西北干旱区植被覆盖时空动态特征

doi:10.13466/j.cnki.lyzygl.2017.01.020

摘要/Abstract

摘要：

用MODIS NDVI数据2000—2015年的归一化植被指数产品,运用变异系数、Theil-Sen median趋势分析耦合Mann-Kendall检验和Hurst指数法,探讨了中国西北干旱区植被覆盖的时空变化特征及未来趋势的预测。研究表明:1)2000—2015年全区植被覆盖的空间异质性较强,有植被覆盖的区域占总面积的35.59%,无植被覆盖的区域占64.41%。受降水的影响,植被覆盖整体呈东南高西北低、山区高平原低的特点;受河流和人工灌溉的影响,绿洲区水热组合条件好,其植被覆盖高于荒漠区。2)近16年全区植被覆盖波动变化不明显,各亚区的波动普遍较低,变异系数小于0.10的比例均超过总面积的1/2。3)16年间全区植被覆盖总体有增长趋势,变化率为0.006/10a。基于像元尺度的分析也表明全区植被覆盖以增长趋势为主,各亚区中河西走廊的增长面积最多,北疆的增长面积最少,均超过1/2。4)全区NDVI的Hurst指数均值为0.73,Hurst指数大于0.5的范围所占比例为86.25%,未来全区植被覆盖的变化趋势以持续性增加为主,其中13.46%区域的未来趋势无法确定。各亚区呈不同程度的增加趋势,河西走廊的增加趋势最明显,北疆的增加趋势相对较弱。

关键词: MODIS, 归一化植被指数, 西北干旱区, 趋势分析, 降水量

Abstract:

Based on the MODIS NDVI data of the normalized difference vegetation index products obtained between 2000 and 2015,Variable coefficient,Theil-Sen median trend analysis,Mann-Kendall test method and Hurst index method were utilized for research on the temporal-spatial dynamic change characteristics of vegetation coverage in the arid region of Northwest China and the future trends. The results showed:1)the vegetation coverage in the entire region has a strong spatial heterogeneity,the area of vegetation and bare fallow accounts for 35.59% and 64.41% of the total area,respectively. Affected by precipitation,higher value area of NDVI is mainly in the mountains and southeastern region which have a rich rainfall,the low value areas of NDVI are concentrated on plains and northwestern region which have a poor rainfall;Influenced by rivers and irrigation,the vegetation coverage of desert is lower than the oasis which has the better hydrothermal conditions. 2)the variation degree of the entire regional vegetation coverage in the recent 16 years was not obvious. The fluctuation in each subregion is slight,and the proportion of region where the variation degree is less than 0.10 is as high as 1/2. 3)the entire regional vegetation coverage in the recent 16 years shows fluctuation changes which have a increase trend,the change rate is 0.006/10a. The analysis based on the pixel scale also shows a increase trend,the area of increase trend in Hexi Corridor is the largest and in Northern Xinjiang is the least. 4)Hurst index average of the entire regional NDVI is 0.73. The scope of Hurst index greater than 0.5 accounts for 86.25%. The change trend of the entire regional vegetation coverage in the future is mainly in persistent increase. Among them,13.46% area change trend cannot be determined. The change trend in the future of the increase degree in each subregion is different,the increase trend in Hexi Corridor is the most obvious and in Northern Xinjiang is the least.

Key words: MODIS, normalized difference vegetation index, the arid region of Northwest China, trend analysis, precipitation

中图分类号:

S718.45

赵晶, 周耀治, 邓兴耀. 西北干旱区植被覆盖时空动态特征[J]. 林业资源管理, 2017, 0(1): 118-126.

ZHAO Jing, ZHOU Yaozhi, DENG Xingyao. Temporal-spatial Dynamic Change Characteristics of Vegetation Coverage in Arid Regions of Northwest China[J]. FOREST RESOURCES WANAGEMENT, 2017, 0(1): 118-126.

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参考文献 26

[1]	Meyer W B, Turner B L . Human population growth and global land-use/cover change[J]. Annual Review of Ecology and Systematics, 1992,23(1):39-61. doi: 10.1146/annurev.es.23.110192.000351
[2]	Gutman G, Ignatov A . The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models[J]. International Journal of Remote Sensing, 1998,19(8):1533-1543. doi: 10.1080/014311698215333
[3]	Fensholt R, Rasmussen K, Nielsen T , et al. Evaluation of earth observation based long term vegetation trends—Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS,Terra MODIS and SPOTVGT data[J]. Remote Sensing of Environment, 2009,113(9):1886-1898. doi: 10.1016/j.rse.2009.04.004
[4]	Huete A, Didan K, Miura T , et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices[J]. Remote Sensing of Environment, 2002,83(1):195-213. doi: 10.1016/S0034-4257(02)00096-2
[5]	姚俊强, 杨青, 陈亚宁 , 等. 西北干旱区气候变化及其对生态环境影响[J]. 生态学杂志, 2013,32(5):1283-1291.
[6]	Myneni R B, Keeling C D, Tucker C J , et al. Increased plant growth in the Northern high latitudes from 1981 to 1991[J]. Nature, 1997,386(6626):698-702. doi: 10.1038/386698a0
[7]	Peng S, Chen A, Xu L , et al. Recent change of vegetation growth trend in China[J]. Environmental Research Letters, 2011,6(4):44027-44039. doi: 10.1088/1748-9326/6/4/044027
[8]	陈亚宁, 李稚, 范煜婷 , 等. 西北干旱区气候变化对水文水资源影响研究进展[J]. 地理学报, 2014,69(9):1295-1304. doi: 10.11821/dlxb201409005
[9]	王海军, 靳晓华, 李海龙 , 等. 基于GIS和RS的中国西北NDVI变化特征及其与气候变化的耦合性[J]. 农业工程学报, 2010,26(11):194-203.
[10]	李奇虎, 陈亚宁 . 1981—2006年西北干旱区NDVI时空分布变化对水热条件的响应[J]. 冰川冻土, 2014,36(2):327-334. doi: 10.7522/j.issn.1000-0240.2014.0040
[11]	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[J]. 中国沙漠, 2014,34(6):1665-1670. doi: 10.7522/j.issn.1000-694X.2014.00032
[12]	王玮, 冯琦胜, 郭铌 , 等. 基于长时间序列NDVI资料的我国西北干旱区植被覆盖动态监测[J]. 草业科学, 2015,32(12):1969-1979. doi: 10.11829/j.issn.1001-0629.2015-0459
[13]	姚俊强, 杨青, 刘志辉 , 等. 中国西北干旱区降水时空分布特征[J]. 生态学报, 2015,35(17):5846-5855. doi: 10.5846/stxb201310242567
[14]	美国国家航天航空局[DB/OL].( 2016 -06-05) [2003-01-01].https://ladsweb.nascom.nasa.gov.
[15]	杜加强, 高云, 贾尔恒 , 等. 近30年新疆植被生长异常值时空变化及驱动因子[J]. 生态学报, 2015,36(7):1915-1927.
[16]	中国科学院数据云[DB/OL].( 2016- 06- 05) [2007-07-01].http://www.csdb.cn/ .
[17]	英国East Anglia大学气候研究中心[DB/OL].( 2016- 06- 05) [2015-06-25].http://www.uea.ac.uk/ .
[18]	Milich L, Weiss E . GAC NDVI interannual coefficient of variation (CoV) images:ground truth sampling of the Sahel along north-south transects[J]. International Journal of Remote Sensing, 2000,21(2):235-260. doi: 10.1080/014311600210812
[19]	Jiang W G, Yuan L H, Wang W J , et al. Spatio-temporal analysis of vegetation variation in the Yellow River Basin[J]. Ecological Indicators, 2015,51:117-126. doi: 10.1016/j.ecolind.2014.07.031
[20]	Yue S, Pilon P, Cavadias G . Power of the Mann-Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series[J]. Journal of Hydrology, 2002,259(1):254-271. doi: 10.1016/S0022-1694(01)00594-7
[21]	Fensholt R, Langanke T, Rasmussen K , et al. Greenness in semi-arid areas across the globe 1981-2007—An earth observing satellite based analysis of trends and drivers[J]. Remote Sensing of Environment, 2012,121:144-158. doi: 10.1016/j.rse.2012.01.017
[22]	Jiapaer G, Liang S L, Yi Q X , et al. Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator[J]. Ecological Indicators, 2015,58:64-76. doi: 10.1016/j.ecolind.2015.05.036
[23]	Zhou L, Tucker C J, Kaufmann R K , et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research:Atmospheres, 2001,106(D17):20069-20083. doi: 10.1029/2000JD000115
[24]	郭铌, 朱燕君, 王介民 , 等. 近22年来西北不同类型植被NDVI变化与气候因子的关系[J]. 植物生态学报, 2008,32(2):319-327. doi: 10.3773/j.issn.1005-264x.2008.02.008
[25]	张琪, 袁秀亮, 陈曦 , 等. 1982-2012年中亚植被变化及其对气候变化的响应[J]. 植物生态学报, 2016,40(1):13-23. doi: 10.17521/cjpe.2015.0236
[26]	Piao S, Wang X, Ciais P , et al. Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006[J]. Global Change Biology, 2011,17(10):3228-3239. doi: 10.1111/j.1365-2486.2011.02419.x

NDVI	占总面积百分比/%	北疆/%	天山/%	南疆/%	祁连山/%	河西走廊/%	内蒙西部/%
<0.1	64.41	22.18	20.76	83.52	23.69	71.86	79.74
0.1≤NDVI<0.2	20.46	44.82	28.91	10.80	37.17	20.75	19.29
0.2≤NDVI<0.3	6.20	14.63	17.46	2.52	15.88	3.55	0.59
0.3≤NDVI<0.4	4.98	12.76	13.37	1.97	11.19	2.91	0.20
0.4≤NDVI<0.5	3.05	5.17	12.40	1.14	9.88	0.93	0.14
≥0.5	0.90	0.44	7.10	0.04	2.19	0.00	0.04

CV_NDVI	变异程度	占总面积百分比	北疆	天山	南疆	祁连山	河西走廊	内蒙西部
CV_NDVI≤0.05	低波动变化	28.83	6.99	10.62	34.97	11.90	25.82	55.71
0.05<CV_NDVI≤0.10	相对较低的波动变化	43.18	48.28	47.19	41.28	46.31	49.18	35.06
0.10<CV_NDVI≤0.15	中等波动变化	17.47	28.62	27.16	13.44	31.07	17.59	7.87
0.15<CV_NDVI≤0.20	相对较高的波动变化	5.38	9.51	7.48	4.66	6.73	4.81	0.92
CV_NDVI>0.20	高波动变化	5.13	6.60	7.55	5.65	3.99	2.60	0.44

β	\|Z_c\|	NDVI变化趋势	占总面积百分比	北疆	天山	南疆	祁连山	河西走廊	内蒙西部
β<0	\|Z_c\|>1.96	显著减小	2.34	3.43	5.23	1.56	0.32	0.91	3.47
β<0	\|Z_c\|≤1.96	轻微减小	17.19	40.66	33.60	10.41	6.24	5.42	12.87
β>0	\|Z_c\|≤1.96	轻微增加	61.25	44.97	54.68	66.95	66.40	59.72	63.49
β>0	\|Z_c\|>1.96	显著增加	19.22	10.94	6.49	21.08	27.03	33.96	20.17

β	\|Z_c\|	H	NDVI预测的类型	占总面积百分比	北疆	天山	南疆	祁连山	河西走廊	内蒙西部
β<0	\|Z_c\|>1.96	>0.5	持续性显著减小	2.29	3.37	5.14	1.53	0.31	0.89	3.32
β<0	\|Z_c\|≤1.96	>0.5	持续性轻微减小	12.65	30.34	24.66	7.36	3.76	4.45	10.21
β>0	\|Z_c\|≤1.96	>0.5	持续性轻微增加	52.49	32.79	40.11	58.80	54.89	56.16	58.72
β>0	\|Z_c\|>1.96	>0.5	持续性显著增加	19.10	10.81	6.20	20.98	26.78	33.93	20.13
—	—	<0.5	无法确定	13.46	22.69	23.89	11.33	14.27	4.57	7.61