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| 1 | Remote sensing-based global crop monitoring: experiences with China’s CropWatch system显示文摘Monitoring the production of main agricultural crops is important to predict and prepare for disruptions in food supply and fluctuations in global crop market prices.China’s global crop-monitoring system(CropWatch)uses remote sensing data combined with selected field data to determine key crop production indicators:crop acreage,yield and production,crop condition,cropping intensity,crop-planting proportion,total food availability,and the status and severity of droughts.Results are combined to analyze the balance between supply and demand for various food crops and if needed provide early warning about possible food shortages.CropWatch data processing is highly automated and the resulting products provide new kinds of inputs for food security assessments.This paper presents a comprehensive overview of CropWatch as a remote sensingbased system,describing its structure,components,and monitoring approaches.The paper also presents examples of monitoring results and discusses the strengths and limitations of the CropWatch approach,as well as a comparison with other global crop-monitoring systems. | Bingfang Wu Jihua Meng Qiangzi Li Nana Yan Xin Du Miao Zhang | 2014 | International Journal of Digital Earth2014，7，2： | 6 |
| 2 | Quantitative extraction of the bedrock exposure rate based on unmanned aerial vehicle data and Landsat-80LI image in a karst environment显示文摘 | Hongyan WANG Qiangzi LI Xin DU Longcai ZHAO | 2018 | Frontiers of Earth Science2018，12，3： | 5 |
| 3 | Crop classification using multi-configuration SAR data in the North China Plain显示文摘 | Kun Jia Qiangzi Li Yichen Tian Bingfang Wu Feifei Zhang Jihua Meng | 2012 | International Journal of Remote Sensing2012，，1： | 2 |
| 4 | Land use and land cover classification using Chinese GF-2 multispectral data in a region of the North China Plain显示文摘The newly launched GF-2 satellite is now the most advanced civil satellite in China to collect high spatial resolution remote sensing data.This study investigated the capability and strategy of GF?2 multispectral data for land use and land cover (LULC) classification in a region of the North China Plain.The pixel-based and object-based classifications using maximum likelihood (MLC) and support vector machine (SVM) classifiers were evaluated to determine the classification strategy that was suitable for GF?2 multispectral data.The validation results indicated that GF-2 multispectral data achieved satisfactory LULC classification performance,and object-based classification using the SVM classifier achieved the best classification accuracy with an overall classification accuracy of 94.33% and kappa coefficient of 0.911.Therefore,considering the LULC classification performance and data characteristics,GF-2 satellite data could serve as a valuable and reliable high-resolution data source for land surface monitoring.Future works should focus on improving LULC classification accuracy by exploring more classification features and exploring the potential applications of GF-2 data in related applications. | Kun JIA Jingcan LIU Yixuan TU Qiangzi LI Zhiwei SUN Xiangqin WEI Yunjun YAO Xiaotong ZHANG | 2019 | Frontiers of Earth Science2019，13，2： | 2 |
| 5 | Maize acreage estimation using ENVISAT MERIS and CBERS-02B CCD data in the North China Plain显示文摘 | Li Qiangzi Wu Bingfang Jia Kun | 2011 | Computers and Electronics in Agriculture2011，78，2： | 1 |
| 6 | Crop planting and type proportion method for crop acreage estimation of complex agricultural landscapes显示文摘 | Wu Bingfang Li Qiangzi | 2012 | International Journal of Applied Earth Observation and Geo-information2012，16，2012： | 1 |
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