Satellite remote sensing is currently the only means to obtain large scale and broad area spatial and temporal information for earth surface studies. In the field of hydrology, RADAR is the remote sensing system most suitable for estimating surface soil moisture, a key factor in understanding water and energy processes between soil, vegetation and atmosphere, as well as for a more meticulous management of the water resources. Several steps forward have been accomplished, both in better comprehension of radar signal’s behaviour once reaching the ground and in its relation to the quantity of water present in the soil. However, in each method proposed, a certain amount of input data that concerns the site of interest is required, a fact that hinders in some sense the great potential of remote sensing and calls for enormous time resources. This research study consisted an attempt to avoid experimental field measurements, in particular surface roughness and geometry of the vegetation -factors taken into consideration when estimating soil moisture - by use of radar satellite images in conjunction with information extracted from optical satellite data. Furthermore, an alternative, more rapid and efficient method has been sought, for which knowledge of the soil roughness parameters would not be a requirement and in which the radar signal would be corrected from the effect of the vegetation and would be directly related to soil moisture. The results show that, thanks to the increased temporal resolution of new remote sensing instruments and in particular of the Sentinel-1 and Sentinel-2 constellations, we can estimate the soil water content in a site characterised by typical Mediterranean vegetation. This is rendered possible by means of a simple empirical formula that takes into consideration the presence of vegetation from optical data, with precision of the results such (root mean square error –rmse- lower by 5%) that can be appreciated in territories, which, like Sardinia, are affected by long periods of drought during summer and may also exhibit very little variation of soil moisture.

Potenzialità del radar nella stima dell'umidità del suolo in un bacino sperimentale in Sardegna.

FOIS, LAURA
2019-02-21

Abstract

Satellite remote sensing is currently the only means to obtain large scale and broad area spatial and temporal information for earth surface studies. In the field of hydrology, RADAR is the remote sensing system most suitable for estimating surface soil moisture, a key factor in understanding water and energy processes between soil, vegetation and atmosphere, as well as for a more meticulous management of the water resources. Several steps forward have been accomplished, both in better comprehension of radar signal’s behaviour once reaching the ground and in its relation to the quantity of water present in the soil. However, in each method proposed, a certain amount of input data that concerns the site of interest is required, a fact that hinders in some sense the great potential of remote sensing and calls for enormous time resources. This research study consisted an attempt to avoid experimental field measurements, in particular surface roughness and geometry of the vegetation -factors taken into consideration when estimating soil moisture - by use of radar satellite images in conjunction with information extracted from optical satellite data. Furthermore, an alternative, more rapid and efficient method has been sought, for which knowledge of the soil roughness parameters would not be a requirement and in which the radar signal would be corrected from the effect of the vegetation and would be directly related to soil moisture. The results show that, thanks to the increased temporal resolution of new remote sensing instruments and in particular of the Sentinel-1 and Sentinel-2 constellations, we can estimate the soil water content in a site characterised by typical Mediterranean vegetation. This is rendered possible by means of a simple empirical formula that takes into consideration the presence of vegetation from optical data, with precision of the results such (root mean square error –rmse- lower by 5%) that can be appreciated in territories, which, like Sardinia, are affected by long periods of drought during summer and may also exhibit very little variation of soil moisture.
21-feb-2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/261279
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