The overall aim of the initiative is to improve donor coordination and to support implementation of the Voluntary Guidelines for the Responsible Governance of Tenure of Land, Fisheries, and Forests in the Context of National Food Security. The original dataset (https://landgov.donorplatform.org/) retains 717 projects in 135 countries with a total value of 8.4 billion dollars and contains information the location, duration, funding and scope of each programme, as well as on the specific aspects of the Voluntary Guidelines it supports. The dataset ingested on the LB aggregates information at the country level, showing total funding and total number of both concluded and ongoing (till January 2016) programmes in each destination country.
The Lao Census of Agriculture 2010/11 was the second agricultural census undertaken in the Lao PDR. Since the first in 1998/99, the agricultural sector underwent significant changes. This Census of Agriculture was implemented by the Lao Ministry of Agriculture and Forestry - LMAF (http://www.maf.gov.la/), with support from the Lao Statistics Bureau (http://www.lsb.gov.la/), and collected basic information on crop and livestock production from every household in the Lao PDR, as well as information on village infrastructure. A sample survey module collected detailed data on agricultural production activities from over 40 thousand farm households.
The census data collection was undertaken in March 2011, whereby crop production data on the 2010 wet season and the 2010/11 dry season was collected. Data are available on the Lao Decide platform (http://www.decide.la/en/)
This dataset contains the estimated area of land held or used by Indigenous Peoples and non-indigenous communities per country as a percentage of the country’s total land area. The data are divided into three categories, each of them correspond to an indicator on the LB.
1) Formally Recognized (i.e., lands recognized by the State)
2) Not Formally Recognized (i.e., lands held or used but not recognized by the State)
3) Total (i.e., lands held or used, independent of recognition status).
The percentages are calculated by dividing the total land area of the country (calculated in GIS using the GADM Database of Global Administrative Areas) by the estimated area of the land held or used by Indigenous Peoples and communities. For more information please visit: http://www.landmarkmap.org/data/.
The dataset can be visualised on a free on-line mapping tool produced by the original data provider: http://www.landmarkmap.org/map.
This qualitative dataset shows how national laws measure up against the international standards on expropriation, compensation, and resettlement as established in Section 16 of the UN Voluntary Guidelines on the Responsible Governance of Tenure of Land Fisheries and Forests in the Context of National Food Security (VGGTs). The UN Committee on World Food Security, a body consisting of 193 governments, endorsed the VGGTs in 2012. The dataset contains indicators which ask yes or no questions about the legal provisions established in national laws. Where laws only partially satisfy the question asked by the indicator, a score of "partial" is provided. If the national laws assessed fully adopt the VGGT principle, then a score of "A" is given. If national laws assessed partially adopt the VGGT principle, then a score of "B" is given. If national laws assessed do not adopt the VGGT principle, then a score of "C" is given. Answering the questions posed by these indicators entailed reviewing a broad range of legally binding instruments, including national constitutions, land acquisition acts, land acts, communal land acts, agricultural land acts, land use acts, regulations, and some court decisions. For more information, please see: http://www.wri.org/publication/encroaching-on-land-and-livelihoods
Also known as the Gender, Institutions and Development Database - OECD, the SIGI dataset address the de jure and de facto situations of discriminatory social institutions across five sub-indices: discriminatory family code, restricted physical integrity, son bias, restricted resourcesand assets, and restricted civil liberties. Each of the sub-indexes contains sub-dimensions, but not all of them are included in the LB. The SIGI index is computed as an unweighted average of the score for all five sub-indices. The dataset includes the 2009 (partially), the 2012 and 2014 releases of the SIGI Database.
The quantitative dataset on forest tenure data by RRI currently covers 52 countries containing nearly 90% of the world’s forests. It monitors spatial forest tenure data - that is, who owns how many hectares of a given forest. RRI recognizes four categories of land ownership:
I) Forestland Owned by Indigenous Peoples and local communities
II) Forestland Designated for Indigenous Peoples and local communities
III) Forestland Administered by governments
IV) Forestland by individuals and private firms
This dataset contains the indicators on health and nutrition (such as Malnutrition Prevalence, Prevalence of HIV, Mortality rate under 5 years, Access to Improved water source...), as provided by the World Bank.
This dataset contains information from the pre-2013 round of Land Governance and Assessment Framework (LGAF) of the World Bank. The 2013 LGAF dataset consists of 27 core land governance indicators, which are then further broken down into a total of 80 dimensions. These dimensions are scored by selecting an appropriate answer among a list of pre-coded statements that draw on global experience. "A" stands for good practice, "D" stands for weak practice. Depending on the country context, a few dimensions may not be eligible for scoring, or sub-dimensions can be added. For more information on specific country values and on the methodology please visit http://go.worldbank.org/21M7S7AZO0
This dataset contains information from the post-2013 round of Land Governance and Assessment Framework (LGAF) of the World Bank. The 2016 LGAF dataset consists of 27 core land governance indicators, which are then further broken down into a total of 116 dimensions. These dimensions are scored by selecting an appropriate answer among a list of pre-coded statements that draw on global experience. "A" stands for good practice, "D" stands for weak practice. Depending on the country context, a few dimensions may not be eligible for scoring, or sub-dimensions can be added. For more information on specific country values and on the methodology please visit http://go.worldbank.org/21M7S7AZO0