Soil legacy data rescue via GlobalSoilMap and other international and national initiatives

2018-04-19T15:37:08+00:00

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format.

Rooting for food security in Sub-Saharan Africa

2018-04-19T16:02:33+00:00

There is a persistent narrative about the potential of Sub-Saharan Africa (SSA) to be a 'grain breadbasket' because of large gaps between current low yields and yield potential with good management, and vast land resources with adequate rainfall.

A spatial data infrastructure for storing and exchanging global soil data

2018-04-25T13:59:48+00:00

A spatial data infrastructure for storing and exchanging global soil data The demand for soil data for agro-ecological and other environmental applications at national, regional and global level is growing; establishing a spatial data infrastructure (SDI) for global soil data is key for connecting soil data holders and serving the user community effectively. Organizations [...]

Root zone plant-available water holding capacity of the Sub-Saharan Africa soil, version 1.0. Gridded functional soil information

2018-04-25T14:13:07+00:00

The objective of this project is to produce a robust, quantitative framework, which is updateable and spatially explicit, to generate and maintain functional soil information on root zone depth and associated plant available soil water holding capacity for a major rainfed staple food crop (maize) in sub-Saharan Africa.

Soil data harmonisation and geostatistical modelling efforts in support of improved studies of global sustainability

2018-04-25T14:36:33+00:00

Future Earth and other large international research and development programmes aim to provide the scientific evidence base required for developing into a sustainable future. Soil, which is an important provider of ecosystem services, remains one of the least developed data layers in global land models and uncertainties are large.