Comparative studies of reconstruction methods for the long term NDVI dataset in the east of Northwest China

doi:10.11686/cyxb2015489

Abstract

Abstract:

A high-level time-series NDVI dataset is not only the basis for continuous monitoring of the land surface, but also an important tool for studying change related to climate and land use factors in terrestrial eco-systems. We reconstructed the noise component of the LTDR NDVI data for the east of Northwestern China where the ecosystem is fragile, using various time-series reconstruction methods. This paper use agrometeorological data and high-level NDVI data to evaluate the accuracy of different reconstruction methods. The results show that: 1) The vegetation or crop land cover is an important factor affecting fitted results of the various reconstruction methods. Each reconstruction method has a different noise reduction ability depending on differences in vegetation or crop growth characters; 2) The D-L reconstruction method has a better noise reduction ability and applicability in those areas of grassland, and woodland for which the annual average NDVI data is higher (NDVI≥0.3) and the NDVI curve has obvious seasonal changes; 3) The S-G reconstruction method has better fidelity ability and applicability in some areas of crop land in winter wheat and in areas of sparse vegetation for which annual average NDVI data are lower (NDVI<0.3) and where the NDVI curve have no obvious seasonal changes.

WANG Wei, GUO Ni, SHA Sha, HU Die, WANG Xiao-Ping, LI Yao-Hui. Comparative studies of reconstruction methods for the long term NDVI dataset in the east of Northwest China[J]. Acta Prataculturae Sinica, 2016, 25(8): 1-13.

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