Measuring the precise nature and causes of land inequality is critical for addressing and implementing policy initiatives related to agricultural productivity, rural development and within-country income distribution. In this study, we argue that measuring land inequality solely among land owners does not provide a complete picture of land allocation among agricultural actors. We analyze land inequality (with or without the inclusion of landless peasants) as well as landlessness to present a holistic picture of land inequality across all districts of Pakistan. We employ data on 152,582 farm households from two rounds of the district-representative Pakistan Social and Living Standard Measurement Survey to construct Gini and Mean Logarithmic Deviation (MLD) indicators of land inequality and decompose it into within- and between-district inequalities. We found that inequalities measured without including landless peasants portray different picture of land disparities than that based on measures of inequality including landless workers. Our main findings are four-fold: 1) Land inequality measured including landless peasants is much higher (Gini = 0.84) than than that without them (Gini = 0.67), and has increased much more between 2007 and 2015 when landless peasants are included (6%) than when measured without them (1%). 2) In 22% of the districts, land inequality without landless peasants decreased between 2007 and 2015 while that measured without them increased. The opposite is true in 5% of the districts. 3) Land inequality without landless workers is higher in irrigated and humid regions with better soil quality and rough terrain while inequality with landless workers is higher in more arid and semi-arid districts. Districts with rough topography face less landlessness in the presence of predominantly-small holder farms, whereas more fertile soil is associated with higher landlessness. 4) Districts based on Pashtun tribal ancestral land distribution rights have the lowest rates of landlessness (20%) while districts with pre-colonial Zamindari-based land distribution show the highest incidence of landlessness (66%). The findings highlight the need for robust tenancy reforms in districts with humid climate, higher land inequality and lower landlessness in order to provide land tenure security to landless tenants and protect them from force eviction by powerful landed elites. Use of information technology in registering land rights through geo-coordinates can be helpful in improving land security and the expansion of the agricultural land markets. Besides, there is a greater need of land redistribution in the southern and south-western districts where landlessness is high despite relatively low extent of land inequality.