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To address increasing environmental challenges around climate change, computational technologies are increasingly being developed and implemented to address environmental sustainability goals. For example, digital agriculture is framed as a set of technologies that can address challenges around resource management in the agricultural industry. However, these technologies may also perpetuate legacies of land dispossession and occupation that may run counter to these efforts towards sustainability. In this presentation, I develop the concept of legibility in the design and development of digital agriculture systems to understand how these legacies are retained. In this context, legibility is defined as bringing situations and environments under control through processes of simplification, such as quantification and subsequent optimization. I draw from fieldwork on the implementation of digital agricultural systems and a historical analysis on scientific agricultural policies in the United States to demonstrate how technologies have been geared to modernize farming at the expense of rural Black and other marginalized communities in the United States. In reading this fieldwork together with the historical case, I address the question: what is made legible to whom? Subsequently, what becomes illegible? As more data-driven systems are used to address challenges around climate change, I argue that we need to extend the ways we understand how these systems impact the governance of labor, labor, and resources in rural communities.