The 2030 Sustainable Development Agenda, proposed by the United Nations in 2015, involves efforts and strategies to achieve several global goals to fight poverty in all its forms. Several indicators were developed to keep track of the advances toward each of them. However, calculating these Sustainable Development Goal’s (SDG) indicators may not be a trivial task, as they depend not only on the availability of data at each country, but also on complex measuring processes applied to sampling units selected by probability sampling designs. This paper presents a discussion on the main sampling issues found when dealing with estimating them, taking the 2.4.1 SDG indicator as an example. Conceptually defined as the proportion of agricultural land where productive and sustainable agriculture is practiced, this is a complex parameter to estimate. A general framework for estimating it under an agricultural dual frame design is presented, and the challenges involved in its estimation discussed.