Abstract
The GFSAD30m cropland extent map has been recently produced at a spatial resolution of 30m as a part of NASA MEaSUREs’ Program Global Food Security Data Analysis (GFSAD) project. Accuracy assessment of this GFSAD30m cropland extent map was initially performed using an assessment strategy involving a simple random sampling (SRS) design and an optimum sample size of 250 for each of 72 different regions around the world. However, while statistically valid, this sampling design was not effective in regions of low cropland proportion (LCP) of less than 15% cropland area proportion (CAP).
 The SRS sampling resulted in an insufficient number of samples for the rare cropland class due to low cropland distribution, proportion, and pattern. Therefore, given our objective of effectively assessing the cropland extent map in these LCP regions, the use of an alternate sampling design was necessary. A stratified random sampling design was applied using a predetermined minimum number of samples followed by a proportional distribution (i.e., SMPS) for different cropland proportion regions to achieve sufficient sample size of the rare cropland map class and appropriate accuracy measures.
 The SRS and SMPS designs were compared at a common optimum sample size of 250 which was determined using a sample simulation analysis in ten different cropland proportion regions. The results demonstrate that the two sampling designs performed differently in the various cropland proportion regions and therefore, must be selected according to the cropland extent maps to be assessed.
Highlights
The cropland regions of different continents distributed around the world exhibit different cropland proportions, cropping patterns, spatial extents, and heterogeneity due to their climatic, topographic, and ecological conditions
The results of the assessment of the cropland maps of different crop proportion regions describe the comparison of the two different sampling designs with respect to the distribution and allocation of reference samples for each map class and the accuracy measures in the following two sections: The evaluation of the two sampling designs was performed by comparing the distribution and allocation of reference samples and accuracy measures of the rare cropland map class in each of the ten cropland proportion regions
The grouping of cropland area proportion of the ten cropland regions resulted in five cropland probability classes in which the two sampling designs were applied, evaluated, and compared to achieve effective accuracy measures of the cropland map class
Summary
The cropland regions of different continents distributed around the world exhibit different cropland proportions, cropping patterns, spatial extents, and heterogeneity due to their climatic, topographic, and ecological conditions. The cropland maps of various cropland proportion regions are important for cropland monitoring and modeling, cropland change analysis, resolving food security issues, and improving crop productivity in different continents [1] To accomplish these objectives, cropland maps of various cropland regions have been generated continuously and effectively using remote sensing data at different spatial resolutions [1,2,3,4]. The error matrices generated with such an insufficient distribution and allocation of samples for the rare cropland map class reported accuracy measures in the LCP regions that were not useful for our analysis [22,23,24,25,26,27]. Given our objective of effectively assessing the cropland extent maps in these LCP regions, the use of an alternate sampling design was desirable and necessary
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