Verónica Barraza

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.

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00 h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R2) was found between FI and PI with precipitation (R2 > 0.5) and soil moisture (R2 > 0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R2 > 0.7) and evapotranspiration (R2 > 0.5), while PI varied with vegetation phenology. Significant differences (p < 0.01) were found among FI values calculated at the four local times.

Monitoring and modelling land surface dynamics in Bermejo River Basin, Argentina: time series analysis of MODIS NDVI data

The purpose of this work was to monitor and model land surface phenology over the past ten years in the South American Bermejo River basin using the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) product. In order to do this, we evaluated the characteristics of the satellite data and information available on the study areas ecosystem to choose the best model to capture the temporal dynamics of NDVI in local vegetation (sufficiently complex to provide a good fit and simple enough so that each parameter has an immediate ecological meaning). An ecological interpretation of model parameters was provided. Different land surfaces showed distinct fluctuations over time in NDVI values, and this information was used to improve object-oriented classification. A decision tree classification was developed to identify spatial patterns of NDVI functional form and the fluctuations that these patterns presented from 2000 to 2010. We integrated inter-annual information in a final map that distinguishes stable areas from changing sites. Assuming that large inter-annual spatial-scale fluctuations were related to climatic events, we established how vegetated land surfaces within the study area responded to these. Our study was designed to emphasize the interpretation of the spatial and temporal scales of land surface phenology.

Study of multifrequency sensitivity to soil moisture variations in the lower Bermejo basin

Abstract In this paper, a sensitivity analysis to soil moisture variations as a rain effect has been performed at several microwave bands over the lower Bermejo basin, a subtropical area of Argentina mostly spread by moderately dense forests. Parameters such as emissivity and Polarization Index have been considered to carry out the study. In particular, the performance of L-band SMOS measurements has been compared with C and X band AMSR-E one, highlighting the better achievement of the lower frequencies due to the weaker interaction with the vegetation structures. This work intends to give a contribution in the subject of soil moisture sensitivity, which is a preliminary step in the development of retrieval algorithms.

River Water Level Prediction Using Passive Microwave Signatures—A Case Study: The Bermejo Basin

The aim of this work is to investigate the exploitation of radiometric acquisitions from satellite sensors at different microwave frequencies in view of the prediction of river water level. A case study has been identified in the Bermejo basin, in northern Argentina. This river is seasonally affected by severe flooding events in the lower part, mostly due to rains occurring in the upper basin, that produce sediment loadings flushing down along the lower basin thus changing the watercourse. While the effectiveness of microwave radiometry at Ka band for flood monitoring is consolidated in the literature, this study also considers X and C bands (provided by the Advanced Microwave Scanning Radiometer (AMSR) series together with the higher frequency) and highlights the better sensitivity to soil conditions of L band data (made recently available, thanks to SMOS) over moderately and densely vegetated areas. This study confirms, first, the well-known capability of passive microwave remote sensing instruments to record brightness temperature variations due to rainfall and floods occurred near river edges under different seasonal conditions. For this purpose, a multifrequency comparative analysis is conducted. Second, it investigates whether these properties can be exploited for flood forecasting: a model which directly links the daily satellite measurements to the river water level has been tested, considering 1- to 7-day forecast horizons. The results show that forecasting models can take advantage of the sensitivity of low frequencies to soil moisture conditions in order to predict flood peaks, despite the instruments low resolutions.

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.

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.

Satellite estimation of flooded area and river water level dynamics

The objective of this paper is to analyze the dynamics of flooded area and water level in a floodplain wetland. To this end we studied a flood that occurred in 2009-2010 related to an ENSO (El Niño/Southern Oscillation) event over the Paraná River delta. The method for obtaining flooded area fraction (ff) and floodplain water level (WL), which is an extension of previously developed algorithms based on passive data, exploits the synergy of passive and active microwave signatures and model simulations of vegetation emissivity. The results are compared with, and plotted against, water level from Rosario port gauge and water level of a lagoon inside the floodplain obtained by microwave altimetry. This graphs are analyzed in terms of the possible equivalent topography of the floodplain.

Monitoring floods in the lower Bermejo river basin using multifrequency microwave signatures

Using Microwave Remote Sensing techniques represents an important contribution to forecasting skill of regional scale flooding events occurring over time scales of days to weeks. Furthermore, it could add skills to predictions of flood peak timing and magnitude, besides climatic change predictions. In this paper, the temporal trends of Polarization Ratio at some AMSR-E bands (C, X, and Ka) will be studied in order to show its potential in flood and rainfall monitoring. To this end ground truth data concerning rainfall and water level measurements in the lower Bermejo Basin in Argentina have been used, and a general correlation between variations of the Polarization Ratio and ground parameters has been found at the various AMSR-E frequencies.