As shalot land decreases annually, it is crucial to take deliberate measures to boost production on current agricultural land. This study aimed to formulate a strategy for optimizing shallot agricultural land in two different landscapes in the tropics. A rapid scan approach was used to identify land characteristics, while linear regression analysis was used to identify land limiting factors on shallot productivity. Literature and DPSIR (Driving Forces, Pressures, States, Impacts, and Responses) were used to develop a land optimization strategy. Typically, the pedogeomorphology analysis showed that both landscapes studied had initial alkaline conditions. Specifically, the fluvial landscape experienced a drastic acidification range (pH 4.55-7.39) due to anthropogenic factors, while the structural landscape maintained its alkaline conditions (pH 6.58-7.74). The regression results showed that the anthropogenic modifications made soil pH and EC limiting factors for productivity (R² = 0.61 for pH; R² = 0.68 for EC). Optimal results were consistently at pH conditions approaching neutral, with EC approaching one dS/m. Finally, land and water management is the best response to land optimization, accompanied by policies favoring local farmers. These findings can be used in policy-making to manage shallot agricultural land in other tropical areas.