Cong Zhou, Runhe Shi, Chao Zhang, Chaoshun Liu, and Wei Gao "Spatio-temporal distribution of NDVI and its correlation with climatic factors in eastern China during 1998-2008", Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 92210G (8 October 2014); https://doi.org/10.1117/12.2060768

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KEYWORDS

Climatology

Wavelets

Humidity

Vegetation

Meteorology

Wavelet transforms

Environmental sensing

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