Since 1950 FAO has prepared and advocated decennial programmes for the World Census of Agriculture (WCA). The 2000 Programme was the sixth in the series. These programmes on one hand serve to promote availability of internationally comparable data on the structure of agriculture; on the other hand they provide methodological guidance to countries in collecting data, following standard concepts, definitions and classifications.
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Library ResourceJournal Articles & BooksDecember, 2013Serbia, Nigeria, Dominican Republic, Zambia, Israel, El Salvador, Afghanistan, Samoa, Ukraine, Peru, Belarus, China, Comoros, Slovakia, Seychelles, Mozambique, Uganda, Kyrgyzstan, Haiti, Iraq, Russia, Mexico, Mongolia
Library ResourceJournal Articles & BooksDecember, 2013Qatar, Bangladesh, United States of America, Afghanistan, Samoa, China, Indonesia, South Sudan, Pakistan, Andorra, Yemen, Singapore, Mexico, Brunei Darussalam, United Arab Emirates, India, Russia, Sudan, Mongolia, Georgia, Montenegro, Lebanon
The Programme for World Census of Agriculture 2000 was the sixth prepared by FAO for encouraging countries to undertake an agricultural census with standardized international concepts, definitions and methodologies. The programme covered the censuses carried out during the decade (1996 – 2005). Some 122 countries carried out an agriculture census during the decade and 114 countries made available their census reports to FAO. This publication is a methodological review of the agricultural censuses conducted within the framework of the Programme for World Census of Agriculture 2000.
Library ResourceJournal Articles & BooksDecember, 2002Switzerland, Chile, Peru, Australia, Jamaica, Bolivia, China, Iran, Russia, Ethiopia, Nepal, Kyrgyzstan, Italy, Tanzania, Ecuador, Argentina, India, United Kingdom, Mexico, Brazil
Statements from FAO's Director-General and the King of Nepal, profiles of mountain issues and activities from countries such as Bolivia, Italy, Kyrgyzstan and Peru, and information on mountain forests, tropical cloud forests and sacred mountains complete Unasylva's foray into the mountains.
Library ResourceReports & ResearchDecember, 2016Egypt, United States of America, Chile, Sweden, Germany, China, Indonesia, Australia, Canada, Republic of Korea, France, Uruguay, Thailand, New Zealand, Japan, Finland, Malaysia, Italy, India, Russia, Turkey, Brazil, Austria
This note presents highlights and recent trends in data for each of the main product groups, as well as a short summary of recent changes or improvements in statistics.
Library ResourceConference Papers & ReportsDecember, 2017Russia, Latvia
The article shows the content of land reforms in the Russian Empire, conducted with the help of land management measures.
В статье показано содержание земельных реформ в Российской Империи, проводимых с помощью землеустроительных мероприятий.
Library ResourcePeer-reviewed publicationFebruary, 2021China, Russia, United States of America
The process of urbanization in China has been accompanied by the conflict of land expropriation, which is not conducive to social stability. Different from the previous angles and methods of studying the conflict of agricultural land expropriation, this study puts forward a new behavioral perspective on the basis of game theory, and constructs an evolutionary game model of the conflict of agricultural land expropriation in China from the perspective of multi-dimensional preference.
Library ResourceJournal Articles & BooksDecember, 1999Egypt, Estonia, Slovakia, Lithuania, Sweden, Ukraine, Denmark, Germany, Latvia, Finland, Japan, Turkey, Uzbekistan, Poland, Netherlands, Russia, Norway, France, Europe
This report presents the outcome of a macroeconomic survey of the forest sector of the Republic of Latvia. It presents issues and parameters facing public and private sector decision-makers in their respective attempts to develop this sector. It identifies opportunities and constraints to investment and proposes measures to, accordingly, either engage them or remove them. It also attempts to introduce simple methodologies to undertake analysis currently constrained by the absence of more comprehensive data.
Library ResourcePeer-reviewed publicationSeptember, 2017Russia, United States of America
Russia’s region of Chernozem and Kastanozem soils in Western-Siberia, where this study focused on the Kulunda steppe, has great potential as a carbon sink, particularly if the current widespread practice of burning crop residue can be replaced with conservation tillage practices that will return the residue to the soil. Environmentally-oriented land use policy measures have been introduced that could accomplish that goal. But these measures are quite recent, and face obstacles in the prevailing post-socialist institutional environment and in cultural norms.
Library ResourcePeer-reviewed publicationMarch, 2021China, Russia, United States of America
The structural index is an important quantitative parameter for revealing the structural properties of loess. However, there is no a widely accepted measurement method for structural index at present. This study aims at presenting a novel method for obtaining the loess structural index (LSI), based on the application of computed tomography (CT) scanning techniques and laboratory physico-mechanical tests. The mountainous area of Lvliang in northwest China was taken as the study area, and Late Pleistocene loess samples were taken from various sites in the region.
Library ResourceReports & ResearchDecember, 2016China, Russia, United States of America
There is a trend to acquire high accuracy land-cover maps using multi-source classification methods, most of which are based on data fusion, especially pixel- or feature-level fusions. A probabilistic graphical model (PGM) approach is proposed in this research for 30 m resolution land-cover mapping with multi-temporal Landsat and MODerate Resolution Imaging Spectroradiometer (MODIS) data. Independent classifiers were applied to two single-date Landsat 8 scenes and the MODIS time-series data, respectively, for probability estimation. A PGM was created for each pixel in Landsat 8 data.
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