Abstract
Multiple cropping index (MCI) is a very important indicator in crop production and agricultural intensification, which represents the degree of utilizing agriculture resources at time scale and the situation of arable land use effectively. The objective of this paper is monitoring multiple cropping index of Henan province of China according to the time series of MODIS-EVI after Savitzky-Golay filter processing from the year 2006 to 2011.The results revealed that this method could provide an effective way to monitor multiple cropping index, and the method of no additional authentication data is independent and reliable. The results was accurate and stable, the slope of linear regression of the multiple cropping index between the statistical results and the remote sensing results was 1.0136 (R2 = 0.779). The precision of sample areas validation was 97.91%. Suggesting that the time series MODIS-EVI which after Savitzky-Golay filtering processed, could provide an effective way to extract spatial information of multiple cropping index for management department of agriculture.
Highlights
In agriculture, multiple cropping is the practice of growing two or more crops in the same space during a single growing season, which is one of effective ways to ensure region grain security
Considering the advantages and disadvantages of each approach, the Savitzky-Golay was applied to the Moderate Resolution Imaging Spectroradiometer (MODIS)-enhanced vegetation index (EVI) time series data to minimize the effects of cloud cover and other sources of noise [Chen, Jönsson, Tamura et al (2004)].The Savitzky-Golay is simple and intuitive in theory, which is a low-pass filtering in time-domain method that smooth time series data by using local polynomial regression model
The increase of multiple cropping index (MCI) plays an important role in increase food production
Summary
Multiple cropping is the practice of growing two or more crops in the same space during a single growing season, which is one of effective ways to ensure region grain security. Multiple cropping is found in many agricultural traditions and prevalent in China. Multiple cropping is measured by multiple cropping index. The multiple cropping index (MCI) is an important indicator of land utilization intensity, and the temporal-spatial dynamics can help to understand the coupling effects of human activities and the ecological environment [Li, Liu, Sun et al (2018)]. The MCI is computed as: MCI(%)= annual total sown area of the crops×100/annual total cultivated land area.
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