One of the main components of Indonesia's Just Economy policy is extensive and rapid land reform, which targets about 12% of the country's land area for redistribution to farmers and communities by 2019. Much of the reform is occurring on forest land. At the same time, the country has pledged a significant reduction of its greenhouse gas emissions by 2030, two thirds of which is to be achieved from forests. Hence agrarian reform potentially conflicts with emission reduction commitments.
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Library ResourcePublication évaluée par des pairsnovembre, 2019Indonésie
Library ResourcePublication évaluée par des pairsnovembre, 2017Indonésie
We examine the emergence of land markets and their effects on forest land appropriation by farm households in Jambi Province, Sumatra, using micro-level data covering land use and land transactions for a period of more than 20 years (1992–2015). Based on a theoretical model of land acquisition by a heterogeneous farming population, different hypotheses are developed and empirically tested. Farm households involved in forest land appropriation differ from those involved in land market purchases in terms of migration status and other socioeconomic characteristics.
Library ResourceRapports et recherchesdécembre, 2020Global
As the United Nations Decade on Biodiversity 2011–2020 comes to a close and countries prepare to adopt a post-2020 global biodiversity framework, this edition of The State of the World’s Forests (SOFO) examines the contributions of forests, and of the people who use and manage them, to the conservation and sustainable use of biodiversity.
Library ResourceRapports et recherchesoctobre, 2014Chine
Individuals cannot privately own land in China but may obtain transferrable land-use rights for a number of years for a fee. Currently, the maximum term for urban land-use rights granted for residential purposes is seventy years. In addition, individuals can privately own residential houses and apartments on the land (“home ownership”), although not the land on which the buildings are situated.
Library ResourcePublication évaluée par des pairsjanvier, 2017Chine
China has a unique land use system in which there are two types of land ownership, namely, state-owned urban land and farmer collective-owned rural land. Despite strict restrictions on the use rights of farmer collective-owned land, rural land is, in fact, developed along two pathways: it is formally acquired by the state and transferred into state ownership, or it is informally developed while remaining in collective ownership.
Library ResourceMultimédiaavril, 2016Asia du sud-est, Cambodge
Library ResourcePublication évaluée par des pairsavril, 2020Global
Understanding the trajectories and extents of land use/land cover change (LULCC) is important to generate and provide helpful information to policymakers and development practitioners about the magnitude and trends of LULCC. This study presents the contributing factors of LULCC, the extent and implications of these changes for sustainable land use in the Finchaa catchment. Data from Landsat images 1987, 2002, and 2017 were used to develop the land use maps and quantify the changes. A supervised classification with the maximum likelihood classifier was used to classify the images.
Library ResourcePublication évaluée par des pairsavril, 2020Éthiopie
Land use and land cover change (LULCC) is a critical factor for enhancing the soil erosion risk and land degradation process in the Wabi Shebelle Basin. Up-to-date spatial and statistical data on basin-wide erosion rates can provide an important basis for planning and conservation of soil and water ecosystems. The objectives of this study were to examine the magnitude of LULCC and consequent changes in the spatial extent of soil erosion risk, and identify priority areas for Soil and Water Conservation (SWC) in the Erer Sub-Basin, Wabi Shebelle Basin, Ethiopia.
Library ResourcePublication évaluée par des pairsmars, 2020Pologne
The wide availability of multispectral satellite imagery through projects such as Landsat and Sentinel, combined with the introduction of deep learning in general and Convolutional Neural Networks (CNNs) in particular, has allowed for the rapid and effective analysis of multiple classes of problems pertaining to land coverage. Taking advantage of the two phenomena, we propose a machine learning model for the classification of land abandonment.
Library ResourceDocuments de politique et mémoiresavril, 2020Kenya, Inde, Global
In late March, Indian Premier Narendra Modi imposed a three-week lockdown to prevent the further spread of the coronavirus. Since then, tens of thousands of migrant workers who had previously provided cheap labour in wealthy homes or on construction sites in the nation’s growing metropolises have been making their way back to their rural home regions.
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