dc.contributor
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.contributor
Universitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai
dc.contributor
Universitat Politècnica de Catalunya. RSLAB - Grup de Recerca en Teledetecció
dc.contributor.author
Sanchez, Nilda
dc.contributor.author
Alonso Arroyo, Alberto
dc.contributor.author
Martinez Fernandez, Jose
dc.contributor.author
Piles Guillem, Maria
dc.contributor.author
Gonzalez Zamora, Angel
dc.contributor.author
Camps Carmona, Adriano José
dc.contributor.author
Vall-Llossera Ferran, Mercedes Magdalena
dc.date.issued
2015-08-01
dc.identifier
Sanchez, N., Alonso-Arroyo, A., Martinez, J., Piles, M., Gonzalez, A., Camps, A., Vall-llossera, M. On the synergy of airborne GNSS-R and landsat 8 for soil moisture estimation. "Remote sensing", 01 Agost 2015, vol. 7, núm. 8, p. 9954-9974.
dc.identifier
https://hdl.handle.net/2117/79572
dc.identifier
10.3390/rs70809954
dc.description.abstract
While the synergy between thermal, optical, and passive microwave observations is well known for the estimation of soil moisture and vegetation parameters, the use of remote sensing sources based on the Global Navigation Satellite Systems (GNSS) remains unexplored. During an airborne campaign performed in August 2014, over an agricultural area in the Duero basin (Spain), an innovative sensor developed by the Universitat Politecnica de Catalunya-Barcelona Tech based on GNSS Reflectometry (GNSS-R) was tested for soil moisture estimation. The objective was to evaluate the combined use of GNSS-R observations with a time-collocated Landsat 8 image for soil moisture retrieval under semi-arid climate conditions. As a ground reference dataset, an intensive field campaign was carried out. The Light Airborne Reflectometer for GNSS-R Observations (LARGO) observations, together with optical, infrared, and thermal bands from Landsat 8, were linked through a semi-empirical model to field soil moisture. Different combinations of vegetation and water indices with LARGO subsets were tested and compared to the in situ measurements. Results showed that the joint use of GNSS-R reflectivity, water/vegetation indices and thermal maps from Landsat 8 not only allows capturing soil moisture spatial gradients under very dry soil conditions, but also holds great promise for accurate soil moisture estimation (correlation coefficients greater than 0.5 were obtained from comparison with in situ data).
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (published version)
dc.format
application/pdf
dc.relation
http://www.mdpi.com/2072-4292/7/8/9954
dc.relation
info:eu-repo/grantAgreement/EC/FP7/607126/EU/European GNSS-R Environmental Monitoring/E-GEM
dc.rights
http://creativecommons.org/licenses/by/3.0/es/
dc.subject
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject
Global Positioning System
dc.subject
Soil moisture--Measurement
dc.subject
Difference water index
dc.subject
High-resolution
dc.subject
GNSS (Sistema de navegació)
dc.subject
Sòls -- Humitat -- Mesurament
dc.title
On the synergy of airborne GNSS-R and landsat 8 for soil moisture estimation
