Agroforestry plays a pivotal role for Sahelian communities by allowing simultaneous improvement of food security and conservation of natural ecosystems and their biodiversity. However, agroforestry systems (AFSs) are particularly heterogeneous in sub-Saharan Africa due to small to very small fields, a large variety of agricultural practices and a diversity of parkland compositions and configurations. This makes spatial sampling processes very important but problematic in terms of representativeness of the landscape heterogeneity to allow an effective study of Sahelian AFSs. In this paper, we proposed, tested and assessed a methodological approach for landscape sampling, mapping and characterization while considering the different types of spatial heterogeneity in complex landscapes, such as Sahelian AFSs. Several complementary methods were combined on the basis of a priori knowledge of agroforestry landscape functioning using multisource data, remote sensing methods, and statistical and spatial analyses applied to landscape ecology. First, the landscape heterogeneity was stratified and used to design two weighted, stratified sampling plans for field surveys of tree species and land use/land cover types. Then, with multisource satellite images together with collected field data, the agroforestry systems were mapped, with a satisfactory accuracy of 85.12% and a Kappa index of 0.81. Finally, we used landscape metrics and diversity indices derived from AFS mapping and the tree species inventory to analyze the diversity of the studied AFS located in the Senegalese Peanut Basin. The results of the analysis evidenced the compositional, configurational and functional heterogeneity found in the study area. This allowed us to demonstrate the ability of the sampling strategy proposed in this paper to capture the various types of heterogeneity in agricultural landscapes. We also showed by implementing the method that it can be used for (i) tree biodiversity analysis, (ii) mapping and (iii) characterization of a complex AFS in sub-Saharan Africa.

农林业通过同时改善粮食安全和保护自然生态系统及其生物多样性，在萨赫勒地区发挥了关键作用。但是，撒哈拉以南非洲地区的农林业系统（AFS）尤其异质，原因是田地面积很小或很小，农业实践种类繁多，公园的组成和构造也多种多样。这使得空间采样过程非常重要，但在景观异质性的代表性方面存在问题，从而无法有效研究萨赫勒AFS。在本文中，我们考虑了Sahelian AFS等复杂景观中不同类型的空间异质性，提出，测试和评估了一种用于景观采样，制图和表征的方法学方法。先验使用多源数据，遥感方法以及应用于景观生态学的统计和空间分析了解农林业景观功能。首先，对景观异质性进行了分层，并用于设计两个加权的分层抽样计划，以进行树种和土地利用/土地覆盖类型的野外调查。然后，利用多源卫星图像以及收集的现场数据，对农林业系统进行了测绘，其准确度达到了85.12％，卡伯指数为0.81。最后，我们使用了从AFS制图和树木物种清单获得的景观指标和多样性指数，来分析位于塞内加尔花生盆地的AFS的多样性。分析结果证明了在研究区域发现的组成，构型和功能异质性。这使我们能够证明本文提出的采样策略能够捕获农业景观中各种类型的异质性。通过实施该方法，我们还证明了该方法可用于（i）树木生物多样性分析，（ii）测绘和（iii）撒哈拉以南非洲复杂AFS的表征。