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Remote sensing estimation of net primary production as monitoring indicator of holm oak savanna management

机译:净初级生产的遥感估计作为圣栎大草原管理的监测指标

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The management of large areas such as the dehesa (a multifunctional agrosilvopastoral system), with approximately 3 million ha in the Iberian Peninsula, requires effective tools to help decision-making on different scales. This work focuses on the monitoring of pasture production using remote sensors. An adaptation of a Light Use Efficiency (LUE) model has been applied using meteorological data and satellite images on two scales: Regional scale - the dehesa area of Andalusia (Southern Spain) with data of the MODerate resolution Imaging Spectroradiometer (MODIS, MODO9Q1 product) during the hydrological years 2013/2104 and 2014/2015; on a field scale - after pasture improvements, using the earth observation satellites SENTINEL-2 during the hydrological years 2015-2016 and 2016-2017.The adaptation of the model proposed in this work pays special attention to: the spatial and temporal interpolation of meteorological variables; the presence of a tree layer as part of the ecosystem that influences spectral data and needs to be taken into account and subtracted accordingly; the estimation of the fraction of photosynthetically active radiation absorbed by the pasture (fPAR); and the empirical estimation of the light use efficiency for natural grasslands, using biomass field measurements.The results obtained presented an error of around 13%, considered adequate for the applications addressed in this study, suggesting that this approach can be useful as an indicator for monitoring the net primary production in this ecosystem.
机译:在伊比利亚半岛约有300万公顷的大面积地区(dehesa,多功能农林牧系统)的管理,需要有效的工具来帮助进行不同规模的决策。这项工作着重于使用遥感器监测牧场生产。利用气象数据和卫星图像在两个尺度上应用了光利用效率(LUE)模型的改编:区域尺度-安达卢西亚(西班牙南部)的Dehesa区域以及中等分辨率成像光谱仪(MODIS,MODO9Q1产品)的数据在2013/2104年和2014/2015年的水文期间;在野外范围内-在改良牧场之后,在2015-2016年和2016-2017年水文年中使用地球观测卫星SENTINEL-2。对本文提出的模型的改编特别注意:气象的时空插值变量作为生态系统一部分的树层的存在会影响光谱数据,需要予以考虑并相应减去;估计牧场吸收的光合有效辐射的比例(fPAR);以及使用生物量场测量法对天然草地的光利用效率进行实证评估。所获得的结果呈现出约13%的误差,被认为足以应付本研究中的应用,这表明该方法可作为衡量生物多样性的指标。监测该生态系统中的净初级生产。

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