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Proceedings Paper

Assessing the applicability of assimilating MODIS data products into crop growth models: a case study in Yucheng, ShanDong Province, China
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Paper Abstract

Monitoring crop growth status and yields using remote sensing data have been a challenges both in estimating the growing parameters and quantifying the seasonal changes. Traditionally, NOAA AVHRR data was applied to estimate and predict crop yields with statistical correlation methods. However, its spatial resolution of 8-km is not satisfying in monitoring crop growth on the site level. The launch of TERRA with moderate resolution imaging spectroradiometer (MODIS) instruments onboard began a new era in remote sensing of the Earth system which is providing a series of products of unparalleled quality and sophistication for the observation and biophysical monitoring of the terrestrial environment. Crop growth models simulate biophysical processes in the soil-crop-atmospheric system provide a continuous description of crop growth and development. Combining a growth model with the input parameters derived from remote sensing data provides spatial integrity as well as a real-time "calibration" of model parameters. A field study was conducted to evaluate the applicability of the 8-day MODIS leaf area index (LAI) data product in operational assessment of wheat growth condition and yields in the region of Yucheng, ShanDong Province, in China. The MODIS LAI product were used to compared with the DSSAT LAI--the output of crop simulation model (DSSAT) and the observed LAI. The MODIS LAI corresponded comparatively well with the DSSAT LAI in the early stage which have been tested well with the observed LAI, however in the later wheat growing stage, there are still some difference between the MODIS LAI and observed LAI. Limitations of this study and its conclusions are also discussed.

Paper Details

Date Published: 1 September 2005
PDF: 7 pages
Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58840X (1 September 2005); doi: 10.1117/12.613070
Show Author Affiliations
Zhan Tian, Institute of Geographical Sciences and Natural Resources Research, CAS (China)
Graduate School of the Chinese Academy of Sciences (China)
Junbang Wang, Institute of Geographical Sciences and Natural Resources Research, CAS (China)
Zhiqiang Gao, Institute of Geographical Sciences and Natural Resources Research, CAS (China)


Published in SPIE Proceedings Vol. 5884:
Remote Sensing and Modeling of Ecosystems for Sustainability II
Wei Gao; David R. Shaw, Editor(s)

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