Crop Yield Forecasting

apply the systematic sampling method to select the sample fields with equal probability
within the sample villages (Zhao and Zhou 2010).
With the development of spatial information techniques such as “3S”, namely RS, GISs,
and Global Positioning Systems (GPSs), the NBS has made great efforts to modernize
the traditional statistical system. Since the 2000s, RS was introduced in the design of the
sampling frame, which constitutes the core of the area sample survey and the basis of
the yield sample survey (Pan et al. 2010). Gradually, use of the list sampling frame evolved
towards that of the area sampling frame. Since 2013, the NBS has officially implemented crop
production area frame sample surveys in Jiangsu, Henan, Liaoning, Jilin, and Hubei provinces
(Xu and Zhou 2013). The design and assessment of the area sampling frame are introduced
by Wang and Wei (2014), and its application in area sample surveys is briefly introduced in
Section 3.1 below. In addition, the NBS’s information infrastructure for agricultural statistics
has been updated. High-tech apparatuses and instruments such as GPS, Personal Digital
Assistants (PDAs), Unmanned Aerial Vehicles (UAVs) and agricultural variable collectors were
used in the NBS’s agricultural measurements, enhancing the efficiency of ground surveys.
Currently, a project on the Fast Agricultural Survey Platform is also being designed in the
NBS; this project aims to combine the rapidity of surveys of crop growth conditions, planting
area, yield and impact of disaster with satellite data and fast survey vehicles equipped with
high-tech survey devices (Wei 2013). Moreover, modern information and communication
technology also enhances the efficiency, objectiveness and harmonization of agricultural
statistical work. A dedicated network with an online reporting system has been introduced
in all NBS survey organizations, from national and provincial to county levels, and specialized
unified data processing programs are used in the survey for data entry, checking and editing
(Xu and Zhou 2013).
2.1.1.1. The remote sensing operation system
In 2003, the NBS collaborated with other universities and research institutes to launch a
research on combining national agriculture statistical survey systems with RS technology.
Several experiments were conducted on the use of multi-scale RS surveys on typical crops
(wheat, maize and rice) from Henan, Hebei, Anhui, Shandong and Jiangsu provinces, and
compared with statistical sample survey results. In 2006, the Ministry of Science and
Technology established the first key project (“National High Technology Research and
Development Program 863”) in the field of “Earth Observation and Navigation Technology:
Research and Application of Key Technologies of National Statistics and Remote Sensing
Service System”. This led to the development of the NSRCP, which aims to comprehensively
combine the country’s current survey system and 3S technology to produce accurate
estimates of crop area and yield statistics for the major crops (wheat, corn and rice) at
provincial and county levels (Zhao et al. 2007). The NSRCP has been operated in five main
grain-producing provinces (Jilin, Henan, Jiangsu, Hunan and Beijing) with an expected
accuracy of planting area and yield at county-level greater than 95 percent. The structure,
functions and application of the NSRCP have been examined by Zhang et al. (2010). Its key
technologies are outlined below.
Crop Yield Forecasting: Methodological and Institutional Aspects 61