Facundo Carmona

SMOS Level-2 Soil Moisture Product Evaluation in Rain-Fed Croplands of the Pampean Region of Argentina

A field campaign was carried out to evaluate the Soil Moisture (SM) MIR_SMUDP2 product (v5.51) generated from the data of the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) aboard the Soil Moisture and Ocean Salinity (SMOS) mission. The study area was the Pampean Region of Argentina, which was selected because it is a vast area of flatlands containing quite homogeneous rain-fed croplands, which are considered SMOS nominal land uses and hardly affected by radio-frequency interference contamination. Transects of ground handheld SM measurements were performed using ThetaProbe ML2x probes within four Icosahedral Snyder Equal Area Earth (ISEA) grid nodes, where permanent SM stations are located. The campaign results showed a negative bias of -0.02 m3m-3 between concurrent SMOS data and ground SM measurements, which means a slight SMOS underestimation, and a standard deviation of ±0.06 m3m-3. Additionally, a good correlation was obtained between the handheld SM measurements taken during the campaign and the permanent SM station data within a node, which pointed out that the station data could be used as reference data to evaluate the SMOS product over a longer temporal period. SMOS-retrieved data were also compared with station mean SM values from 2012 to 2014. A general SMOS underestimation of -0.05 m3m-3 was observed, with a standard deviation of ±0.04 m3m-3, which yields an uncertainty of ±0.07 m3m-3 for the SMOS product. Although the random error meets the SMOS missions goal of ±0.04 m3m-3, the product overall uncertainty is higher than that due to the significant dry bias, which is also found in other regions of the world.

Vegetation Index to estimate chlorophyll content from multispectral remote sensing data

Abstract Normalized Area Vegetation Index (NAVI) is proposed for estimating chlorophyll content (Chl) from remote sensing data. NAVI is obtained using only two bands on red and near infrared regions of the spectrum. It is derived from the hyperspectral NAOC index, which was initially developed for the Chl mapping. For determining the relationship between NAOC and NAVI we used 257 spectra obtained with the Proba/CHRIS sensor during the SPARC-2003/2004 campaigns in Barrax, Spain. NAVI was estimated with different pairs of bands and a correlation matrix with NAOC index was obtained. Results show very good linear correlation coefficients, with values ≥ 0.97. NAVI allows to estimate leaf Chl from satellite data with medium spectral resolution.

A method for soil moisture probes calibration and validation of satellite estimates

Graphical abstract