2001-2015年中国植被覆盖人为影响的时空格局
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摘要
基于MODIS-NDVI和气温、降水数据,使用基于变异系数的人为影响模型定量计算了2001-2015年中国植被覆盖人为影响,辅以趋势分析、Hurst指数等方法探讨了中国植被覆盖人为影响的时空变化特征及未来演变趋势。研究发现:①2001-2015年,中国植被覆盖人为影响由南向北空间分异愈发明显,年均值为-0.0102,植被覆盖在人类活动影响下轻微减少,负影响面积占51.59%,略大于正影响面积。②中国植被覆盖人为影响年际变化特征明显,整体呈负影响波动减少趋势,降速为0.5%/10a,其中正影响、负影响均呈增大趋势,正影响增速(0.3%/10a)远大于负影响(0.02%/10a)。③2001-2015年间,中国植被覆盖人为正影响重心向东北方向移动,负影响重心向西南方向移动,东北部植被覆盖在人为影响下不断改善,西南部人类活动对植被破坏程度不断增大。④中国植被覆盖人为影响主要呈负影响减少和正影响增大趋势,面积占比分别为28.14%和25.21%,生态环境趋于改善。⑤Hurst指数分析表明,中国植被覆盖人为影响未来演变趋势的反向特征强于正向特征,主要呈人为负影响先减少后增大趋势,面积占比15.59%。
Based on MODIS-NDVI and climate data, using an artificial influence model based on coefficient of variation to quantitatively calculate the human impact of vegetation cover(NDVIH) in China from 2001 to 2015, Sen+Mann-Kendall model and Hurst index were used to analyze the spatial-temporal feature and the future trends. It was found that:(1) In the year from 2001 to 2015, the Spatial Differentiation of NDVIH in China was more obvious from southern part to northern part, with an average annual mean value of-0.0102, the vegetation coverage decreased slightly under human activities, the negative impact area accounting for51.59% which is slightly larger than the positive impact area.(2) The interannual variation of NDVIH in China is obvious, showing the negative impact volatility decreased, the rate of decline is 0.5%/10 a; among which the positive and negative effects all showed an increasing trend, the positive growth rate(0.3%/10 a) is much larger than the negative impact(0.02%/10 a).(3) During 2001-2015, the center of gravity of positive impact has moved to the northeast, the center of gravity of negative impact has moved to the southwest, vegetation cover in northeastern China has improved under the influence of mankind, and human activities in the southwest have increased the degree of vegetation destruction.(4) The proportion of "negative impact reduction" and "positive impact increase" trend of NDVIH in China appeared to be the largest which accounting for 28.14% and 25.21% of the total, and the ecological environment is improving.(5) The reverse characteristics of NDVIH change were stronger than the same characteristic in China, mainly showed a negative impact which decreased at the first and then increased with the rate of 15.59% of the total area.
Based on MODIS-NDVI and climate data, using an artificial influence model based on coefficient of variation to quantitatively calculate the human impact of vegetation cover(NDVIH) in China from 2001 to 2015, Sen+Mann-Kendall model and Hurst index were used to analyze the spatial-temporal feature and the future trends. It was found that:(1) In the year from 2001 to 2015, the Spatial Differentiation of NDVIH in China was more obvious from southern part to northern part, with an average annual mean value of-0.0102, the vegetation coverage decreased slightly under human activities, the negative impact area accounting for51.59% which is slightly larger than the positive impact area.(2) The interannual variation of NDVIH in China is obvious, showing the negative impact volatility decreased, the rate of decline is 0.5%/10 a; among which the positive and negative effects all showed an increasing trend, the positive growth rate(0.3%/10 a) is much larger than the negative impact(0.02%/10 a).(3) During 2001-2015, the center of gravity of positive impact has moved to the northeast, the center of gravity of negative impact has moved to the southwest, vegetation cover in northeastern China has improved under the influence of mankind, and human activities in the southwest have increased the degree of vegetation destruction.(4) The proportion of "negative impact reduction" and "positive impact increase" trend of NDVIH in China appeared to be the largest which accounting for 28.14% and 25.21% of the total, and the ecological environment is improving.(5) The reverse characteristics of NDVIH change were stronger than the same characteristic in China, mainly showed a negative impact which decreased at the first and then increased with the rate of 15.59% of the total area.
引文
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[8]Wei Zhenfeng,Wang Deguang,Zhang Chong,et al.Response of vegetation cover to climate change and human activities in Northwest China during 1999-2010.Journal of Desert Research,2014,34(6):1665-1670.[韦振锋,王德光,张翀,等.1999-2010年中国西北地区植被覆盖对气候变化和人类活动的响应.中国沙漠,2014,34(6):1665-1670.]
[9]Li Shuangshuang,Yan Junping,Wan Jia.The spatial-temporal changes of vegetation restoration on Loess Plateau in Shaanxi-Gansu-Ningxia Region.Acta Geographica Sinica,2012,67(7):960-970.[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.地理学报,2012,67(7):960-970.]
[10]Wardlow B D,Egbert S L.Large-area crop mapping using time-series MODIS 250m NDVI data:An assessment for the U.S.Central Great Plains.Remote Sensing of Environment,2008,112(3):1096-1116.
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[13]Luo Min,Guli Jiapaer,Guo Hao,et al.Spatial-temporal variation of growing-season NDVI and its responses to hydrothermal condition in the Tarim River Basin from 2000 to 2013.Journal of Natural Resources,2017,32(1):50-63.[罗敏,古丽·加帕尔,郭浩,等.2000-2013年塔里木河流域生长季NDVI时空变化特征及其影响因素分析.自然资源学报,2017,32(1):50-63.]
[14]Li Huixia,Liu Guohua,Fu Bojie.Response of vegetation to climate change and human activity based on NDVI in the Three-river Headwaters Region.Acta Ecologica Sinica,2011,31(19):5495-5504.[李辉霞,刘国华,傅伯杰.基于NDVI的三江源地区植被生长对气候变化和人类活动的响应研究.生态学报,2011,31(19):5495-5504.]
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[16]Holben B.Characteristics of maximum-value composite images from temporal AVHRR data.International Journal of Remote Sensing,1986,7(11):1417-1434.
[17]Li Fei,Zeng Yuan,Li Xiaosong,et al.Remote sensing based monitoring of terrestrial variations in vegetation activity in China from 1982 to 2009.Science China:Earth Sciences,2014,44(8):1671-1678.[李飞,曾源,李晓松,等.近30年中国陆地植被活动遥感监测.中国科学:地球科学,2014,44(8):1671-1678.]
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[19]Bai Hongying,Ma Xingping,Gao Xiang,et al.Variations in January temperature and 0°C isothermal curve in Qinling Mountains based on DEM.Acta Geographica Sinica,2012,67(11):1443-1450.[白红英,马新萍,高翔,等.基于DEM的秦岭山地1月气温及0℃等温线变化.地理学报,2012,67(11):1443-1450.]
[20]Wang Siwei,Liu Yong,Zhu Chaohong,et al.Contrast on different spatial interpolation methods of Daily Surface Temperature Data in terrain complex area,Qinghai Province.Plateau Meteorology,2011,30(6):1640-1646.[王思维,刘勇,朱超洪,等.青海省逐日地面气温数据不同插值方法的对比.高原气象,2011,30(6):1640-1646.]
[21]Zeng Hongwei,Li Lijuan,Zhang Yongxuan,et al.Study on spatial interpolation of precipitation with large scale samples:A case study on 2009's precipitation of China.Progress in Geography,2011,30(7):811-818.[曾红伟,李丽娟,张永萱,等.大样本降水空间插值研究:以2009年中国年降水为例.地理科学进展,2011,30(7):811-818.]
[22]Li Chuanhua,Zhao Jun,Shi Yinfang,et al.The impact of human activities on net primary productivity based on the coefficient of variation:A case study of the Shiyang River Basin.Acta Ecologica Sinica,2016,36(13):4034-4044.[李传华,赵军,师银芳,等.基于变异系数的植被NPP人为影响定量研究:以石羊河流域为例.生态学报,2016,36(13):4034-4044.]
[23]Li Chuanhua,Zhao Jun.Spatiotemporal variations of vegetation NPP and related driving factors in Shiyang River Basin of Northwest China in 2000-2010.Chinese Journal of Ecology,2013,32(3):712-718.[李传华,赵军.2000-2010年石羊河流域NPP时空变化及驱动因子.生态学杂志,2013,32(3):712-718.]
[24]Zhao Zhuowen,Zhang Lianpeng,Li Xing,et al.Monitoring vegetation dynamics during the growing season in Ningxia based on MOD13Q1 data.Progress in Geography,2017,36(6):741-752.[赵卓文,张连蓬,李行,等.基于MOD13Q1数据的宁夏生长季植被动态监测.地理科学进展,2017,36(6):741-752.]
[25]Sen P K.Estimates of the regression coefficient based on Kendall's Tau.Journal of the American Statistical Association,1968,63(324):1379-1389.
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