Analysis of Vegetation Dynamics over Liaoning Province Based on Remote Sensing Data
WANG Li-wen1,2, WEI Ya-xing3, NIU Zheng1
1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 2. Graduate School of Chinese Academy of Sciences, Beijing 100039, China 3. College of Urban and Environmental Sciences Liaoning Normal University, Dalian 116029, China
Abstract：In the present paper, the authors used normalized difference vegetation index (NDVI) data derived from NOAA AVHRR sensor to analyze spatial heterogeneity and temporal dynamics of Liaoning province during the past two decades. A set of 2 292 spatially distributed NDVI values were analyzed to investigate obvious deviations by the mean-monthly values from 1982 to 2001. Various statistical analyses including minimum, mean and maximum values, coefficient of variation (CV), standardized anomalies (Z-scores), and 36-month running mean were used for monthly NDVI values to research spatial and temporal variations in vegetation. In Liaoning province, the authors found the strong seasonal oscillations during plants growing period, the maximum value of NDVI appeared in July-August, and seasonal variation ranged from 6% to 14% of CV value. Vegetation greenness kept upward trend from 1984 to 1990, but showed downward trend from 1991 to 1998. Vegetation greenness followed an interannual oscillation period of 7-8 years. The authors also found that the variation of NDVI peak along latitude direction was 20%-25% greater in 1991-1999 than in 1982-1990 in dry season across Liaoning province. The conclusions of this paper suggest that the patterns of vegetation variability in Liaoning province were caused by enhanced aridity occurring over the last decade of the 20th century.
Key words：Remote sensing;Vegetation dynamics;EI Nino;Drought;Liaoning Province
王莉雯1,2,卫亚星3,牛铮1. 基于遥感数据的辽宁省植被变化分析[J]. 光谱学与光谱分析, 2008, 28(12): 2956-2960.
WANG Li-wen1,2, WEI Ya-xing3, NIU Zheng1. Analysis of Vegetation Dynamics over Liaoning Province Based on Remote Sensing Data. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2008, 28(12): 2956-2960.
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