Source
Source Contact person/organisation Contact person/organisation Direct source Direct sourceSurface water: Joint Research Centre & Pekel et al. (2016) High-resolution mapping of global surface water and its long-term changes supporting data. Data can be viewed here:
Political and administrative boundaries: FAO (2015) Global Administrative Unit Layers (GAUL)
Data Characteristics Data Characteristics Date last updated Date last updated Concepts & Classifications Concepts & Classifications Key statistical concept Key statistical conceptSurface water and surface water change
Methodology: http://dx.doi.org/10.1787/72a9e331-en
Surface water changes impact in different ways on biodiversity and climate. Both surface water gains and losses have biodiversity costs and impacts on ecosystem service provision. Damming is known to be one of the most important anthropogenic impacts on freshwater ecosystems. Dams fragment river systems and potentially block migration routes, leading to the loss of megafauna as well as changing the downstream flooding patterns and sediment deposition leading to the loss of floodplains, riparian zones and wetlands.
"Permanent surface water" is defined as areas that were water for every month of the reference year. "Seasonal surface water" is defined as areas that were water for 1 to 11 months of the reference year. It should be noted that these data refer only to water surface area, they do not estimate the volume of water gained or lost.
Note
These indicators are calculated by intersecting political, administrative or functional urban area boundaries with raster datasets using GIS software. They provide accessible tabular statistics of the underlying datasets for a variety of geographic output areas that can be used immediately without performing the spatial analysis that would otherwise be required.
Maps of the underlying geographic data set/s used can be viewed in a web browser at the above links. Prospective users are encouraged to examine the underlying data for their area of interest and familiarise themselves with the methodology used in their production so as to better understand what the data show and what kinds of conclusions they can be used to support. Irrespective of the underyling data, all earth-observation derived statistics come with caveats such as scale dependence, limitations associated with classification of continuous phenomena into discrete classes, and uneven geographical and temporal accuracy.
For more details on the methodology see:
Methodology: http://dx.doi.org/10.1787/72a9e331-en
Surface water: Joint Research Centre & Pekel et al. (2016) High-resolution mapping of global surface water and its long-term changes supporting data. Data can be viewed here:
Political and administrative boundaries: FAO (2015) Global Administrative Unit Layers (GAUL)
Surface water and surface water change
Methodology: http://dx.doi.org/10.1787/72a9e331-en
Surface water changes impact in different ways on biodiversity and climate. Both surface water gains and losses have biodiversity costs and impacts on ecosystem service provision. Damming is known to be one of the most important anthropogenic impacts on freshwater ecosystems. Dams fragment river systems and potentially block migration routes, leading to the loss of megafauna as well as changing the downstream flooding patterns and sediment deposition leading to the loss of floodplains, riparian zones and wetlands.
"Permanent surface water" is defined as areas that were water for every month of the reference year. "Seasonal surface water" is defined as areas that were water for 1 to 11 months of the reference year. It should be noted that these data refer only to water surface area, they do not estimate the volume of water gained or lost.
Note
These indicators are calculated by intersecting political, administrative or functional urban area boundaries with raster datasets using GIS software. They provide accessible tabular statistics of the underlying datasets for a variety of geographic output areas that can be used immediately without performing the spatial analysis that would otherwise be required.
Maps of the underlying geographic data set/s used can be viewed in a web browser at the above links. Prospective users are encouraged to examine the underlying data for their area of interest and familiarise themselves with the methodology used in their production so as to better understand what the data show and what kinds of conclusions they can be used to support. Irrespective of the underyling data, all earth-observation derived statistics come with caveats such as scale dependence, limitations associated with classification of continuous phenomena into discrete classes, and uneven geographical and temporal accuracy.
For more details on the methodology see:
Methodology: http://dx.doi.org/10.1787/72a9e331-en