Mercedes Salvia

Model investigation about the potential of C band SAR in herbaceous wetlands flood monitoring

Wetlands are areas where the presence of water at or near the soil surface drives the natural system. Imaging radars (SARs) have distinct characteristics which make them of significant value for monitoring and mapping wetland inundation dynamics. The presence or absence of water (which has a much higher dielectric constant than dry or wet soil) in wetlands may significantly alter the signal detected from these areas depending on the dominant vegetation type, density, and height. The objective of this paper is to present our current research efforts to explain and correctly simulate the radar response of wetland vegetation/inundation mixtures, and use simulations as an aid for retrieval applications. The radar response of junco marshes under different flood conditions and vegetation stages is analysed using a set of 13 multipolarization ENVISAT ASAR scenes acquired over the Paraná River Delta marshes during the period 2003–2005. The main aspect of the approach followed is the simulation of SAR wave interactions with vegetation and water, using an adapted and improved version of the EM model developed at Tor Vergata University. The results obtained indicate that with the refined EM model, it is possible to represent with a good accuracy VV and HH SAR responses of junco marshes for a variety of environmental conditions. Further work and data are needed to explain measured HV backscattering. The general agreement obtained between simulations and observations permitted the development of a simple retrieval scheme, and estimates of water level below the canopy were obtained for different environmental conditions. RMS errors of forward simulations and retrievals are reported and discussed.

The Effect of Rain and Flooding Events on AMSR-E Signatures of La Plata Basin, Argentina

The objective of this paper is to describe and explain the effects on selected AMSR-E channels of two strong events, i.e., a rainstorm and a flooding, occurred in the Argentine section of La Plata basin. More specifically, the rainstorm took place within the Chaco region, which is covered by a continuous, moderately dense forest. The flooding affected the terminal part of Parana¿ River. The study is based on monitoring the temporal trends of the polarization indexes at various AMSR-E bands. In the forest, the rainstorm produces an effect on C band channels which is moderate, but well evident. The presence of this effect agrees with model simulations presented in previous papers. In the Parana¿ River, measurements of water level are available. Variations of polarization index at various frequencies are observed in correspondence with variations of water level in four different stations. However, the amount of the effect and the correlation between variables are dependent on the properties of the areas surrounding the stations. The Delta of Parana¿ river, where a land cover map is available, was selected for estimation of fraction of flooded area by using an algorithm available in the literature.

Monitoring Vegetation Moisture Using Passive Microwave and Optical Indices in the Dry Chaco Forest, Argentina

Information about daily variations of vegetation moisture is of widespread interest to monitor vegetation stress and as a proxy to evapotranspiration. In this context, we evaluated optical and passive microwave remote sensing indices for estimating vegetation moisture content in the Dry Chaco Forest, Argentina. The three optical indices analyzed were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Infrared Index (NDII) and, for the microwave region the Frequency Index (FI). All these indices are mainly sensitive to leaf area index (LAI), but NDWI and NDII, and FI are also sensitive to leaf water content (LWC) and Canopy Water Content (CWC) respectively. Using optical and microwave radiative transfer models for the vegetation canopy, we estimated the range of values of LAI, LWC and CWC that can explain both NDWI/NDII and FI observations. Using a combination of simulations and microwave and optical observations, we proposed a two step approach to estimate leaf and canopy moisture content from NDWI, NDII and FI. We found that the short variation of LWC estimated from NDWI and NDII present a dynamic range of values which is difficult to explain from the biophysical point of view, and it is partially related to atmosphere contamination and canopy radiative transfer model limitations. Furthermore, the observed FI short-term variations (~ 8 days) cannot be explained unless significant CWC variations are assumed. The CWC values estimated from FI present a short-term variations possibly related to vegetation hydric stress.

Comparing soil moisture retrievals from SMOS, ASCAT and AMSR-E over the Pampas plains

Currently, there are several satellite systems of coarse spatial resolution that observe the Earth in the microwave region of the electromagnetic spectrum. They provide operational soil moisture products, among them AMSR-E/LPRM, ASCAT, SMOS. This work aims at answering the following questions: 1) are these products comparable?, 2) how does one evaluate their quality and if they are realistic in view of the lack of in situ data at their spatial scale? To answer these questions, we have analyzed time series of the soil moisture product for the different systems mentioned above. Two types of analysis were performed: a) analysis of spatial anomalies and their correlations, b) analysis of temporal anomalies and application of the Triple Collocation method for error estimation. Land cover maps, precipitation data and NDVI time series were used as ancillary information.

Monitoring and modeling land surface dynamics in Bermejo River Basin, Argentina: Time series analysis of MODIS and AMSR-E data

In this paper, we show that MODIS NDVI and AMSR-E microwave vegetation indexes (MVI) data can be used to monitor land surface phenology in the Bermejo River Basin. For this purpose, the statistical nature of the study areas NDVI and MVI time series was analyzed. For NDVI, widely known time series models were tested and modified. NDVI temporal variation trends show functional forms that originate from the general annual performance of land surface phenology. Using these functional forms, a classification scheme is proposed. Furthermore, we also explored the possibility to use MVIs in order to improve the classification using assumptions about canopy structure that influence vegetation emissivity and opacity.

C-Band Radiometric Response to Rainfall Events in the Subtropical Chaco Forest

In this letter, multitemporal signatures collected by Advanced Microwave Scanning Radiometer (AMSR-E) over the dry forest of Chaco, located in North Argentina, are analyzed. The forest has a biomass of about 100 t/ha and a woody volume of about 120 m3/ha. A clear increase of polarization index at C-band is observed after intense rain events in two different locations. Simulations of a discrete model attribute this effect to variations of soil moisture and predict an effect comparable with the measured one. Results indicate that there is a potential to monitor soil moisture variations below dry forests with moderate biomass, also in view of the forthcoming availability of L-band data.

Monitoring flooded area fraction in floodplains of Paraná basin using passive and active microwave systems

Over the past two decades, orbital passive microwave systems have proven to be sensitive to flood condition in large floodplains. This sensitivity is rooted in the well differentiated emission properties of calm water with respect to non-flooded land of any kind. In this paper, AMSR-E observations of an herbaceous wetland area on the Paraná River sub-basin were analyzed during the 2009–10 timeframe when this region was affected by a strong and long lasting flooding. Evident effects on the difference between vertically and horizontally polarized brightness temperatures (ΔT) were observed at C-band. The fraction of vegetated flooded area was estimated by applying an improved algorithm which uses ENVISAT ASAR data at specific dates to calibrate AMSR-E temporal series. Also, using a theoretical emission model, the behavior of ΔT flooded is discussed.

AMSR-E observations of rain and flood events over vegetated areas of LA Plata basin

This work analyzes AMSR-E signatures collected in two sites of La Plata basin, in South America. Within the wide Chaco forest, an area close to Las Lomitas meteorological station was selected. Here the forest is uniform, but not very dense, with biomass values in the range 70–120 t/ha. After strong rain events, appreciable variations of polarization index at C and X band were observed. As expected, the better dynamic range is obtained at C band. Also AMSR-E signatures collected during a strong flooding event in the Delta of Paraná River were analyzed. Variations of polarization index are strong, as expected. Information about the water level in the river was made available by hydrometric stations. We selected specific pixels characterized by different kinds of land cover: agricultural fields, marshes, and planted forests. A significant correlation between polarization index (at various frequencies) and water level is proved. A flood monitoring algorithm based on AMSR-E brightness temperature difference is tested. Optical and radar data are used as ancillary input for calibration and validation proposes.

Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

Abstract In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

Time series of microwave derived products: Looking for disturbances in argentine Chaco Forest region

The objective of this article is to compare the trends of two vegetation indices (MODIS EVI (optical) and AMSR-E/ LPRM VOD (microwave)) using BFAST (Breaks For Additive Seasonal and Trend) method to monitor vegetation dynamics during the period 2002-2011. The comparison was carried out on a dry forest area in Argentina, Dry Chaco Forest, where deforestation is common. We show that BFAST detects several classes of changes in the analyzed timeframe (related to major phenological changes), accounting for abrupt disturbances and gradual trends. Differences between the classes of the major trend changes were found in the two time series analyzed. These results show the potential to combine optical and passive microwave indices to identify different classes of disturb.