Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Sobrino, JA; Franch, B; Mattar, C; Jimenez-Munoz, JC; Corbari, C (2012). A method to estimate soil moisture from Airborne Hyperspectral Scanner (AHS) and ASTER data: Application to SEN2FLEX and SEN3EXP campaigns. REMOTE SENSING OF ENVIRONMENT, 117, 415-428.

Abstract
In this paper the soil moisture is estimated at airborne level and at satellite level by combining remotely sensed images with in situ measurements. At airborne level we process high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor, and at satellite level we compute images acquired with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The study has been accomplished in the framework of two field campaigns in the Barrax region (Spain): the SEN2FLEX (SENtinel-2 and FLuorescence EXperiment) campaign which was developed in July of 2005 and the SEN3EXP (Sentinel-3 Experiment) campaign which was carried out in June of 2009. The methodology proposed considers the correlation between the surface temperature, the Normalized Difference Vegetation Index (NDVI) and the emissivity. With this methodology the soil moisture from AHS data can be obtained with a Root Mean Square Error (RMSE) of 0.05 m(3)/m(3) compared with ground measurements and from ASTER images with a RMSE of 0.06 m(3)/m(3). (C) 2011 Elsevier Inc. All rights reserved.

DOI:
0034-4257

ISSN:
10.1016/j.rse.2011.10.018

NASA Home Page Goddard Space Flight Center Home Page