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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Integration of high- and low-resolution satellite data to estimate pine forest productivity in a Mediterranean coastal area
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Integration of high- and low-resolution satellite data to estimate pine forest productivity in a Mediterranean coastal area

机译：整合高分辨率和低分辨率卫星数据，以估计地中海沿岸地区的松树林生产力

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The estimation of vegetation primary productivity is particularly important in fragile Mediterranean environments that are vulnerable to both natural and human-induced perturbations. The current work was aimed at using remotely sensed data taken by various sensors to infer information about a protected coastal pine forest in Tuscany (Central Italy), which could serve for driving a simplified model of carbon fluxes, C-Fix. Being based on the direct relationship between normalized difference vegetation index (NDVI) and fraction of absorbed photosynthetically active radiation (FAPAR), C-Fix uses satellite and standard meteorological data to simulate gross (GPP) and net (NPP) primary productivity of forest ecosystems. Due to the limited size of the study area, a major difficulty was in creating an NDVI dataset with suitable spatial and temporal resolutions, which was essential for the model functioning. To reach this objective, eight Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images of two years (2000 and 2001) were merged to low-resolution NDVI estimates taken by both the Advanced Very High Resolution Radiometer (AVHRR) and VEGETATION (VGT) sensors. The C-Fix outputs for representative pine forest sites were evaluated by comparison to accurate estimates derived from a model of forest ecosystem processes previously calibrated in a similar environment (Forest-BGC). This analysis showed the potential of C-Fix for rapidly estimating GPP over wide forest areas when suitable NDVI inputs are provided. In particular, a slight superiority of VGT over AVHRR data was demonstrated, which could be reasonably attributed to the relevant higher radiometric and geometric properties. The estimation of NPP was instead quite inaccurate, due to the problematic simulation of forest respiration, which should necessarily rely on more complete modeling operations.
机译：在易受自然和人为干扰的脆弱地中海环境中，估算植被初级生产力特别重要。当前的工作旨在利用各种传感器获取的遥感数据来推断关于托斯卡纳（意大利中部）受保护的沿海松树林的信息，这可以用于驱动简化的碳通量模型C-Fix。 C-Fix基于归一化差异植被指数（NDVI）和吸收的光合有效辐射（FAPAR）的直接关系，使用卫星和标准气象数据来模拟森林生态系统的总（GPP）和净（NPP）初级生产力。由于研究区域的大小有限，主要困难在于创建具有适当时空分辨率的NDVI数据集，这对于模型的功能至关重要。为了实现此目标，将两年（2000年和2001年）的八张Thematic Mapper（TM）/ Enhanced Thematic Mapper Plus（ETM +）图像合并到由超高分辨率高分辨率辐射计（AVHRR）和VEGETATION进行的低分辨率NDVI估计中（VGT）传感器。通过与由先前在类似环境（Forest-BGC）中校准过的森林生态系统过程模型得出的准确估计值进行比较，对代表性松树林地的C-Fix输出进行了评估。该分析表明，如果提供了合适的NDVI输入，C-Fix可以在广阔的森林地区快速估算GPP。特别是，证实了VGT相对于AVHRR数据略有优势，这可以合理地归因于相关的更高的辐射和几何特性。相反，由于对森林呼吸的模拟存在问题，因此对NPP的估算非常不准确，因此必须依赖更完整的建模操作。

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