Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index

The global distribution of croplands is of critical interest to a wide group of end-users. Different crops have their own representative phenological stages during their growing seasons, which differ considerably from other natural vegetation types. During the last decade, the Moderate Resolution Imaging Spectroradiometer (MODIS) has become a key tool for vegetation monitoring because of its high temporal resolution, extensive scope, and rapid availability of various products. However, mixed pixels caused by the moderate spatial resolution produce significant errors in crop area estimation. Here we propose a Crop Proportion Phenology Index (CPPI) to express the quantitative relationship between the MODIS vegetation index (VI) time series and winter wheat crop area. The utility of this index was tested in two experimental areas in China: one around Tongzhou and the other around Shuyang, as representative districts around a metropolis and a rural area, respectively. The CPPI performed well in these two regions, with the root mean square error (RMSE) in fractional crop area predictions ranging roughly from 15% in the individual pixels to 5% above 6.25 km(2). The training samples containing mixtures of crop types mitigated the challenges of pure end-member selection in a spectral mixture analysis. A small number of training samples are sufficient to generate the CPPI, which is adaptable to other crop types and larger regions. Estimating the CPPI parameters across larger spatial scales helped improve the stability of the model. (C) 2011 Elsevier Inc. All rights reserved.