Evaluation of Three MODIS-Derived Vegetation Index Time Series for Dryland Vegetation Dynamics Monitoring

被引:81
作者
Lu, Linlin [1 ]
Kuenzer, Claudia [2 ]
Wang, Cuizhen [3 ]
Guo, Huadong [1 ]
Li, Qingting [1 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth RADI, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] German Aerosp Ctr DLR, German Remote Sensing Data Ctr DFD, D-82234 Wessling, Germany
[3] Univ S Carolina, Dept Geog, Columbia, SC 29208 USA
基金
中国国家自然科学基金;
关键词
MODIS; vegetation index; dryland; vegetation dynamics; time series; phenology; SATELLITE DATA; CLOUD MASK; NDVI DATA; PHENOLOGY; XINJIANG; COVER; SAHEL; VARIABILITY; SAVANNA; CLIMATE;
D O I
10.3390/rs70607597
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding the spatial and temporal dynamics of vegetation is essential in drylands. In this paper, we evaluated three vegetation indices, namely the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Enhanced Vegetation Index (EVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Surface-Reflectance Product in the Xinjiang Uygur Autonomous Region, China (XUAR), to assess index time series' suitability for monitoring vegetation dynamics in a dryland environment. The mean annual VI and its variability were generated and analyzed from the three VI time series for the period 2001-2012 across XUAR. Two phenological metrics, start of the season (SOS) and end of the season (EOS), were detected and compared for each vegetation type. The mean annual VI images showed similar spatial patterns of vegetation conditions with varying magnitudes. The EVI exhibited high uncertainties in sparsely vegetated lands and forests. The phenological metrics derived from the three VIs are consistent for most vegetation types, with SOS and EOS generated from NDVI showing the largest deviation.
引用
收藏
页码:7597 / 7614
页数:18
相关论文
共 56 条
[1]   Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981-2003 [J].
Anyamba, A ;
Tucker, CJ .
JOURNAL OF ARID ENVIRONMENTS, 2005, 63 (03) :596-614
[2]  
Bannari A., 1995, Remote Sens. Rev., V13, P95, DOI [DOI 10.1080/02757259509532298, https://doi.org/10.1080/02757259509532298, 10.1080/02757259509532298]
[3]   Evaluation of MODIS and NOAA AVHRR vegetation indices with in situ measurements in a semi-arid environment [J].
Fensholt, R ;
Sandholt, I .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2005, 26 (12) :2561-2594
[4]   Evaluation of Earth Observation based global long term vegetation trends - Comparing GIMMS and MODIS global NDVI time series [J].
Fensholt, Rasmus ;
Proud, Simon R. .
REMOTE SENSING OF ENVIRONMENT, 2012, 119 :131-147
[5]   MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets [J].
Friedl, Mark A. ;
Sulla-Menashe, Damien ;
Tan, Bin ;
Schneider, Annemarie ;
Ramankutty, Navin ;
Sibley, Adam ;
Huang, Xiaoman .
REMOTE SENSING OF ENVIRONMENT, 2010, 114 (01) :168-182
[6]   Climate variability as a dominant driver of post-disturbance savanna dynamics [J].
Gibbes, Cerian ;
Southworth, Jane ;
Waylen, Peter ;
Child, Brian .
APPLIED GEOGRAPHY, 2014, 53 :389-401
[7]   Modelling terrestrial carbon exchange and storage: Evidence and implications of functional convergence in light-use efficiency [J].
Goetz, SJ ;
Prince, SD .
ADVANCES IN ECOLOGICAL RESEARCH, VOL 28, 1999, 28 :57-92
[8]   Recent trends in vegetation dynamics in the African Sahel and their relationship to climate [J].
Herrmann, SM ;
Anyamba, A ;
Tucker, CJ .
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS, 2005, 15 (04) :394-404
[9]   AVHRR derived phenological change in the Sahel and Soudan, Africa, 1982-2005 [J].
Heumann, B. W. ;
Seaquist, J. W. ;
Eklundh, L. ;
Jonsson, P. .
REMOTE SENSING OF ENVIRONMENT, 2007, 108 (04) :385-392
[10]   Noise reduction of NDVI time series: An empirical comparison of selected techniques [J].
Hird, Jennifer N. ;
McDermid, Gregory J. .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (01) :248-258