The implications of land area measurement extend well beyond agricultural productivity. Disaggregated land ownership data are an input into analyses of agrarian structures and how these evolve with economic and demographic change, the related analyses of land inequality, and how this might be related to income inequality and its trends. Notable examples are the literature on the relationship between asset distribution and income inequality (Deininger and Squire, 1998; Deininger and Olinto, 1999), or the related work on agrarian structures and inequality (Carter, 2000). Unequal distribution of land has been linked to less propoor growth, participation in and occurrence of civil strife, and delayed long-run human capital development (Deininger and Squire, 1998; Macours 2011; André and Platteau, 1998; Baten and Juif, 2013). Carletto et al. (2015) find that the area measurement methodology used in calculating the land Gini coefficient has consequences on the level of inequality observed, with self-reported area estimates resulting in underestimated land inequality. Failure to adequately measure land limits the ability to analyze the agricultural economy and its relationship with land inequality.

Land registration and titling programs require high quality land area measurement for fair program implementation. Such programs are frequently met with opposition and accusations of corruption or favoritism. Ongoing land certification reform efforts in Ethiopia have recently moved from the first stage of certification, which consisted of identification of plots by land markings and neighbor recall, to the second stage certification in which GPS measurements would replace the first stage data. A recent study analyzing the demand for the second stage certification concluded that the majority of the demand for such area measurement comes from land administrators, as households exhibited a low and declining willingness to pay over the period 2007 to 2012 (Bezu and Holden, 2013). International organizations have also emphasized the importance of objective area measurement in land registration and redistribution. In its support to the Zimbabwe Ministry of Lands and Rural Resettlement 2014-2016 Action Plan (UNDP, 2014), the United Nations Development Programme explicitly mentions GPS and remote sensing as requirements for the successful tracking of the redistributed, post-2000 Land Reform Program parcels through the creation of a national land information database.

The methodological menu for collecting land area measurements is diverse and selection of the appropriate method depends on several factors. This paper focuses on the methods that hold relevance for agricultural and household surveys.<sup>2</sup> Readers interested in a broader approach to the measurement of agricultural land are referred to FAO (1982) and Sud et al. (2015). This is an important distinction because several measures of agricultural land that are important for agricultural statistics can be collected separately from information about the holding or the household (e.g. when the goal is to estimate crop

> 2 The focus will also be on low income countries with little or no cadastral or administrative information to integrate this type of data collection.

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