The analysis of winter wheat dynamic growth based on the data of MODIS coupled with in situ observation

Hong-wei Zhang; Huai-liang Chen

doi:10.1117/12.864813

22 October 2010 The analysis of winter wheat dynamic growth based on the data of MODIS coupled with in situ observation

Hong-wei Zhang, Huai-liang Chen

Proceedings Volume 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII; 78242M (2010) https://doi.org/10.1117/12.864813
Event: SPIE Remote Sensing, 2010, Toulouse, France

Abstract

In this paper, the analysis methods, which used to descript the winter wheat growing features, have been found of satellite remote sensing coupled with the data of LAI, dry matter weight, etc. the results showed that the revised rate of remote sensing to in-situ observation is different in different developmental stages of winter wheat. Mainly manifested in the following aspects (1) In the early stage of growth and development of winter wheat (in March), the leaf area index LAI of winter wheat is small, due to the impact of soil background, the winter wheat NDVI which retrieved from MODIS data (leaf area index LAI can be calculated from NDVI) are vary greatly from in-situ observations, the revised coefficient is relatively large. (2) In the rapid vegetative growth stage (April), the ground was completely covered by winter wheat, the influence of soil background decreased, and LAI which retrieved from remote sensing closing to the data in-situ observation accordingly and the revised coefficient is smaller than in the early stage of winter wheat. (3) The LAI decreased sharply in the later stage of winter wheat. So the LAI accuracy of remote sensing retrieval as well as reduced. The differences are largest between the remote sensing retrieval and in-situ observation, and the revised coefficient is largest in all growing stage.

Citation Download Citation

Hong-wei Zhang and Huai-liang Chen "The analysis of winter wheat dynamic growth based on the data of MODIS coupled with in situ observation", Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 78242M (22 October 2010); https://doi.org/10.1117/12.864813

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