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首页> 外文期刊>Remote Sensing >Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series
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Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series

机译:利用FAPAR时间序列的物候度量标准对萨赫勒牧场的饲料生物量进行监测

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Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables—large seasonal integral (LINTG), length of growing season, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999–2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77), indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51) and should improve the operational monitoring of forage resources in Sahelian rangelands.
机译:及时监测植物生物量对于萨赫勒牧场的牧草资源管理至关重要。萨赫勒地区年生物量产量的估算基于卫星年均标准化植被指数(NDVI)与原地生物量数据之间的简单关系。这项研究提出了一种新的方法,该方法使用了来自吸收光合有效辐射分数(FAPAR)的SPOT-VEGETATION时间序列和原位生物量之间的物候指标之间的多线性模型。具有三个变量(大季节积分(LINTG),生长季节的长度和季节结束的减少率)的模型在以下条件下表现最佳(MAE = 605 kg·DM / ha; R 2 = 0.68)塞内加尔的萨赫勒生态系统(1999-2013年期间的数据)。具有年度最大值(PEAK)和季节开始日期的模型表现出相似的表现(MAE = 625 kg·DM / ha; R 2 = 0.64),从而可以及时估计草料的可利用量。生态区域中研究区域的细分提高了总体精度(MAE = 489.21 kg·DM / ha; R 2 = 0.77),表明度量标准与生态系统特性之间存在关系。 LINTG是具有高叶片生物量的木质牧场的主要解释变量,而对于以草木植被为主的地区,它是PEAK度量。该方法的性能优于已建立的基于NDVI的生物量产品(MAE = 818 kg·DM / ha,R 2 = 0.51),并应改善萨赫勒牧场的牧草资源运营监控。

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