## 1 Introduction  
Savanna biomes cover roughly one-fifth of the planet's terrestrial surface with the largest spatial extents found in sub-Saharan Africa. Among the savanna-range countries, agricultural activity constitutes a large segment of the economic sector, employing 70% of labor and accounting for 32% of GDP [1]. Traditional smallholder farming systems dominate the agricultural landscape where smallholders play an integral part in shaping the socioeconomic and ecological fabric of the region and provide the foundation for food security. Despite increasing agricultural production over the last 30 years, yield has not kept pace with exponential population growth and food insecurity remains prevalent [2]. The response of cultivating more land to increase productivity has put savannas under intense pressure [3,4] with little improvement in yield [2]. To meet the rapidly growing food demands of the projected doubling of the region's population by 2050 [5], and the growing interest in using the capacity for additional cropland to enhance economic development in the region [6,7], conversion of savanna to cropland is expected to continue at an advancing pace. In addition to this concern, this region's high climate variability, and vulnerability to drought, pose a significant and increasing risk to agriculturally-based livelihoods [8,9]. A mechanism that can support the monitoring and assessment of food security and improve understanding of how climate variability affects regional crop production could offer a valuable tool to the region.  
Reliable cropland maps are fundamental to informing both local and global development and natural resource management policies [6], being an essential input for evaluating food security, land use/land cover dynamics, investment priorities, conservation policies, and a host of other factors [10, 11, 12]. Yet, there is little agreement of the cropland baseline, reflected by the lack of consensus among regional and global land cover products. Global estimates of total cropland area differ by as much as 40% [13], and estimates within semi-arid regions of Africa have even greater uncertainty, largely attributable to the difficulty of mapping cropland in smallholder systems [12,14].  
This difficulty is pronounced in savannas, where smallholder systems predominate, and the characteristics of savanna vegetation make it particularly hard to distinguish from small-scale farms. Smallholders use low intensity practices to cultivate small fields, and often preserve large fruit-bearing trees within their field boundaries [15]. The combination of field size, residual tree canopies, and crop diversity magnify the within-class variability of crop field while blurring the spectral distinction between croplands and savannas. The difficulty in distinguishing cropland from savanna is evidenced by the disagreement between products derived from remote sensing and statistical inventories of African agriculture [16,17]. Given these discrepancies, and the absence of a single reliable dataset to inform policy decisions regarding food security issues and land use, an effective and rigorous methodology for mapping croplands from satellite images is much needed for sub-Saharan savanna landscapes [18].