Paper
30 December 1997 Evaluation of spatially distributed remotely sensed data to estimate hydrologically related parameters
Roberto Colombo, Pietro Alessandro Brivio, Eugenio Zilioli, Marco Mancini
Author Affiliations +
Proceedings Volume 3222, Earth Surface Remote Sensing; (1997) https://doi.org/10.1117/12.298144
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom
Abstract
In this study spatially distributed and semi-distributed hydrological-related parameters, such as the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), albedo and surface temperature, were evaluated by means of multitemporal optical remotely sensed data and field radiometric measurements acquired in different hydrologic conditions of the Virginiolo catchment (Italy). Land use land cover classifications were performed using Landsat Thematic Mapper (TM) data of spring and summer seasons. Digital counts were converted into calibrated radiance values and, after atmospheric correction, reflectance measurements were obtained. To estimate the spatially distributed LAI values and their changes related to the modifications of environmental and agrometeorological conditions within the catchment area, an empirical relationship between NDVI and LAI for Mediterranean areas reported in literature was used. Broadband surface albedo was estimated from spectral reflectance measurements obtained from the TM narrow bands following Brest & Goward's approach, and surface temperature was derived from the TM channel 6. Radiometric and thermoradiometric measurements, collected over selected fields were used to estimate the same hydrological-related parameters. When satellite images are not available, due to the presence of clouds, such parameters may be used in a semi-distributed hydrological modeling.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roberto Colombo, Pietro Alessandro Brivio, Eugenio Zilioli, and Marco Mancini "Evaluation of spatially distributed remotely sensed data to estimate hydrologically related parameters", Proc. SPIE 3222, Earth Surface Remote Sensing, (30 December 1997); https://doi.org/10.1117/12.298144
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KEYWORDS
Reflectivity

Earth observing sensors

Satellites

Landsat

Vegetation

Temperature metrology

Clouds

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