Abstract This study aimed to evaluate the potential use of normalized difference vegetation index (NDVI) from satellite-derived remote sensing data for monitoring rodent abundance in semi-arid areas of Tanzania. We hypothesized that NDVI could potentially complement rainfall in predicting rodent abundance spatially and temporally. NDVI were determined across habitats with different vegetation types in Isimani landscape, Iringa Region, in the southern highlands of Tanzania. Normalized differences in reflectance between the red (R) (0.636–0.673 mm) and near-infrared (NIR) (0.851–0.879 mm) channels of the electromagnetic spectrum from the Landsat 8 [Operational Land Imager (OLI)] sensor were obtained. Rodents were trapped in a total of 144 randomly selected grids each measuring 100 × 100 m2, for which the corresponding values of NDVI were recorded during the corresponding rodent trapping period. Raster analysis was performed by transformation to establish NDVI in study grids over the entire study area. The relationship between NDVI, rodent distribution and abundance both spatially and temporally during the start, mid and end of the dry and wet seasons was established. Linear regression model was used to evaluate the relationships between NDVI and rodent abundance across seasons. The Pearson correlation coefficient (r) at p ≤ 0.05 was carried out to describe the degree of association between actual and NDVI-predicted rodent abundances. The results demonstrated a strong linear relationship between NDVI and actual rodent abundance within grids (R2 = 0.71). NDVI-predicted rodent abundance showed a strong positive correlation (r = 0.99) with estimated rodent abundance. These results support the hypothesis that NDVI has the potential for predicting rodent population abundance under smallholder farming agro-ecosystems. Hence, NDVI could be used to forecast rodent abundance within a reasonable short period of time when compared with sparse and not widely available rainfall data.

中文翻译：

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归一化差异植被指数（NDVI）在坦桑尼亚半干旱地区小农农业生态系统啮齿动物种群丰度预测中的应用

摘要 本研究旨在评估来自卫星遥感数据的归一化差异植被指数 (NDVI) 在监测坦桑尼亚半干旱地区啮齿动物丰度方面的潜在用途。我们假设 NDVI 可以潜在地补充降雨量在空间和时间上预测啮齿动物丰度。NDVI 是在坦桑尼亚南部高地伊林加地区 Isimani 景观中不同植被类型的栖息地中确定的。获得了来自 Landsat 8 [Operational Land Imager (OLI)] 传感器的电磁波谱的红色 (R) (0.636–0.673 mm) 和近红外 (NIR) (0.851–0.879 mm) 通道之间反射率的归一化差异。啮齿动物被困在总共 144 个随机选择的网格中，每个网格的尺寸为 100 × 100 m2，在相应的啮齿动物诱捕期间记录了相应的 NDVI 值。通过转换进行栅格分析，以在整个研究区域的研究网格中建立 NDVI。建立了旱季和雨季开始、中期和结束期间 NDVI、啮齿动物分布和丰度之间的空间和时间关系。线性回归模型用于评估 NDVI 与跨季节啮齿动物丰度之间的关系。进行 p ≤ 0.05 的 Pearson 相关系数 (r) 来描述实际和 NDVI 预测的啮齿动物丰度之间的关联程度。结果表明 NDVI 与网格内实际啮齿动物丰度之间存在很强的线性关系 (R2 = 0.71)。NDVI 预测的啮齿动物丰度显示出很强的正相关（r = 0. 99) 估计的啮齿动物丰度。这些结果支持 NDVI 具有预测小农农业生态系统下啮齿动物种群丰度的潜力的假设。因此，与稀疏且不广泛可用的降雨数据相比，NDVI 可用于在合理的短时间内预测啮齿动物的丰度。