Aboveground Net Primary Production (ANPP), an indicator of ecosystems’ ability to capture and convert solar energy, is critical to evaluate and manage ecosystem carbon balance index including rangelands. Measuring ANPP over a large area is difficult at it varies with different factors including climate and anthropogenic, while satellite-based information shows strong opportunity. The aim of this study was to estimate the ANPP of Plant Functional Types (PFTs) using Landsat-8 imagery over the rangelands of Hir-Neur from Ardabil Province, Iran as a case study area. Landsat-8 Operational Land Imager (OLI) satellite images were collected on 9^th June 2017 aligning with the field sampling of PFTs ANPP. Eleven sampling sites with 10 plots at each site (locations recorded with a Global Positioning System, GPS) were selected along a transect with elevation gradient and the ANPP of PFTs were recorded. Twenty-two vegetation indices were calculated from the Landsat-8 imagery and the index values were extracted for the sampling plots. Correlation between derived indices and field collected ANPP data were calculated. Predictive relationships between PFTs and total ANPP and satellite indices were developed using a 3^rd-order polynomial model and the model was used to map the whole study area. The best estimation of PFTs and total ANPP was obtained using the Vegetation Index (VI3) for grasses (R²=0.47), Iron Oxide (IO) for forbs (R²=0.51), and Renormalized Difference Vegetation Index (RDVI) for shrubs (R²=0.50). The Difference Vegetation Index (DVI) was the best estimator for the total ANPP (R²=0.49). The overall accuracies of the maps were acceptable (MAE, MDE, RMSE <0.5). Results showed a difference when using PFTs for ANPP estimation in comparison with direct ANPP estimation. Thus, direct estimation of ANPP from the satellite based indices would be more accurate. This study also showed promising capabilities of the indices based on PFTs and total ANPP for estimating aboveground biomass, supply-demand balance and carbon balance at the study area and elsewhere with similar ecological conditions. This study also showed opportunity to select the most appropriate vegetation indices for the estimation of PFTs and the total ANPP.

地上净初级生产力（ANPP）是生态系统捕获和转化太阳能的能力的指标，对于评估和管理包括牧场在内的生态系统碳平衡指数至关重要。在大范围内测量ANPP是困难的，因为它会随气候和人为因素等不同因素而变化，而基于卫星的信息则显示出巨大的机会。这项研究的目的是使用伊朗阿尔达比勒省Hir-Neur范围内的Landsat-8影像估算植物功能类型（PFT）的ANPP。在9^日收集了Landsat-8作战陆地成像仪（OLI）卫星图像2017年6月与PFT ANPP的现场采样保持一致。沿着具有高程梯度的样条线选择了11个采样点，每个采样点有10个地块（使用全球定位系统GPS记录的位置），并记录了PFT的ANPP。从Landsat-8影像中计算出22个植被指数，并为采样区提取了指数值。计算了派生指标与现场收集的ANPP数据之间的相关性。植物功能型和总ANPP和卫星指数之间的关系预测用3开发的^第三阶多项式模型，并利用该模型绘制了整个研究领域。使用草的植被指数（VI3）（R ² = 0.47），用草的氧化铁（IO）（R）获得PFT和总ANPP的最佳估计² = 0.51），以及灌木的归一化差异植被指数（RDVI）（R ² = 0.50）。植被差异指数（DVI）是总ANPP（R ²= 0.49）。地图的总体精度是可以接受的（MAE，MDE，RMSE <0.5）。与直接ANPP估算相比，使用PFT进行ANPP估算时，结果显示出差异。因此，从基于卫星的索引直接估计ANPP将更加准确。这项研究还显示了基于PFT和总ANPP的指数在研究区域和具有类似生态条件的其他地区估算地上生物量，供需平衡和碳平衡方面的潜力。这项研究还显示了选择最合适的植被指数来估算PFT和总ANPP的机会。