Accuracy assessment on the crop area estimating method based on RS sampling at national scale: a case study of China's rice area estimation assessment

Abstract

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.