Soil Survey to Characterize 2 Sentinel Sites (CIAT)
| dc.creator | International Center for Tropical Agriculture | |
| dc.creator | Selian Agricultural Research Institute | |
| dc.date | 2015 | |
| dc.date | 2024-06-04T09:44:22Z | |
| dc.date | 2024-06-04T09:44:22Z | |
| dc.date.accessioned | 2026-06-27T15:20:43Z | |
| dc.description | The Land Degradation Surveillance Framework (LDSF) used by AfSIS was employed to conduct a systematic biophysical assessment of various ecological and soil health metrics. The LDSF was based on a hierarchical spatially stratified, random sampling approach consisting of 100 km2 sentinel landscapes, which were statistically representative of the variability in climate, topography, and vegetation of the study area under consideration. To predict soil properties for areas where samples were not collected, relatively large number of samples from representative locations were taken. To overcome the huge cost of analyzing large soil samples using conventional laboratory techniques, near and mid-infrared spectroscopy approaches were used. Project title: Identification of the Key Biophysical Production Constraints to Crops and Livestock at Farm and Landscape Levels Project abstract: The project undertakes soil survey to characterize 2 sentinel sites (Long and Matufa); and agronomic survey to estimate farmers' actual yield. Project website: http://africa-rising.net/ | |
| dc.identifier | https://hdl.handle.net/10568/144663 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/101695 | |
| dc.language | en | |
| dc.publisher | International Food Policy Research Institute | |
| dc.rights | Open Access | |
| dc.source | International Center for Tropical Agriculture; Selian Agricultural Research Institute. 2015. Soil Survey to Characterize 2 Sentinel Sites (CIAT). Washington, DC: International Food Policy Research Institute. https://doi.org/10.7910/DVN/KLPHCG. Harvard Dataverse. Version 1. | |
| dc.subject | soil analysis | |
| dc.title | Soil Survey to Characterize 2 Sentinel Sites (CIAT) | |
| dc.type | Dataset |