Semiarid and savanna‐type (SAST) ecosystems in East Africa have unique plant species compositions and characteristics that make quantifying this biome's seasonality and interannual variability difficult. Phenoregion classification offers a way to use seasonality of vegetation growth to help understand the phenological spatial patterns of complex landscapes. Here, we used Normalized Difference Vegetation Index (NDVI) time series from Landsat 8 to map phenoregions in scenes centered around national parks from Mt. Kenya National Park (Kenya) to Limpopo National Park (Mozambique). We then assessed whether landscape‐scale controls on phenology are consistent across the region or whether they vary across this latitudinal gradient. We compared our phenoregion maps to MODIS Land Cover and geology, and we used multinomial logistic regression to determine the role that elevation, slope, aspect, and geology play in driving phenological differences. The sites' phenoregions showed no unique land cover composition, suggesting that MODIS land cover does not capture the subtle variations identified in phenoregion analysis. Multinomial logistic regression showed that geographic trend (x‐ and y‐directions) was a strong predictor in four of the five landscapes and that, depending on the scene, geology, elevation, or aspect was a strong secondary predictor. Using seasonality of the NDVI time series to generate phenoregions provides different and, in some cases, more ecologically relevant information, compared to vegetation maps that use only land cover from a single season or time period to generate ecoregions. With a significant population of humans and animals that live in and depend on SAST ecosystems, it is important to better understand vegetation processes and factors that affect them as climate change becomes an increasingly pertinent issue in dry systems.

中文翻译：

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东非大断面上来自陆地卫星的表象区域的环境控制

东非的半干旱和热带稀树草原（SAST）生态系统具有独特的植物物种组成和特征，难以量化该生物群落的季节性和年际变异性。物域划分提供了一种利用植被生长的季节性来帮助了解复杂景观的物候空间格局的方法。在这里，我们使用了Landsat 8的归一化植被指数（NDVI）时间序列来绘制以山峰国家公园为中心的场景中的表象区域。肯尼亚国家公园（肯尼亚）至林波波国家公园（莫桑比克）。然后，我们评估了景观学方面的物候尺度控制在整个区域是否一致，或者在整个纬度梯度上是否有所不同。我们将phenoregion地图与MODIS Land Cover和地质进行了比较，我们使用多项式逻辑回归来确定海拔，坡度，坡向和地质在驱动物候差异方面的作用。站点的表层区域没有显示出独特的土地覆被组成，这表明MODIS的土地覆被并未捕获表层区域分析中发现的细微变化。多项式Lo​​gistic回归显示地理趋势（x和y方向）在五个景观中的四个中是一个很强的预测指标，并且取决于场景，地质状况，海拔或纵横比是一个重要的次要预测指标。与仅使用单个季节或时间段内的土地覆盖来生成生态区的植被图相比，使用NDVI时间序列的季节性来生成phenoregions可以提供不同的信息，在某些情况下，还可以提供更多与生态相关的信息。由于存在大量人类和动物，并依赖于SAST生态系统，因此重要的是要更好地了解植被过程和影响其的因素，因为气候变化已成为干旱系统中日益重要的问题。