Detection and Modeling of Vegetation Phenology Spatiotemporal Characteristics in the Middle Part of the Huai River Region in China

Di Xu and Meichen Fu
Additional contact information
Di Xu: School of land Science and Technology, China University of Geosciences, Beijing 100083, China
Meichen Fu: School of land Science and Technology, China University of Geosciences, Beijing 100083, China

Sustainability, 2015, vol. 7, issue 3, 1-17

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.

Keywords: spatiotemporal; Huai River; empirical orthogonal function; temporal unmixing analysis; vegetation phenology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/7/3/2841/pdf (application/pdf)
https://www.mdpi.com/2071-1050/7/3/2841/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:7:y:2015:i:3:p:2841-2857:d:46541

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().