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Application of Landsat TM data to evaluate soil hydrological status inthe Arno basin, Italy: preliminary results,

机译:应用Landsat TM数据评估意大利阿诺盆地的土壤水文状况:初步结果,

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Abstract: Remote sensing can be a very interesting source of distributed data for large or medium scale hydrological modeling, where soil status and land conditions can be extremely different from one zone to another and a large amount of in-situ measurement would be necessary. In this study two Landsat TM images of the lower part of the Arno basin (Tuscany, Italy) taken in 1991 have been processed using several techniques. Cluster analysis gave interesting results in monitoring the state of soil and vegetation in the two different periods of the year. Clusters obtained have been compared with the distribution of different pedological classes and soil use and with geomorphological information derived from the DTM. Landsat data have been used also to obtain several soil water content indexes, and produce maps of soil moisture. A principal component analysis has been used to obtain data that are directly dependent on soil and as less influenced as possible by other factors like vegetation. Finally, an algorithm to retrieve soil hydraulic properties (permeability, gravitational storage, capillary storage) from geomorphologic data (slope, aspect) and pedological class has been studied, using Monte Carlo simulation and optimization techniques. The spatially distributed hydraulic properties of soil have been applied in a physically based hydrological model. The results have been compared with soil water content indexes obtained from Landsat data analysis on two sub-basins of the Arno river. !11
机译:摘要:遥感可以是大型或中型水文建模的分布式数据的一个非常有趣的源,其中土壤状态和土地条件可能与一个区域到另一个区域非常不同,并且需要大量的原位测量。在这项研究中,使用了1991年的Arno盆地(托斯卡纳,意大利)的下半年LANDSAT TM图像,采用了几种技术处理。集群分析产生了有趣的结果,以监测今年两次不同时期的土壤和植被状况。将获得的簇与不同的小学类和土壤利用的分布进行了比较,以及衍生自DTM的地貌信息。 Landsat数据也已用于获得几种土壤水分含量指标,并产生土壤水分地图。主要成分分析已被用于获得直接依赖土壤的数据,并通过植被等其他因素尽可能少的影响。最后,研究了从蒙特卡罗模拟和优化技术研究了从地貌数据(斜坡,方面)和小学阶层的土壤液压性能(渗透率,重力储存,毛细管存储)的算法。土壤的空间分布式液压性能已应用于物理基础的水文模型。结果已经将结果与土地水含量指标进行了比较,从arno河的两个子盆地上获得的土地水含量指标。 !11

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