基于SSA-Mann Kendall的草原露天矿区NDVI时间序列分析

doi:10.3724/SP.J.1047.2016.01110

摘要/Abstract

摘要：

针对煤矿区植被指数时间序列研究中,存在年际尺度上对植被动态规律刻画不全面、月际尺度上因物候性周期波动导致变化趋势和周期振荡信号微弱难以提取、基于变换的变化检测物理意义不够明确的问题,本文以胜利露天矿区为例,在月际尺度,基于SSA-Mann Kendall重建草原露天矿区的采矿扰动区和伪不变特征区MODIS NDVI时间序列的趋势和周期振荡信号,从显著程度和突变时间2方面对趋势成分进行定量化分析,并结合各特征区周期振荡演变特征揭示采矿扰动下草原露天矿区植被生长的动态规律。结果表明：SSA-Mann Kendall能将NDVI时间序列的微弱信号充分放大,便于提取,并可对趋势成分进行定量化表达,结合周期振荡与趋势成分的演变特征有助于辅助识别矿区植被生长的动态特点;伪不变特征区植被无显著下降趋势,采矿扰动区下降趋势显著,且露天采场较排土场的趋势更为明显,草原露天矿区地表植被损伤具有突发性,突变点多发于矿井开工建设时;扰动形式差异导致部分矿井露天采场和排土场周期振荡演变特征存在差异,露天采场植被消失殆尽,排土场因植被恢复措施而具有更复杂的动态特点。

关键词: NDVI时间序列, 奇异谱分析, Mann Kendall, 变化趋势, 周期振荡

Abstract:

Vegetation index time series have difficulty to depict the detailed response of vegetation dynamics to coal mining and the signals of change trend and periodic oscillation at an inter-annual scale. While at the monthly scale, the signals are so weak that they are hard to be extracted due to the disturbance of vegetation phenology. In addition, the physical significance of the transformation detection algorithm is still unclear. In order to solve these problems and to reveal the change trend and periodic oscillation of vegetation growth in the disturbance area of grassland open-cast mine, this paper selected Shengli open-cast mine area as an study area to extract, amplify and quantitatively compute the signals of the monthly change trend and periodic oscillation based on the MODIS NDVI time series from January 2001 to December 2013 in the mining disturbance area and the unchanged feature region. SSA-Man Kendall was adopted to extract the change trend and periodic oscillation. Moreover, we quantitatively analyzed the significant degree and jump time. For the change trend, the Sen slope of the change components were calculated, which could indicates the change direction. Then the trend significance was measured based on the results of Mann Kendall trend analysis. Combined with the moving-t test for some fuzzy catastrophe points, the time points of abrupt changes were also detected. For the periodic oscillation, it was estimated based on the utilization of power spectrum analysis. The evolution characteristics of NDVI time series′ periodic oscillation in different feature regions were also studied. The results show that SSA-Mann Kendall can effectively extract the signals of change trend and be competent in depicting the periodic oscillation at different time scales, as well as quantitatively express the change trend signals. A downward trend of NDVI time series in the stopes is significant, and it is more significant than the waste dumps within the same mine area, while the trend in the unchanged feature region is relative stable. In addition, damage of vegetation is a sudden event in the grassland opencast mine area, and the catastrophe points of NDVI time series usually occur at the beginning of the mine construction. In the partial open-cast mines, NDVI time series′ periodic oscillation in the stopes and waste dumps are different, which are related to the different disturbance forms within these areas. In particular, the vegetation almost vanishes in the stopes with coal mining, however, the dynamics of vegetation growth are more complex in the waste dumps due to the effective vegetation restoration.

Key words: NDVI time series, singular spectrum analysis, Mann Kendall, trend of change, periodic oscillation

贾铎, 牟守国, 赵华. 基于SSA-Mann Kendall的草原露天矿区NDVI时间序列分析[J]. 地球信息科学学报, 2016, 18(8): 1110-1122.DOI:10.3724/SP.J.1047.2016.01110

JIA Duo,MU Shouguo,ZHAO Hua. Analysis of NDVI Time Series in Grassland Open-cast Coal Mines Based on SSA-Mann Kendall[J]. Journal of Geo-information Science, 2016, 18(8): 1110-1122.DOI:10.3724/SP.J.1047.2016.01110

图/表 13

图1

表1

表2

图2

图3

表3

露天矿区各特征区NDVI时间序列变化趋势及突变时间[27]

特征区	地点	方差贡献率/（%）	$β$	M-K	变化趋势	突变时间/月
露天采场	东三号露天矿	30.43	-0.00829	-8.9110	下降	89
	西三号露天矿	20.67	-0.00094	-11.3752	下降	124
	西一号露天矿	19.88	-0.00175	-3.7253	下降	124
	露天锗矿	24.38	-0.00170	-5.7451	下降	122
排土场	东三号露天矿	17.84	-0.00148	-8.6812	下降	114
	西三号露天矿	19.93	-0.00336	-6.3153	下降	101
	西一号露天矿	17.89	-0.00066	-3.3851	下降	71
	露天锗矿	59.59	-0.00392	-9.3554	下降	90
伪不变特征区	植被覆盖区域	14.57	-0.00027	-1.4573	-	-

表3

图4

图5

表4

图6

图7

图8

图9

参考文献 27

[1]	赵英时. 遥感应用分析原理与方法[M].北京:科学出版社,2003:387-396.
	[ Zhao Y S.Theory and method of remote sensing application and analysis[M]. Beijing: Science Press, 2003:387-396. ]
[2]	侯学会,牛铮,高帅.近十年中国东北森林植被物候遥感监测[J].光谱学与光谱分析,2014,34(2):515-519. doi: 10.3964/j.issn.1000-0593(2014)02-0515-05
	[ Hou X H, Niu Z, Gao S.Phenology of forest vegetation in northeast of China in ten years using remote sensing[J]. Spectroscopy and Spectral Analysis, 2014,34(2):515-519. ] doi: 10.3964/j.issn.1000-0593(2014)02-0515-05
[3]	Chen B Z, Xu G, Coops N C, et al.Changes in vegetation photosynthetic activity trends across the Asia-Pacific region over the last three decades[J]. Remote Sensing of Environment, 2014,144:82-41. doi: 10.1016/j.rse.2013.12.018
[4]	贾明明,任春颖,刘殿伟,等.基于环境星与MODIS时序数据的面向对象森林植被分类[J].生态学报,2014,34(24):7167-7174. doi: 10.5846/stxb201310112438
	[ Jia M M, Ren C Y, Liu D W, et al.Object-oriented forest classification based on combination of HJ-1 CCD and MOD1S-NDVI data[J]. Acta Ecologica Sinica, 2014,34(24):7167-7174. ] doi: 10.5846/stxb201310112438
[5]	Brown J, Kastens H J, Coutinho A C, et al.Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data[J]. Remote Sensing of Environment, 2013,130:39-50. doi: 10.1016/j.rse.2012.11.009
[6]	Ma X L, Huete A, Yu Q, et al.Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect[J]. Remote Sensing of Environment, 2013,139:97-115. doi: 10.1016/j.rse.2013.07.030
[7]	Jamali S, Jönsson P, Eklundh L, et al.Detecting changes in vegetation trends using time series segmentation[J]. Remote Sensing of Environment, 2015,156:182-195. doi: 10.1016/j.rse.2014.09.010
[8]	李晶,Carl E Z,李松,等.基于时序NDVI的露天煤矿区土地损毁与复垦过程特征分析[J].农业工程学报,2015,31(16):251-257.
	[ Li J, Carl E Z, Li S, et al.Character analysis of mining disturbance and reclamation trajectory in surface coal-mine area by time-series NDVI[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015,31(16):251-257. ]
[9]	Djebou D C, Singh P V, Frauenfeld W O.Vegetation response to precipitation across the aridity gradient of the southwestern United States[J]. Journal of Arid Environments, 2015,15:35-43. doi: 10.1016/j.jaridenv.2015.01.005
[10]	郭笑怡,刘德赢,张洪岩.大兴安岭NDVI时间序列的长程相关性特征分析[J].地球信息科学学报,2013,15(1):152-158. doi: 10.3724/SP.J.1047.2013.00152
	[ Guo X Y, Liu D Y, Zhang H Y.Detecting long-range correlations in NDVI over Greater Khingan Mountains[J]. Journal of Geo-information Science, 2013,15(1):152-158. ] doi: 10.3724/SP.J.1047.2013.00152
[11]	蔡博峰,于嵘.基于遥感的植被长时序趋势特征研究进展及评价[J].遥感学报,2009,13(6):1170-1186.
	[ Cai B F, Yu R.Advance and evaluation in the long time series vegetation trends research based on remote sensing[J]. Journal of Remote Sensing, 2009,13(6):1170-1186. ]
[12]	Wessels K J, Prince S D, Malherbe J, et al.Can human-induced land degradation be distinguished from the effects of rainfall variability? a case study in South Africa[J]. Journal of Arid Environments, 2007,68(2):271-297. doi: 10.1016/j.jaridenv.2006.05.015
[13]	刘亚龙,王庆,张明明,等.山东地区NDVI与气象因子持续性分析[J].资源科学,2010,32(9):1777-1782.
	[ Liu Y L, Wang Q, Zhang M M, et al.Analysis of the persistence of NDVI and climatic factors in the Shandong Peninsular[J]. Resources Science, 2010,32(9):1777-1782. ]
[14]	王澄海,崔洋.西北地区近50年降水周期的稳定性分析[J].地球科学进展,2006,21(6):576-584.
	[ Wang C H, Cui Y.A study of the stability of the precipitation cycle over northwest China in the past 50 years[J]. Advances in Earth Science, 2006,21(6):576-584. ]
[15]	Golyandina N, Korobeynikov A.Basic singular spectrum analysis and forecasting with R[J]. Computational Statistics and Data Analysis, 2014,71:934-954. doi: 10.1016/j.csda.2013.04.009
[16]	殷守敬,吴传庆,王桥,等.多时相遥感影像变化检测方法研究进展综述[J].光谱学与光谱分析,2013,33(12):3339-3342. doi: 10.3964/j.issn.1000-0593(2013)12-3339-04
	[ Yin S J, Wu C, Wang Q, et al.Review of change detection methods using multi-temporal remotely sensed images[J]. Spectroscopy and Spectral Analysis, 2013,33(12):3339-3342. ] doi: 10.3964/j.issn.1000-0593(2013)12-3339-04
[17]	LPDAAC. MODIS user guide[EB/OL]. .
[18]	Jönsson P, Eklundh L.TIMESAT-a program for analyzing time-series of satellite sensor data[J]. Computers and Geosciences, 2004,30(8):833-845. doi: 10.1016/j.cageo.2004.05.006
[19]	Helldén U, Christian T.Regional desertification: a global synthesis[J]. Global and Planetary Change, 2008,64(3-4):169-176. doi: 10.1016/j.gloplacha.2008.10.006
[20]	毕如田,白中科.基于遥感影像的露天煤矿区土地特征信息及分类研究[J].农业工程学报,2007,23(2):77-82.
	[ Bi R T, Bai Z K.Land characteristic information and classification in opencast coal mine based on remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering, 2007,23(2):77-82. ]
[21]	Tabari H, Talaee P H.Temporal variability of precipitation over Iran: 1966-2005[J]. Journal of Hydrology, 2011,396(3-4):313-320. doi: 10.1016/j.jhydrol.2010.11.034
[22]	魏凤英. 现代气候统计诊断与预测技术[M].北京:气象出版社,2007:71-76.
	[ Wei F Y.Modern climatic statistical diagnosis and forecasting technology[M]. Beijing: China Meteorological Press, 2007:71-76. ]
[23]	Vautard R, Yiou P, Ghil M.Singular spectrum analysis: a toolkit for short, noisy chaotic signals[J]. Physica D: Nonlinear Phenomena, 1982,58(1):95-126. doi: 10.1016/0167-2789(92)90103-T
[24]	徐克红,程鹏飞,文汉江.太阳黑子数时间序列的奇异谱分析和小波分析[J].测绘科学,2007,32(6):35-38. doi: 10.3771/j.issn.1009-2307.2007.06.011
	[ Xu K H, Cheng P F, Wen H J.Singular spectrum analysis and wavelet analysis on time series of Sunspot[J]. Science of Surveying and Mapping, 2007,32(6):35-38. ] doi: 10.3771/j.issn.1009-2307.2007.06.011
[25]	李常斌,王帅兵,杨林山,等.1951-2010年洮河流域水文气象要素变化的时空特征[J].冰川冻土,2013,35(5):1259-1266. doi: 10.7522/j.issn.1000-0240.2013.0142
	[ Li C B, Wang S B, Yang L S, et al.Spatial and temporal variation of main hydrologic meteorological elements in the Taohe River basin from 1961 to 2010[J]. Journal of Glaciology and Geocryology, 2013,35(5):1259-1266. ] doi: 10.7522/j.issn.1000-0240.2013.0142
[26]	Qi W, Zhang Y L, Gao J G, et al.Climate change on the southern slope of Mt.Qomolangma (Everest) region in Nepal since 1971[J]. Journal of Geographical Sciences, 2013,23(4):595-611. doi: 10.1007/s11442-013-1031-9
[27]	王园香,唐世浩,郑照军.1982-2006年中国5-9月的NDVI变化与人类活动影响分析[J].地球信息科学学报,2015,17(11):1333-1340. doi: 10.3724/SP.J.1047.2015.01333
	[ Wang Y X, Tang S H, Zheng Z J.Analysis of NDVI and the impact of human activity in China from may to september during 1982 to 2006[J]. Journal of Geo-information Science, 2015,17(11):1333-1340. ] doi: 10.3724/SP.J.1047.2015.01333

比特位	含义	比特位	含义	比特位	含义
0-1	VI质量总评	8	云边界	11-13	陆地/水域标记
2-5	VI可用性	9	大气二向性校正	14	雪/冰
6-7	气溶胶含量	10	混合云	15	云阴影

VI质量总评指数	质量描述	权重
0	产生质量较高的植被指数数据	1
1	产生植被指数但需参考其他QA数据	0.6
2	产生植被指数但大部分像元受云影响	0.2
3	因其他原因无植被指数	0

特征区	重建成分组合	贡献率/(%)	周期/月	重建成分组合	贡献率/(%)	周期/月	重建成分组合	贡献率/(%)	周期/月
东三号露天矿采场	R4+R5+R6	13.30	11.1	R2+R3	12.33	31.2	R7+R8	6.16	13
东三号露天矿排土场	R2+R3	13.16	10.4	R4+R5+R9	13.00	6	R6+R7+R8	10.48	14
西一号露天矿采场	R2+R3+R4	19.47	13	R5+R6	9.61	11.1	R7+R8	8.80	7.8
西一号露天矿排土场	R2+R3+R4	28.01	12	R5+R6+R7	13.93	6	R8+R9	8.01	-
西二号露天矿采场	R2+R3	16.43	10.4	R4+R5+R6	15.67	5.5	R7+R8	6.29	-
西二号露天矿排土场	R2+R3+R4	21.01	10.4	R7+R8+R9	9.54	-	R5+R6	8.43	39
露天锗矿采场	R2+R3	11.78	9	R5+R6+R7	10.45	12	R4+R8+R9	10.37	-
露天锗矿排土场	R3+R4	11.18	13	R5+R6	10.44	11.1	R7+R8+R9	5.20	-