Remote Sensing technology has been used in agricultural statistics since early 1970s in developed countries and since late 1970s in China. It has greatly improved the efficiency with its accurate, timingly and credible information. But agricultural monitoring using remote sensing has not yet been assessed with credible data in China and its accuracy seems not consistent and reliable to many users. The paper reviews different methods and the corresponding assessments of agricultural monitoring using remote sensing in developed countries and China, then assesses the crop area estimating method using Landsat TM remotely sensed data as sampling area in Northeast China. The ground truth is ga-thered with global positioning system and 40 sampling areas are used to assess the classification accu-racy. The error matrix is constructed from which the accuracy is calculated. The producer accuracy, the user accuracy and total accuracy are 89.53%, 95.37% and 87.02% respectively and the correlation coefficient between the ground truth and classification results is 0.96. A new error index δ is introduced and the average δ of rice area estimation to the truth data is 0.084. δ measures how much the RS classification result is positive or negative apart from the truth data.
China is one of the main soybean production countries in the world and soybean is of great importance in agricultural
industry, domestic consumption and international trade. In recent years, however, China has become the largest
soybean importer in the world. Therefore timely credible information about soybean planting area and production is
essential for government decision making and agricultural management on domestic consumption and international
trade. Moreover, information on soybean planting and continuous planting location is critical for distributing farmer
subsidies and production management. In this paper, an operational system based on multi-resolution remotely sensed
data was developed for the soybean area inventory and continuous cropping area monitoring. A stratified sampling
method is employed to extract and locate major soybean-planting regions, which are later surveyed using remote
sensing data. At the same time, sub regions are constructed based on cropping systems in which remotely sensed data of
different resolutions are applied for the soybean area estimation and replanting area location assessment.
Conference Committee Involvement (1)
Disaster Forewarning Diagnostic Methods and Management
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