基于NDVI时间序列的近12年中国植被覆盖的单调趋势分析

李强; 张翀

doi:10.13961/j.cnki.stbctb.2014.03.026

您当前的位置：

首页 >

文章列表页 >

基于NDVI时间序列的近12年中国植被覆盖的单调趋势分析

试验研究

- 基于NDVI时间序列的近12年中国植被覆盖的单调趋势分析
- An Analysis of Monotonic Trend of Vegetation Cover in China Based on NDVI Time Series
- 水土保持通报 2014年33卷第3期页码：135-140
- 作者机构：
  
  1. 陕西师范大学旅游与环境学院,陕西,西安,710062
  2. 陕西学前师范学院环境与资源管理系,陕西,西安,710100
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目"基于过程的陕北能源富集区土地利用转型与时空配置研究"(41301618);陕西师范大学中央高校基本科研业务费专项资金资助(GK201404005);陕西省社会科学基金项目(13D019);陕西省教育厅科学研究计划项目(2013JK0851)
- DOI：10.13961/j.cnki.stbctb.2014.03.026
  中图分类号：
- 纸质出版：2014
- 稿件说明：
移动端阅览
李强, 张翀. 基于NDVI时间序列的近12年中国植被覆盖的单调趋势分析[J]. 水土保持通报, 2014,33(3):135-140.

LI Qiang, ZHANG Chong. An Analysis of Monotonic Trend of Vegetation Cover in China Based on NDVI Time Series[J]. Bulletin of Soiland Water Conservation, 2014, 33(3): 135-140.
李强, 张翀. 基于NDVI时间序列的近12年中国植被覆盖的单调趋势分析[J]. 水土保持通报, 2014,33(3):135-140. DOI： 10.13961/j.cnki.stbctb.2014.03.026.

LI Qiang, ZHANG Chong. An Analysis of Monotonic Trend of Vegetation Cover in China Based on NDVI Time Series[J]. Bulletin of Soiland Water Conservation, 2014, 33(3): 135-140. DOI： 10.13961/j.cnki.stbctb.2014.03.026.

摘要

基于1999-2010年SPOT-VEGETATION旬值NDVI数据

并结合谐波分析、线性趋势和Kendall's τ趋势等方法对中国各年植被生长季起止时刻进行了确定

并得到中国生长季植被覆盖的单调性趋势。结果表明: (1) 1999-2010年中国植被覆盖呈明显增加趋势。中国植被覆盖变化存在4 a的稳定增长期与1 a的突然下降期。(2) 中国生长季植被覆盖Kendall's τ趋势平均值为0.287 3

总体上呈持续改善趋势

持续性较高的改善区主要分布在105°E以东

30°-40°N之间的区域。(3) 中国植被覆盖受纬度地带性影响较为明显。纬度低

生物多样性程度较高的地区

则植被覆盖改善趋势明显

持续性强

反之改善趋势及持续性较低。黄三角和风沙区等生态脆弱区

长三角、珠三角与兰州市周边地区等经济快速发展区

植被覆盖退化严重。

Abstract

Using harmonic analysis

linear regression and Kendall's τ trend

based on the 10 day SPOT-VEGETATION NDVI from 1999 to 2010

we determined the beginning and end times of vegetation growth of each year

found the monotonic trend of vegetation coverage in growing season and interpolated the trend difference and growing season change of vegetation coverage for different vegetation types. Results are as follows: (1) From 1999 to 2010

the vegetation cover in China showed a progressively increasing trend as a whole. The annual variation of vegetation cover displayed the periodicity of 4 years steady growth and 1 year sudden decline. (2) On average

Kendall's τ trend for vegetation cover in growing season in China presented a continuous improvement

being 0.2873. The improved area with high persistence was mainly distributed in the region between 30°-40°N

and to the east of 105°E. (3) The vegetation cover was controlled by the change of latitude. The trend showing improvement was more significant and persistent at low latitude with high degree of biological diversity. The vegetation cover showed serious degradation in the ecological fragile zones like the Yellow River Delta and windy-sandy region

as well as in the rapid economic development areas like the Yangtze River Delta

Pearl River Delta and surrounding area of Lanzhou City.

关键词

Keywords

references

Foley J A, Levis S, Costa M H, et al. Incorporating dynamic vegetation cover within global climate models[J]. Ecological Applications, 2000,10(6):1620-1632.

IPCC. 4th Assessment report of the intergovernmental panel on climate change[M]. Synthesis Report, 2007:52.

穆少杰,李建龙,陈奕兆.2001-2010年内蒙古植被覆盖度时空变化特征[J].地理学报,2012,67(9):1255-1268.

Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation[J]. Remote Sensing of Environment, 1979(8):27-150.

Prince S D, Tucker C J. Satellite remote sensing of rangelands in Botswana (Ⅱ):NOAA AVHRR and herbaceous vegetation[J]. International Journal of Remote Sensing, 1986,7(11):1555-1570.

Alcaraz-Segura D, Chuvieco E, Epstein H E, et al. Debating the greening vs. browning of the North American boreal forest:Differences between satellite datasets[J]. Global Change Biology, 2009,16(2):760-770.

Pettorelli N, Vik J O, Mysterud A, et al. Using the satellite-derived NDVI to assess ecological responses to environmental change[J]. Trends in Ecology & Evolution, 2005,20(9):503-510.

White M A, de Beurs K M, Didan K, et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006[J]. Global Change Biology, 2009,15(10):2335-2359.

Tottrup C, Rasmussen M S. Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time series of remote sensing data[J]. Agriculture, Ecosystems & Environments, 2004,103(3):545-560.

Hüttich C, Herold M, Schmullius C, et al. Indicators of Northern Eurasia's land-cover change trends from SPOT-VEG ETATION time-series analysis 1998-2005[J]. International Journal of Remote Sensing, 2007, 248(18):4199-4206.

Symeonakis E, Drake N. Monitoring desertification and land degradation over sub-Saharan Africa[J]. International Journal of Remote Sensing, 2004,25(3):573-592.

Baldocchi D, Falge E, Gu L, et al. FLUXNET:A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities[J]. Bulletin of the American Meteorological Society, 2001,82(11):2415-2434.

Sparks T H, Aasa A, Huber K, et al. Changes and patterns in biologically relevant temperatures in Europe 1941-2000[J]. Climate Research, 2009,39(3):191-207.

Zhang Ke, Kimball J S, Mu Qiaozhen, et al. Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005[J]. Journal of Hydrology, 2009,379(1/2):92-110.

White M A, Running S W, Thornton P E. The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest[J]. International Journal of Biometeorology, 1999,42(3):139-145.

De Beurs K M, Henebry G M. Trend analysis of the Path finder AVHRR Land(PAL) NDVI data for the deserts of central Asia[J]. Geoscience and Remote Sensing Letters, IEEE, 2004,1(4):282-286.

Rogier de Jong, Sytze de Bruin, Allard de Wit. Analysis of monotonic greening and browning trends from global NDVI time-series[J]. Remote Sensing of Environment, 2011,115(2):692-702.

White M A, Thornton P E, Running S W. A continental phenology model for monitoring vegetation responses to interannual climatic variability[J]. Global Biogeochemical Cycles, 1997,11(2):217-234.

Jones M O, Kimball J S, Jones L A, Satellite passive microwave detection of North America start of season[J]. Remote Sensing of Environment, 2012,123:324-333.

Moulin S, Kergoat L, Viovy N, et al. Global-scale assessment of vegetation phenology using NOAA/AV HRR satellite measurements[J]. Journal of Climate, 1997,10(6):1154-1170.

Zhang Xiaoyang, Friedl M A, Schaaf C B, et al. Monitoring vegetation phenology using MODIS[J]. Remote Sensing of Environment, 2003,84(3):471-475.

Reed B C, White M, Brown J F. Remote sensing phenology[M]//Schwartz M D. Phenology:An Integrative Environmental Science. Dordrecht, The Netherlands:Kluwer Academic Publishing, 2003.

徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002.

Hirsch R M, Slack J R, Smith R A. Techniques of trend analysis for monthly water quality data[J]. Water Resources Research, 1982,18(1):107-121.

Alcaraz-Segura D, Liras E, Tabik S, et al. Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR Sensor:LTDR, GIMM S, FASIR, and PAL(Ⅱ)[J]. Sensors, 2010,10(2):1291-1314.

邱海军,曹明明.基于SPOT VEGETATION数据的中国植被覆盖时空变化分析[J].资源科学,2011,33(2):335-340.

程殿龙.2000年旱灾与抗旱工作[J].防汛与抗旱,2001(1):30-35.

民政部救灾处.2001年全国自然灾害和救灾工作情况[J].中国减灾,2002(1):30-33.

朴世龙,方精云.最近18年来中国植被覆盖的动态变化[J].第四纪研究,2001,21(4):294-302.

李双双,延军平,万佳.近10年陕甘宁黄土高原区植被覆盖时空变化特征[J].地理学报,2012,67(7):960-970.

何太蓉,庄红娟,刘存东.秦岭-黄淮平原交界带中东部近50年气候变化特征与趋势[J].安徽农业科学,2009,37(14):6532-6534.

王强,张勃,戴声佩.基于GIMMS AVHRR NDVI数据的三北防护林工程区植被覆盖动态变化[J].资源科学,2011,33(8):1613-1620.

浏览量

1386

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于kNDVI与结构方程模型的洞庭湖区植被覆盖时空变化及驱动机制分析

晋西北黄土丘陵沟壑区典型灌草植被土壤水分动态变化规律研究

基于SPOT-VGT数据的新疆1998-2007年植被覆盖变化监测

大巴山地区植被覆盖变化及其对气候变化的响应

水热条件和人类活动对山西省植被覆盖变化的影响