[1]王涛,田阳,相如.不同NDVI年值提取方法对秦岭山地植被变化及其气候响应的影响[J].北方园艺,2017,41(24):148-155.[doi:10.11937/bfyy.20172254]
　WANG Tao,TIAN Yang,XIANG Ru.Impact of Different Extracted Methods of Annual NDVI on Vegetation Cover Change and Their Response to Climate Change in Qinling Mountains[J].Northern Horticulture,2017,41(24):148-155.[doi:10.11937/bfyy.20172254]
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不同NDVI年值提取方法对秦岭山地植被变化及其气候响应的影响

《北方园艺》[ISSN:1001-0009/CN:23-1247/S] 卷: 第41卷 期数: 2017年24 页码: 148-155 栏目: 出版日期: 2017-12-25
Title:
Impact of Different Extracted Methods of Annual NDVI on Vegetation Cover Change and Their Response to Climate Change in Qinling Mountains
作者:
王涛1; 2; 3; 田阳4; 相如2
1.西北大学 城市与环境学院，陕西 西安 710127；2.西安科技大学 测绘科学与技术学院，陕西 西安 710054；3.黄土高原土壤侵蚀与旱地农业国家重点实验室，中国科学院 水利部水土保持研究所，陕西 杨凌 712100；4.重庆市綦江区横山镇人民政府，重庆 401460
Author(s):
WANG Tao1; 2; 3; TIAN Yang4; XIANG Ru2
1.College of Urban and Environmental Science,Northwest University,Xi′an,Shaanxi 710127；2.College of Geomatics,Xi′an University of Science and Technology,Xi′an,Shaanxi 710054；3.State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau/Institute of Water and Soil Conservation,Chinese Academy of Sciences and Ministry of Water Resources,Yangling,Shaanxi 712100；4.The People′s Government of Hengshan Town Qijiang District Chongqing Municipal,Chongqing 401460
关键词:
MODIS NDVI; MVC; 气温; 降水; 秦岭山地
Keywords:
MODIS NDVI; MVC; temperature; precipitation; Qinling Mountains
DOI:
10.11937/bfyy.20172254
文献标志码:
A
摘要:
基于2000—2014年秦岭山地MODIS NDVI影像、气温和降水数据，分别利用平均值法（AVM）、最大值合成法（MVC）、平均-最大值合成法（AMVC）、时序重建方法（RAVM）获取NDVI年值，分析了不同方法下NDVI时空变化过程与趋势，及其与气温、降水的相关性，以期为秦岭山地植被动态变化及其气候响应准确评估提供方法基础。结果表明：RAVM获取的NDVI年值效果较好，平均值居中，线性变化趋势极显著。其次为AMVC、MVC和AVM法获取的NDVI年值偏高和偏低。山地植被动态监测中，植被退化是关注的热点问题，AMVC方法计算得到的秦岭山地NDVI线性减少趋势分布面积最大，其次为MVC、RAVM、AVM方法。不同NDVI年值提取方法下，NDVI与气温的相关性具有一定的差异。如相关系数空间分散分布（MVC和RAVM）和相对集中分布（AVM和AMVC），NDVI与气温的正相关为主（AVM和RAVM）和负相关为主（MVC和AMVC）。但4种不同方法下NDVI与降水的相关性均以正相关为主，表明不同方法表现植被与降水关系具有一致性，而植被与气温的关系不稳定。
Abstract:
On the basis of the MODIS NDVI images,temperature and precipitation data from 2000 to 2014 in Qinling Mountains,the spatial and temporal variation of NDVI and the correlation between NDVI and temperature,precipitation were analyzed with 4 different extraction methods on annual NDVI value,such as AVM (Average Value Method),MVC (Maximum Value Composition),AMVC (Average-Maximum Value Composition) and RAVM method (Reconstruction-Average Value Method).This study would provide an information to accurate assessment of NDVI change in Qinling Mountains.The results showed that the RAVM was the best to extract annual value of NDVI,and the linear change trend was very significant,followed by the AMVC,while the annual value of NDVI extracted by MVC and AVM were higher and lower.Vegetation degradation was a hot issue for the monitoring of Qinling Mountains.The linear reduction trend area calculated by AMVC was the largest,followed by the MVC,RAVM and AVM.The correlation between NDVI and temperature was different to a certain extent,such as the spatial distribution of coefficient was relatively scattered (MVC and RAVM) or concentrated (AVM and AMVC),and the positive (AVM and RAVM) or negative correlation (MVC and AMVC).But the correlation between NDVI and precipitation was positive for the 4 different methods,which reflect the correlation between NDVI and precipitation was stable and unstable between NDVI and temperature.

参考文献/References:

[1]GAO X J,SHI Y,ZHANG D F,et al.Climate change in China in the 21st century as simulated by a high resolution regional climate model[J].Chinese Science Bulletin,2012,57(10):1188-1195.

[2]STOKER T F,QIN G K,PLATTNER M,et al.IPCC,2013:Summary for policy makers[A].Climate Change 2013:The physical basis.Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[R].Cambridge University Press,Cambridge,United Kingdom and New York,NY,USA.
[3]WALTHER G R,POST E,CONVEY P,et al.Ecological responses to recent climate change[J].Nature,2002,416:89-395.
[4]白红英.秦巴山区森林植被对环境变化的响应[M].北京:科学出版社,2014:1-42.
[5]GARTZIA M,CABELLO F P,BUENO C G,et al.Physiognomic and physiologic changes in mountain grassland in response to environmental and anthropogenic factors[J].Applied Geography,2016,66:1-11.
[6]LIU X,ZHU X,PAN Y,et al.Vegetation dynamics in Qinling-Daba Mountains in relation to climate factors between 2000 and 2014[J].Journal of Geographical Sciences,2016,26(1):45-58.
[7]ZHAO X,MA C,XIAO L.The vegetation history of Qinling Mountains,China[J].Quaternary International,2014,325:55-62.
[8]WESSELS K J,PRINCE S D,FROST P E,et al.Assessing the effects of human-induced land degradation in the former homelands of northern south Africa with a 1 km AVHRR NDVI time-series[J].Remote Sensing of Environment,2004,91:47-67.
[9]ZHAN Z Z,LIU H B,LI H M,et al.The relationship between NDVI and terrain factors:A case study of Chongqing[J].Procedia Environmental Science,2012,12:765-771.
[10]BOSCHETTI M,NUTINI F,BRIVIO P A,et al.Identification of environmental anomaly hot spots in west Africa from time series of NDVI and rainfall[J].ISPRS Journal of Photogrammetry and Remote Sensing,2013,78:26-40.
[11]ZHOU H,ROMPAEY A V,WANG J.Detecting the impact of the ‘Grain for Green’ program on the mean annual vegetation cover in the Shaanxi Province,China using SPOT-VGT NDVI data[J].Land Use Policy,2009,26:954-960.
[12]LI S,YANG S,LIU X,et al.NDVI-based analysis on the influence of climate change and human activities on vegetation restoration in the Shaanxi-Gansu-Ningxia region,central China[J].Remote Sensing,2015,7:11163-11182.
[13]FENSHOLT R,PROUD S R.Evaluation of earth observation based global long term vegetation trends-comparing GIMMS and MODIS global NDVI time series[J].Remote Sensing of Environment,2012,19:131-147.
[14]STEFANOV W L,NETZBAND M.Assessment of ASTER land cover and MODIS NDVI data at multiple scales for ecological characterization of an arid urban center[J].Remote Sensing of Environment,2005,99:31-43.
[15]崔晓临,白红英,王涛.秦岭地区植被NDVI海拔梯度差异及其气温响应[J].资源科学,2013,35(3):618-626.
[16]崔晓临,赵娟,白红英,等.基于MODIS NDVI的陕西省植被覆盖变化分析[J].西北农林科技大学学报(自然科学版),2013,41(5):87-93.
[17]王涛,陶辉,雷刚,等.博斯腾湖流域植被覆盖变化及驱动因素分析[J].中国农学通报,2015,31(4):228-236.
[18]王涛,杨梅焕,徐澜.陕西榆林地区植被退化与沙漠化趋势分析[J].西北师范大学学报(自然科学版),2017,53(2):104-111.
[19]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002:37-70.

备注/Memo

第一作者简介：王涛（1984-），男，河南汤阴人，博士，讲师，现主要从事区域环境变化等研究工作。E-mail：wht432@163.com.

基金项目：国家林业公益性行业科研专项资助项目（201304309）；黄土高原土壤侵蚀与旱地农业国家重点实验室开放基金资助项目（A314021402-1616）；陕西省大学生创新创业训练计划资助项目（201710704072）。
收稿日期：2017-08-01

更新日期/Last Update: 2017-12-29