摘要
遥感技术作为对大尺度陆表监测研究的有效手段,被广泛应用于自然地理环境各要素的研究中。其中,植被物候作为自然界规律性、周期性的事件,对自然环境尤其是气候变化有着重要的指示作用。以陕西省为研究区,采用Savitzky-Golay(S-G)滤波方法对MODIS归一化植被指数(normalized difference vegetation index,NDVI)数据进行时间序列重构,并在此基础上,提取陕西省2001—2016年间的植被物候期信息进行其时空变化特征分析。研究结果表明:(1)陕西省的植被物候空间分布特征与其不同地形地貌的空间分布具有较好的一致性;(2)陕西省生长季开始的平均时间在每年的第120天,生长季结束的平均时间在第280天,生长季长度平均为160 d;(3)2001—2016年间陕西省植被生长季开始时间变化趋势为波动提前,变化率约为-0. 79 d/a(R2=0. 40,P <0. 01),生长季结束时间变化趋势表现为波动推迟,变化率约为0. 50 d/a(R2=0. 25,P <0. 05),生长季长度变化呈波动延长趋势,变化率约为1. 29 d/a(R2=0. 37,P <0. 05);(4)在不同的物候期,陕西省植被的物候变化趋势空间分布差异较大。
Remote sensing has been widely used in the study of natural geographical environment as an effective method to monitor the large-scale of surface. Among them,as a regular and periodic event in nature,vegetation phenology plays an important role in the natural environment,especially climate change. With Shaanxi Province as the study area and on the basis of the time series reconstruction of the MODIS NDVI data by using the Savitzky-Golay filtering method,the authors extracted and analyzed the vegetation phenology parameters of Shaanxi Province for the spatio-temporal changes from 2001 to 2016. The conclusions are as follows:(1) The spatial distribution characteristics of vegetation phenology are in good agreement with the spatial distribution of different landforms in Shaanxi Province.(2)The average start of season(SOS) was on the 120 th day,the average end of season(EOS)was on the 280 th day,and the average length of season(LOS) was 160 days;(3) From 2001 to 2016,the change of SOS was-0. 79 d/a(R2= 0. 4,P < 0. 01),the EOS was 0. 50 d/a(R2= 0. 25,P < 0. 05),and the LOS was1. 29 d/a(R2= 0. 37,P < 0. 05);(4) In the period of different phenological stages,the spatial distribution of phenological change trend of vegetation in Shaanxi Province is relatively large.
作者
韩红珠
白建军
张波
马高
HAN Hongzhu;BAI Jianjun;ZHANG Bo;MA Gao(School of Geography and Tourism, Shaanxi Normal University, Xi'an 710062, China;National Demonstration Center for Experimental Geography Education, Shaanxi Normal University, Xi'an 710062,China;China Academy of Space Technology Xi'an , Xi'an 110000, China)
出处
《国土资源遥感》
CSCD
北大核心
2018年第4期125-131,共7页
Remote Sensing for Land & Resources
基金
国家自然科学基金项目“基于格网的空间要素多层次关联与融合研究”(编号:41171310)
陕西省自然科学基础研究计划项目“土壤质地、作物类型及物候期对遥感干旱指数的影响--以陕西省为例”(编号:2016MJ4016)共同资助。
关键词
NDVI
物候
时空变化
陕西省
NDVI
phenology
spatio - temporal variation
Shaanxi Province