Analysis on estimation accuracy of crop area caused by spatial sampling factors based on remote sensing data

Abstract: Crop acreage estimation is important for the assurance of food security and establishment of national socio-economic development planning. During the current development period, rapid, accurate and reliable estimation for crop acreage is particularly significant in China since the estimation can be affected by many factors such as ecological degradation and farmland reduction. Spatial sampling technology plays an important and irreplaceable role in crop acreage investigation and estimation. However, the effects of sampling factors on estimation are unclear. This study analyzed data on late-season rice in paddy field of Hunan province of China, an area with significant flooded paddy rice agriculture and mixed rice cropping patterns, in order to quantitatively evaluate the influence and sensibility of various monitoring factors (sampling ratio, sampling grid, and sample distribution) on sampling efficiency of the existing space sampling techniques for estimating crop planting acreage. Nine kinds of sampling units and 31 kinds of sampling ratio levels were designed. Spatial stratified sampling was used, and the late rice planting proportion was considered as the stratification symbol. 1000 times repeated trials were conducted based on every kind of sampling plan. Spatial distribution (Variance to Mean Ratio, VMR) of every sampling units and sampling ratio levels were determined. Spatial statistics methods and manifold accuracy evaluation indices (relative estimation error and standard deviation) were used to analyze the acreage estimation results obtained based on the different sampling plans. Then a comprehensive model based on sampling grid, sampling ratio, and sample distribution was developed to assess the sampling monitoring error rate of crop acreage estimation. The result demonstrated that: 1) With the increasing of the sampling grid, the average estimation error increased (R2=0.92), and when the sampling grid was less than 5 km, the estimation error rate was controlled within 5%, the standard deviation was not more than 0.12; 2) With the increasing of the sampling ratio, the average estimation error decreased (R2=0.82), and when the sampling ratio was greater than 0.4%, the estimation error rate was controlled within 5%, and the standard deviation was less than 0.12; 3) Under the condition in which the sampling ratio had been determined, the sample spatial distribution of the sample was an important factor affecting the accuracy of sampling. With the sample distribution tending to cluster distribution, the average estimation error rate increased, and when the variance to mean ratio (VMR) was less than 0.7 the estimation error rate and the standard deviation was controlled within 5% and 0.1, respectively; 4) The quantitative model reflecting the influence of the three factors on crop acreage estimation accuracy was developed. In summary, this study revealed the influence rules and sensibility of sampling factors (sampling ratio, sampling grid, and sample distribution) on crop acreage estimation. In addition, a good method was developed for optimizing spatial sampling and improving the accuracy of crop acreage estimation based on the particular sampling program.