Soil Survey to Characterize 2 Sentinel Sites (CIAT)

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. About the project 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: Project start date: 01/11/2012 Project end date : 01/10/2013

非洲土壤信息服务（African Soil Information Service，缩写AfSIS）所采用的土地退化监测框架（Land Degradation Surveillance Framework，缩写LDSF），被用于对各类生态与土壤健康指标开展系统性生物物理评估。

该LDSF采用层级式空间分层随机抽样方法，以100平方千米的哨兵样区（sentinel landscapes）作为抽样单元，这些样区在统计层面可表征所研究区域内气候、地形与植被的变异特征。

为对未采集样本的区域开展土壤属性预测，研究从具有代表性的采样点位采集了数量相对充足的土壤样本。

为规避传统实验室技术分析大量土壤样本所需的高额成本，本研究采用了近红外与中红外光谱分析技术。

关于本项目
项目标题：农场与景观尺度下制约作物与畜禽生产的关键生物物理因素识别
项目摘要：本项目开展土壤调查以刻画2个哨兵样区（隆（Long）与马图法（Matufa））的特征，并实施农艺调查以估算农户的实际作物产量。
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项目启动日期：2012年11月1日
项目结束日期：2013年10月1日