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生态学报  2010 

Satellite observed crop calendar and its spatio-temporal characteristics in multiple cropping area of Huang-Huai-Hai Plain
黄淮海多熟种植农业区作物历遥感检测与时空特征

Keywords: Huang-Huai-Hai Plain,remote sensing,multiple cropping,crop calendar,MODIS,EVI,LSWI
黄淮海
,遥感,多熟种植,作物历,MODIS,EVI,LSWI

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Abstract:

Multiple cropping is one of the most influenced intensified agricultural land use activity in China because of the increased pressure on water, ecosystems and environment. However, due to the lack of spatial and temporal explicitly data of multiple cropping and crop calendar, there were significant uncertainty in agricultural productivity and Carbon dynamic monitoring, modeling and evaluation on regional to larger scale. In Huang-Huai-Hai Plain, an important agricultural region in China, more than 70% of total cropland land area was planted with winter-wheat and maize double cropping system. It has been proved that identifying multiple cropping and crop calendar and assigning appropriate light use efficiency to C3 and C4 crops could substantially improve our ability to model and evaluate the seasonal dynamics of carbon flux in such winter-wheat and maize rotation system. In this study, we analyze spatial and temporal patterns of crop growth process and crop calendar in the winter-wheat and maize double cropping system using multi-temporal satellite images from the Moderate Resolution Imaging Spectral radiometer (MODIS) and in-situ observation of key crop phenological transition dates, and explore a method to examine and extract crop calendar of each crop season in Huang-Huai-Hai plain from MODIS Enhanced Vegetation Index (EVI) and MODIS Land Surface Water Index (LSWI) time series curves by combining agro-meteorological observation data and MODIS data with a resolution of 500m at 8-day intervals. Multiple cropping distribution, temporal transition characteristics and heterogeneity of the start and the end time of each crop season were examined and analyzed, and the method also was validated by comparing with in-situ observed start date and end date records of winter-wheat and maize. The method and crop calendar products discussed in this paper could be applied in agricultural productivity estimation, biogeochemical cycle modeling and agricultural ecosystem monitoring.

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