Paper
11 December 1998 Application of Landsat TM data to evaluate soil hydrological status in the Arno basin, Italy: preliminary results
Francesca Caparrini, Enrica Caporali, Giuliana Profeti
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Francesca Caparrini, Enrica Caporali, and Giuliana Profeti "Application of Landsat TM data to evaluate soil hydrological status in the Arno basin, Italy: preliminary results", Proc. SPIE 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology, (11 December 1998); https://doi.org/10.1117/12.332781
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Cited by 3 scholarly publications.
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KEYWORDS
Soil science

Earth observing sensors

Landsat

Data modeling

Data storage

Vegetation

Capillaries

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