Developing a Method to Estimate Maize Area in North and Northeast of China Combining Crop Phenology Information and Time-Series MODIS EVI

Abstract

Remote sensing (RS) is a convenient technology to estimate the regional cultivation areas of crops. However, the accurate estimation of maize areas using RS over a broad region is a significant challenge due to the large phenology differences and insufficient prior knowledge in space. To address this issue, a new method was developed in this work. In this method, the correlation (r ) and root mean standard error (RMSE) between the time-series moderate resolution imaging spectroradiometer enhanced vegetation index (MODIS EVI) and the standard EVI curve of maize from a reference area are computed. Pixels with a high value of r and a low value of RMSE were identified as maize areas. The phenology information observed at agro-meteorological stations was also used to recognize maize pixels from the pixel-level phenology derived from time-series MODIS EVI. The proposed method provides an accurate characterization of the phenology differences over the study area by making use of the planting and maturity dates only. In addition, the few location-dependent parameters make the recognition of maize planting areas over large regions easier than previous studies. The proposed method was implemented over the Northeast China Plain (NECP) and North China Plain (NCP). The derived results were compared with official statistical results, and a close agreement was observed. At the city level, the satellite-derived estimates agreed well with the statistics with the R 2 (RMSE) of 0.86(110.97 k hm 2 ) in the NECP and 0.76(68.74 k hm 2 ) in the NCP. At the county level, the R 2 (RMSE) is 0.82(25.47 k hm 2 ) in the NECP and 0.75(5.93 k hm 2 ) in the NCP. At both temporal levels, the R 2 (RMSE) results obtained in this work are higher(lower) than those published in other studies. The obtained results indicate that the proposed method is effective in maize area estimation over broad regions.