Abstract
In this study, the regionalestimation ofmaize yield was reported with integrating a process-based mechanism model and MODIS remote sensing data. AC4 plant photosynthetic pathway mode was developed and to substitute for the C3 plant photosynthetic pathway in the remote-sensing-photosynthesis -yield estimation for crops (RS-P-YEC) model, and the Harvest Index (HI) derived from the ratio of grain to stalk yield was adopted in the developed model. We performed maize yield simulation by using the developed model in the Northeast China (NEC) region from 2007-2009. The selected countyleveldata at from the NEC region was validatedwith the MODIS-simulated results. We found that that the correlation coefficientbetween the simulated yield and the statistics yield is high (R2=0.637, n=69),and the spatial pattern of MODIS-simulated yield was agree with the statisticaldistribution in the NEC. It indicatedthe improved model has ability to estimateC4 crops in large area.
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Zhang, J., Yao, F. (2013). MODIS Satellite Data Coupled with a Vegetation Process Model for Mapping Maize Yield in the Northeast China. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. GRMSE 2013. Communications in Computer and Information Science, vol 399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41908-9_21
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DOI: https://doi.org/10.1007/978-3-642-41908-9_21
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