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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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2018 Impact Factor: 1.205

Front Earth Sci    0, Vol. Issue () : 227-236    https://doi.org/10.1007/s11707-012-0321-3
RESEARCH ARTICLE
Assessing phenological change in China from 1982 to 2006 using AVHRR imagery
Haiyan WEI1(), Philip HEILMAN1, Jiaguo QI2, Mark A. NEARING1, Zhihui GU3, Yongguang ZHANG4
1. USDA-ARS Southwest Watershed Research Center, AZ 85719, USA; 2. Michigan State University, MI 48824-1117, USA; 3. Shenzhen University, Shenzhen 518060, China; 4. Beijing Normal University, Beijing 100875, China
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Abstract

Long-term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and climate. In this study we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT program to quantify annual vegetation production and its changing trend. Results showed great spatial variability in vegetation growth and its temporal trend across the country during the 25-year study period. Significant decreases in vegetation production were detected in the grasslands of Inner Mongolia, and in industrializing regions in southern China, including the Pearl River Delta, the Yangtze River Delta, and areas along the Yangtze River. Significant increases in vegetation production were found in Xinjiang, Central China, and North-east China. Validation of the NDVI trends and vegetated area changes were conducted using Landsat imagery and the results were consistent with the analysis from AVHRR data. We also found that although the causes of the vegetation change vary locally, the spatial pattern of the vegetation change and the areas of greatest impact from national policies launched in the 1970s, such as the opening of economic zones and the ‘Three-North Shelter Forest Programme’, are similar, which indicates an impact of national policies on ecosystem change and that such impacts can be detected using the method described in this paper.

Keywords AVHRR      China      remote sensing      climate change      policy      desertification      temporal trend      phenology     
Corresponding Author(s): WEI Haiyan,Email:haiyan.wei@gmail.com   
Issue Date: 05 September 2012
 Cite this article:   
Haiyan WEI,Philip HEILMAN,Jiaguo QI, et al. Assessing phenological change in China from 1982 to 2006 using AVHRR imagery[J]. Front Earth Sci, 0, (): 227-236.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-012-0321-3
https://academic.hep.com.cn/fesci/EN/Y0/V/I/227
Fig.1  Seasonal parameters computed in TIMESAT: (a) beginning of season; (b) peak; (c) end of growing season; (d) amplitude; (e) small integral over the growing season, area between NDVI curve and zero level; (f) base value; (Adapted from )
Fig.2  The small integral over the growing season in 1982 across China
Fig.3  Different vegetation dynamics explain the difference in small integral in deciduous and evergreen forests. Data was extracted for E’erguna-Zuo Qi in the North-east China (deciduous) and Sanming City in the South-east China (evergreen), respectively, in 1982
Fig.4  Trend of vegetation growth during 1982 to 2006, indicated by the slope value of linear relationship between annual small integral over growing season with year (≤0.05). The number and location names are selected counties that show significant positive or negative trends (see Figs. 5 and 6)
Fig.5  Examples of positive (upper panel) and negative (lower panel) trends in vegetation growth for eight selected counties
#CountyLinear regression between the values of annual small integral (y) and time from 1982 to 2006 (x)r2
positive trends
1Changjiy = 43.18 x - 832270.72
2Dengkouy = 27.63 x - 536130.72
3Qingshuihey = 50.27 x - 980400.59
4Aohany = 58.76 x - 1144120.62
negative trends
5Nantongy= -103.87 x + 2104720.70
6Guanningy= -114.19 x + 2325010.48
7Qianjiangy= -87.20 x + 1766360.72
8Mabiany= -73.84 x + 1512330.42
Tab.1  Trend of small integral over growing season at locations indicated in Fig. 4
Fig.6  Time series of annual rainfall during 1982 to 2006 at selected counties indicated there were no significant precipitation changes at these locations
Fig.7  Location of Landsat image pairs used for validation (quadrangle with number 1-8). Legend refers to Fig. 4
Fig.8  Validation of AVHRR NDVI using Landsat data
Landsat classification resultsTrend analysis results from AVHRR for county nearby/within
#LocationDateSatelliteSensorResolution/mVegetated area/ %Vegetation change */%County nameSlope of the linear trend **
1Inner Mongolia24-Aug-1989Landsat 5TM3010.1815.40Yakeshi12.87
13-Jul-2000Landsat 7ETM+3011.75
2Xinjiang13-Aug-1979Landsat 2MSS607.7851.67Jimusa'er26.20
28-Jun-2002Landsat 7ETM+3011.80
3Inner Mongolia15-Sep-1977Landsat 2MSS6044.99-4.58Wulate-Zhong-3.48
14-Sep-2000Landsat 7ETM+3042.93
4Liaoning5-Jul-1976Landsat 2MSS6064.3713.64Huangren32.67
21-Sep-2001Landsat 7ETM+3073.15
5Hebei3-May-1979Landsat 2MSS6026.9356.33Xingtai38.23
7-May–2000Landsat 7ETM+3042.10
6Henan14-May–1988Landsat 5TM3047.05-5.53Dengfeng-24.56
10-May–2000Landsat 7ETM+3044.45
7Hubei16-Aug-1984Landsat 2MSS6066.54-45.34Xiantao-74.56
22-Jul-2001Landsat 7ETM+1536.37
8Guangdong10-Nov-1979Landsat 3MSS6081.27-19.56Zengcheng-94.32
14-Sep-2000Landsat 7ETM+3065.37
Tab.2  Vegetation change at 8 locations based on classification on Landsat images
Fig.9  Vegetation area classified from Landsat image, (a) Xinjiang, Sep 15, 1977; (b) Xinjiang, Sep 14, 2000; (c) Guangdong, Aug 16,1984; (d) Guangdong, July 22, 2001
Fig.10  The cultivated land area in Shanghai decreased 35% from 1978 to 2005, based on data from Shanghai Municipal Statistics Bureau.
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