Abstract
Vegetation plays an important role in atmospheric, hydrologic and biochemical cycles and is an important indicator of the impact of climate and human factors on the environment. In this paper, a method, which combines the empirical orthogonal function (EOF) and temporal unmixing analysis (TUA) methods, is applied to monitor the phenological characteristcs and spatial distribution of vegetation phenology in the middle part of the Huai River region. Based on the variance and EOF curves, the EOF provides the number of phenology modes, information which is the basis for an accurate temporal unmixing model. The TUA describes the temporal vegetation phenological details and spatial distribution. Importantly, this approach does not require assumptions, prior information or pre-defined thresholds. The vegetation phenology curves derived from the MODIS EVI data using the combined EOF and TUA methods display much more detail than the curves from Landsat TM using spectral mixture analysis (SMA). Additionally, the vegetation phenology spatial distribution from MODIS EVI is consistent with the field survey data. The combination method of EOF and TUA can be used to monitor vegetation phenology spatiotemporal change in a large area from time series of MODIS EVI data.
Highlights
Vegetation phenology dynamics influence the ecosystem through seasonal changes in albedo [1], canopy conductance [2,3] and by exerting strong effects on water and heat fluxes [4], carbon cycling [5]and net ecosystem productivity [6]
The first four empirical orthogonal function (EOF) explain the majority of the vegetation changes in the middle Huai River region
Sampling for agricultural production estimation is based on random statistical selection, but phenology partitions derived from the joint application of the EOF and temporal unmixing analysis (TUA) methods could narrow the sampling frame and optimize the sampling results
Summary
Vegetation phenology dynamics influence the ecosystem through seasonal changes in albedo [1], canopy conductance [2,3] and by exerting strong effects on water and heat fluxes [4], carbon cycling [5]. Based on variances and EOF curves, EOFs provide prior statistical dimensions for a temporal unmixing model. This paper’s objectives are: (1) to apply the combined method of EOF and TUA to produce the temporal phenology endmembers and spatial vegetation abundance in the middle part of Huai River region from MODIS EVI time series; and (2) validate the EOF and TUA methods by comparing their results with those derived from Landsat TM using spectral unmixing and with a field survey spatial map. The TUA method helps to explain realistic meaning of the statistic EOFs. The spatiotemporal processes were validated using phenology curves extracted from Landsat and a phenology spatial map derived from field surveys. Spectral mixture analysis (Substrate-Vegetation-Dark endmembers) has been used to extract vegetation abundance time series curves that are compared with phenological endmembers from EVI, to calibrate the phenology patterns [7,22]. Spatial vegetation phenology maps based on field survey [23,24,25] are compared with vegetation phenology map derived from the EOF and TUA methods
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