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On the Influences of vegetation biomass on COSMO-Skymed X-band

机译：植被生物量对COSMO-Skymed X波段的影响

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The knowledge of spatial and temporal variability of land cover is important to manage water resources for yield forecasting, water stress prediction, irrigation water management and flood protection. Cloud cover dramatically reduces the temporal resolution of optical data thus limiting their operational use; in addition, the spatial resolution is often inadequate for applications in heterogeneous areas. On the other hand, algorithms based on Synthetic Aperture Radar (SAR) implemented to retrieve vegetation parameters are not yet fully validated. New SAR missions (COSMO-Skymed and Terrasar-X) may represent a suitable source of data for operational uses due to the high spatial and temporal resolution, although X band is not optimal for agricultural and hydrological applications. This paper reports the influence of soil-vegetation variables (especially biomass indices) on X-band COSMO-Skymed data using Ping Pong products. The study is carried out over two different sites: the SELE plain (in the south-eastern part of Campania, Italy) that is mainly characterized by herbaceous plants and tree crops; and the Campobello-Castelvetrano area (in the south-western part of Sicily, Italy) mainly covered by olive trees, vineyards and woods. The sensitivity analysis is performed by comparing vegetation indices (NDVI or LAI) derived by Landsat TM 5 and ETM+ 7 with COSMO-Skymed (CSK) images acquired in May-June 2010 within the project COSMOLAND (Use of COSMO-SkyMed SAR data for LAND cover classification and surface parameters retrieval over agricultural sites) funded by the Italian Space Agency (ASI). Sensitivity analysis results address to develop algorithms to retrieve vegetation biomass maps from CSK X band characterized by high temporal and spatial resolution.
机译：土地覆盖物的时空变化知识对于管理水资源以进行产量预测，水压力预测，灌溉水管理和防洪至关重要。云层极大地降低了光学数据的时间分辨率，从而限制了其操作用途；另外，空间分辨率通常不足以用于异构区域。另一方面，基于合成孔径雷达（SAR）的用于检索植被参数的算法尚未得到充分验证。尽管X波段并不是农业和水文应用的最佳选择，但新的SAR任务（COSMO-Skymed和Terrasar-X）可能由于高的时空分辨率而代表了适合业务使用的数据源。本文使用乒乓产品报告了土壤植被变量（尤其是生物量指数）对X波段COSMO-Skymed数据的影响。该研究在两个不同的地点进行：SELE平原（在意大利坎帕尼亚的东南部），主要特征是草本植物和树木。以及Campobello-Castelvetrano地区（位于意大利西西里岛的西南部），主要覆盖有橄榄树，葡萄园和树林。通过将Landsat TM 5和ETM + 7得出的植被指数（NDVI或LAI）与2010年5月至6月在COSMOLAND项目中获得的COSMO-Skymed（CSK）图像进行比较（使用LAND的COSMO-SkyMed SAR数据），进行了敏感性分析。由意大利航天局（ASI）资助的覆盖分类和在农业场地的地表参数检索。敏感性分析结果致力于开发从具有高时空分辨率的CSK X波段检索植被生物量图的算法。

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