Fallow land mapping for better crop monitoring in Huang-Huai-Hai Plain using HJ-1 CCD data

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Zhang, Miao^1 ; Wu, Bingfang^1 ; Meng, Jihua^1 ; Dong, Taifeng^1 ; You, Xingzhi^1

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Olympic Village Science Park, West Beichen Road, Chaoyang District, Beijing, China^1

关键词: Arable land;    Crop monitoring;    Guidance and control;    Hj-1 ccds;    Normalized difference vegetation index;    Production prediction;    Socio-economic development;    Structure adjustments;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012048/pdf
DOI  :  10.1088/1755-1315/17/1/012048

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The prediction of grain production is essential for socio-economic development planning, guidance and control of macro cropping structure adjustment. Fallow areas should be identified each growing season which is critical for grain production prediction. This paper focuses on fallow arable land monitoring during summer grain season in the Huang-Huai-Hai Plain using China Environment Satellite HJ-1 CCD data. With the two satellites HJ-1A and HJ-1B, high temporal Normalized Difference Vegetation Index (NDVI) can be obtained. HJ-1 CCD data were acquired from early March to early June in 2010 over the Huang-Huai-Hai Plain. Multi-temporal HJ-1 CCD data were pre-processed and time series of NDVI were derived. An algorithm for separating cropped and fallow areas was developed based on three key periods of NDVI in early-March, mid-April and mid-May, 2010. The influence of fallow arable lands to yield estimation and crop condition monitoring over the Huang-Huai-Hai Plain were also investigated and analyzed. Preliminary results in this paper showed that HJ-1 CCD data are capable for fallow land monitoring. Information of fallow arable lands is an essential part of crop monitoring and it should be incorporated into crop monitoring systems. In the future, the fallow lands over autumn grain season should also be identified and information of fallow arable lands should be generated yearly in order to get more reliable production prediction.