In a Nutshell

LANDex is a global land governance index that aims to put people at the centre of land data, democratising land monitoring and building a data ecosystem that better captures the complex experience of land governance from diverse perspectives.

Built in consultation with members and strategic partners of ILC, LANDex is based on common people-centered indicators and methodologies, giving a platform to the individuals and communities often absent in official numbers. Organised around ILC’s 10 Commitments, the Global LandGovernance Index measures progress towards people-centred land governance (PCLG) on three levels: the legal framework, implementation and outcome or impact. In addition, standardised LANDex indicators allow members to generate globally comparable data and contribute to the monitoring of the Sustainable Development Goals (SDGs) and the Voluntary Guidelines for Tenure (VGGTs). Early uptake and successes have been reported in pilot countries, including Nepal, where government representatives committed to exploring the use of the tool for formal data collection.

All LANDex indicators are set on a 0-100 scale, with 100 being the highest possible score. A high score reflects the extent to which a country has fulfilled all aspects of the indicator, whether calculation- or evaluation-based. LANDex scores are not meant to rank countries but rather allow the land community to assess how the country is performing on important aspects of land governance. Through time, these scores reflect to what extent land governance appears to be improving or worsening in specific areas.

Learn more in the LANDex InfoNote, available here.

Background and Rationale

The ILC Roadmap for Implementation of the ILC Strategy 2016 2021 clearly states the need for a tool that would enable country platforms to capture the shifting status of land governance with respect to the 10 Commitments of People-Centred Land Governance (PCLG).

Overcoming Fragmentation

The concept behind LANDex emerged in 2016 during the “Land and the Data Revolution” event at the CIVICUS International Civil Society Week (ICSW) in Bogotá. Discussions centred on the important role of civil society in land monitoring and resulted in a scoping paper focused on the same.

From this, a fundamental question emerged: What could ILC do to consolidate land monitoring efforts at the country level, particularly those related to PCLG? It was in respond to this question that an initial proposal for a “dashboard" emerged: a tool that would offer a set of common monitoring tools that could be used to monitor land governance.

In elaborating this proposal, a number of considerations were made:

In Practice

In creating LANDex, the idea was not to reinvent the wheel but instead to identify opportunities to collaborate and align with ongoing initiatives at the local, national and global level.

Three levels of indicators

The indicators retained in consultations tended towards three categories:

Four kinds of methodology

For each indicator, existing methodologies were identified or developed in the case that none existed. In general, the methodologies fall into four categories:

  1. People-based assessments, which draw on the knowledge and experiences of individuals
  2. Calculations, which depend on best available data, whether official or non-government
  3. Survey-based indicators, which draw from third-party datasets such as PRIndex, and
  4. Joint incident collection, which is used to collect data for 10C on violations against defenders.

Diverse data sources

LANDex promotes the use of diverse data sources, which include but are not limited to a) administrative data, such as that found in official statistical publications, b) household surveys, carried out by national governments or third-parties, c) people-based assessments, including the perspectives of unaffiliated individuals, and d) participatory or community-generated data.

By broadening the sources of data that can be used to fulfill its indicators, LANDex offers a more nuanced understanding of land issues and gives priority to people-centred data.