首页> 外文会议>Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology; 20070918-20; Florence(IT) >Integration of Ground and Satellite Data to Simulate Forest Carbon Budget on Regional Scale
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Integration of Ground and Satellite Data to Simulate Forest Carbon Budget on Regional Scale

机译:整合地面和卫星数据以模拟区域规模的森林碳收支

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Simulating the main terms of forest carbon budget (GPP, NPP, NEE) is important for both scientific and practical reasons. This operation was performed for a region of Central Italy (Tuscany) by the integrated processing of ground and satellite data. Several data layers (meteorology, forest type, volume, etc.) were first collected in order to characterize the eco-climatic and forest features of the region. FAPAR estimates with 1 km resolution were obtained by processing VGT NDVI data. Relying on these data sets, monthly estimates of forest GPP were produced by means of a simplified, NDVI-based parametric model, C-Fix. These GPP estimates were used to calibrate a well known bio-geochemical model, BIOME-BGC, in order to find its best configurations for simulating all main functions (photosynthesis, respirations, allocations, etc.) of the most widespread Tuscany forest types. The calibrated versions of BIOME-BGC were then applied to produce respiration estimates for all regional forest surfaces during the study period. The obtained GPP and respiration estimates, which were referred to equilibrium conditions, were converted into the values of actual forests by applying a simplified approach which relies on the ratio of actual over potential tree volume as an indicator of forest distance from climax. The C-Fix photosynthesis estimates of actual forests were finally integrated with relevant BIOME-BGC simulated respirations in order to assess net forest carbon fluxes.
机译:出于科学和实践的原因,模拟森林碳预算的主要术语(GPP,NPP,NEE)非常重要。通过对地面和卫星数据进行综合处理,对意大利中部(托斯卡纳)地区执行了此操作。首先收集了几个数据层(气象,森林类型,体积等),以表征该地区的生态气候和森林特征。通过处理VGT NDVI数据可获得1 km分辨率的FAPAR估计值。依靠这些数据集,通过简化的基于NDVI的参数模型C-Fix得出了森林GPP的月度估算值。这些GPP估算值用于校准众所周知的生物地球化学模型BIOME-BGC,以便找到其最佳配置,以模拟最广泛的托斯卡纳森林类型的所有主要功能(光合作用,呼吸作用,分配等)。然后,在研究期间,将经过校准的BIOME-BGC版本应用于所有区域森林表面的呼吸估计。通过使用简化方法,将获得的GPP和呼吸估计值(称为平衡条件)转换为实际森林的值,该方法依赖于实际树木与潜在树木体积之比作为森林与高潮距离的指标。最终,将实际森林的C-Fix光合作用估计值与相关的BIOME-BGC模拟呼吸相结合,以评估森林净碳通量。

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