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A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform
No full textA global reference dataset on cropland was collected through a crowdsourcing campaign implemented using Geo-Wiki. This reference dataset is based on a systematic sample at latitude and longitude intersections, enhanced in locations where the cropland probability varies between 25-75% for a better representation of cropland globally. Over a three week period, around 36K samples of cropland were collected. For the purpose of quality assessment, additional datasets are provided. One is a control dataset of 1793 sample locations that have been validated by students trained in image interpretation. This dataset was used to assess the quality of the crowd validations as the campaign progressed. Another set of data contains 60 expert or gold standard validations for additional evaluation of the quality of the participants. These three datasets have two parts, one showing cropland only and one where it is compiled per location and user. This reference dataset will be used to validate and compare medium and high resolution cropland maps that have been generated using remote sensing. The dataset can also be used to train classification algorithms in developing new maps of land cover and cropland extent
Modelling Land Use Change in Brazil:2000-2050
No full textThe input and output land cover dataset across all modelled time periods (2000-2050) and scenarios resulting from the work of the REDD-PAC project in Brazil.
Please consult the data section of the REDD-PAC website (http://redd-pac.org/new_page.php?contents=data1.csv) to access a data visualization tool and to obtain the dataset in WFS format.
This dataset can be accessed and displayed using GIS software such as QGIS. Please consult the metadata file for further instruction
The Characteristics Approach to Population Aging: New Measures
No full textPopulations all over the world are getting older. Not only will there be more elderly people alive in the future, but the elderly themselves will be changing. In general, they will be living longer, have better cognitive functioning, and be more educated. Nevertheless, conventional measures of population aging assume the characteristics of the elderly will not be changing. The combination of this static view of the elderly and the dynamics of age structure change produces a misleading picture of how population aging evolved in the past and how it is likely develop in the future.
For the formulation of appropriate public policies and for an informed public discussion of population aging, it is crucial that the most accurate measures are used.
Table Re-Aging 1
Table Re-Aging 1 contains three measures. The first is the old age threshold. This is the age at which remaining life expectancy first falls below 15 years. The prospective proportion old is the proportion of the population at or above the old age threshold. The prospective old age dependency ratio has the number of people at or above the old age threshold in the numerator and the number of people from age 20 to the old age threshold in the denominator.
Table Re-Aging 2
Table Re-Aging 2 contains the conventional median age and related prospective measures. The conventional median age could differ very slightly from the UN figure because of different interpolation procedures. In order to compute prospective median ages, we have to choose a life table to use as a standard. In the column labelled “Prospective Median Age” the standard is the life table for the region/country in 2010. In the column labelled “Prospective Median Age (Japan standard)” the standard life table is from Japan in 2010. Prospective median age is the age derived from the standard life table where remaining life expectancy is the same as it is at the median age in the indicated year. Because of the way it is constructed, the prospective median age using the country’s life table as a standard is the same in 2010 and the conventional median age.
Table Re-Aging 3
Data accompanying Sanderson WC, Scherbov S (2015), Are we overly dependent on conventional dependency ratios? Population and Development Review, 41(4), 687–708.
The figures in Table Re-Aging 3 are all based on data produced by the United Nations for the 2015 volume of World Population Prospects. There figures differ slightly from those in the article because the latter were based on data from the 2012 volume of World Population Prospects. All the data are for both sexes combined.
Table Re-Aging 3 contains projections of (1) economic dependency ratios, 2) health care cost old-age dependency ratios, (3) pension cost dependency ratios, and (4) prospective old age dependency ratios. The figures are for OECD countries from 2013 to 2050
A global dataset of crowdsourced land cover and land use reference data (2011-2012)
No full textGlobal land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general
Harmonized World Soil Database - HWSD (version 1.2)
Full text linkHWSD-coverDuring discussions at the International Institute for Applied Systems Analysis (IIASA) in 1996, the need was identified for refinement of the agro-edaphic element of IIASA and FAO's Agro-Ecological Zones (AEZ) methodology then being used for IIASA’s "Modeling Land Use and Land Cover Change in Europe and Northern Eurasia (LUC)" project.
An IIASA Interim Report was produced in 1997 detailing twenty soil attributes identified as being important for land evaluation, the analyses performed on existing databases, and methodologies for the development of taxotransfer rules to derive necessary data. Conclusions of this report were used for the analyses of that time, but the process that was born continued to develop into what would eventually become a separate product, the Harmonized World Soil Database.
Between 2003 and 2006, IIASA and FAO sought out additional partners, including:
- ISRIC-World Soil Information, together with FAO, were responsible for the development of regional soil and terrain databases and the WISE soil profile database;
- the European Soil Bureau Network, which had recently completed a major update of soil information for Europe and northern Eurasia, and
- the Institute of Soil Science, Chinese Academy of Sciences, which provided the recent 1:1,000,000 scale Soil Map of China.
Vast volumes of recently collected regional and national updates of soil information collected by the partners were assimilated and harmonized by IIASA, where the HWSD raster, database, and viewer software were designed, implemented, and packaged for CD and web distribution into this state-of-the-art database. Version 1.0 was released in 2008. Since then, it has been updated with new information several times, has been used extensively around the world, and has recently been adopted by the Global Soil Partnership (GSP) as the definitive soil database at present, with plans for further updates made as part of the GSP process.
The HWSD is of immediate use in the context of the Climate Change Convention and the Kyoto Protocol for soil carbon measurements and for the FAO/IIASA Global Agro-ecological Assessment studies (GAEZ 2012), for which HWSD was developed in the first place. The HWSD contributes sound scientific knowledge for planning sustainable expansion of agricultural production to achieve food security and provides information for national and international policymakers in addressing emerging problems of land competition for food production, bio-energy demand and threats to biodiversity.
The HWSD is a 30 arc-second raster database with over 16000 different soil mapping units that combines existing regional and national updates of soil information worldwide (SOTER, ESD, Soil Map of China, WISE) with the information contained within the 1:5 000 000 scale FAO-UNESCO Soil Map of the World (FAO, 19711981).
The resulting raster database consists of 21600 rows and 43200 columns, which are linked to harmonized soil property data. The use of a standardized structure allows for the linkage of the attribute data with the raster map to display or query the composition in terms of soil units and the characterization of selected soil parameters (organic Carbon, pH, water storage capacity, soil depth, cation exchange capacity of the soil and the clay fraction, total exchangeable nutrients, lime and gypsum contents, sodium exchange percentage, salinity, textural class and granulometry).
Reliability of the information contained in the database is variable: the parts of the database that still make use of the Soil Map of the World such as North America, Australia, West Africa and South Asia are considered less reliable, while most of the areas covered by SOTER databases are considered to have the highest reliability (Central and Southern Africa, Latin America and the Caribbean, Central and Eastern Europe)