The Quantificational Evaluation of a Sampling Unit Error Derived from Main Crop Area Monitorings at National Scale Based 3S in China
Abstract:It is certainly clear that grain production is of great importance to any country, especially to China. Therefore, it is very important for local and central governments to get accurate main crop area information in time. Remote Sensing Application Centre (RSAC), belonging to the Ministry of Agricultural of China, has been working on monitoring the main crop areas as operational task and research project for several years. One problem coming from the monitoring system is whether the sampling error deriving from difference of sampling units exists, furthermore, the error has not been quantificationally evaluated if it exists. Meanwhile, the estimation accuracy for crop areas in a certain year needs to be considered. For the time being, RSAC has to use investigated data of crop areas of two consecutive years to estimate the change rate of crop areas. Aiming at the issue, the experiment based same sampling units, which is acted as a research project authorized by CAAE (Chinese Academy of Agricultural Engineering), has been done by RSAC in 2010. This paper has given detailed account of the experiment. Three kinds of sampling units, which area and shape are same in one kind of sampling unit, which area is not same among three kinds of sampling units, were designed. Meanwhile, the sampling unit used before by RSAC which was designed to the frame of relief map at the scale of 1:50000 is also applied to the experiment in order to analyze the error produced by itself. Using the four sampling units to evaluate with 3S the planting areas of cotton and late-rice, acting as representatives of main crops in China, related to operational task and project research, the experiment result analyzed with statistical methods shows that the difference is significant among the estimated planting areas based the four sampling units for cotton and late-rice, especially extremely significant for late-rice.
Document Type: Research Article
Publication date: January 1, 2012
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