Thuy Le Toan

On the characterization of agricultural soil roughness for radar remote sensing studies

The surface roughness parameters commonly used as inputs to electromagnetic surface scattering models (SPM, PO, GO, and IEM) are the root mean square (RMS) height s, and autocorrelation length l. However, soil moisture retrieval studies based on these models have yielded inconsistent results, not so much because of the failure of the models themselves, but because of the complexity of natural surfaces and the difficulty in estimating appropriate input roughness parameters. In this paper, the authors address the issue of soil roughness characterization in the case of agricultural fields having different tillage (roughness) states by making use of an extensive multisite database of surface profiles collected using a novel laser profiler capable of recording profiles up to 25 m long. Using this dataset, the range of RMS height and correlation values associated with each agricultural roughness state is estimated, and the dependence of these estimates on profile length is investigated. The results show that at spatial scales equivalent to those of the SAR resolution cell, agricultural surface roughness characteristics are well described by the superposition of a single scale process related to the tillage state with a multiscale random fractal process related to field topography.

Large-Scale Mapping of Boreal Forest in SIBERIA using ERS Tandem Coherence and JERS Backscatter Data

Siberias boreal forests represent an economically and ecologically precious resource, a significant part of which is not monitored on a regular basis. Synthetic aperture radars (SARs), with their sensitivity to forest biomass, offer mapping capabilities that could provide valuable up-to-date information, for example about fire damage or logging activity. The European Commission SIBERIA project had the aim of mapping an area of approximately 1 million km2 in Siberia using SAR data from two satellite sources: the tandem mission of the European Remote Sensing Satellites ERS-1/2 and the Japanese Earth Resource Satellite JERS-1. Mosaics of ERS tandem interferometric coherence and JERS backscattering coefficient show the wealth of information contained in these data but they also show large differences in radar response between neighbouring images. To create one homogeneous forest map, adaptive methods which are able to account for brightness changes due to environmental effects were required. In this paper an adaptive empirical model to determine growing stock volume classes using the ERS tandem coherence and the JERS backscatter data is described. For growing stock volume classes up to 80 m3/ha, accuracies of over 80% are achieved for over a hundred ERS frames at a spatial resolution of 50 m.

On current limits of soil moisture retrieval from ERS-SAR data

Assesses the feasibility of retrieving soil moisture content over smooth bare-soil fields using European Remote Sensing synthetic aperture radar (ERS-SAR) data. The roughness conditions considered in this study correspond to those observed in agricultural fields at the time of sowing. Within this context, the retrieval possibilities of a single-parameter ERS-SAR configuration is assessed using appropriately trained neural networks. Three sources of error affecting soil moisture retrieval (inversion, measurement, and model errors) are identified, and their relative influence on retrieval performance is assessed using synthetic datasets as well as a large pan-European database of ground and ERS-1 and ERS-2 measurements. The results from this study indicate that no more than two soil moisture classes can reliably be distinguished using the ERS configuration, even for the restricted roughness range considered.

Biomass quantification of Andean wetland forages using ERS satellite SAR data for optimizing livestock management

Abstract Spatio-temporal information on the biomass of totora reeds and bofedal water-saturated Andean grasslands, which are a critical forage resource for smallholders in Bolivias Altiplano, is needed to promote their protection and improve livestock management. Satellite radar data appear well adapted to map biomass and to monitor biomass changes in this environment for two reasons: (a) the C-band (5.3 GHz) radar data is particularly sensitive to vegetation biomass when the canopy is over an underlying water surface or a water-saturated soil; this is through the dominant scattering mechanisms involving vegetation–water surface interaction; (b) the cloud cover during the growing period which corresponds to the rainy season. This paper assesses the potential of ERS satellite radar data for retrieving biomass information, which is spatially highly variable owing to the numerous small, nonuniform areas of totora harvesting and bofedal grazing. Ground data, including vegetation humid and dry biomass, were collected over 18 months during satellite descending passes at 12 sites located between the Eastern Cordillera and Titicaca Lake, representing three vegetation units: shoreline and inland totoras, and Puna bofedales. ERS-SAR data were analysed as a function of plant biomass at homogeneous totora and bofedal areas. Because of the small size of these areas (typically 20×30 m), the SAR data need to be processed using an advanced multitemporal filter which improves radiometric resolution without significant reduction of the spatial resolution. The radar backscattering coefficient (σ° in dB) measured by ERS was found to be sensitive at both per site and per vegetation unit levels to humid and dry biomass of totora reeds and bofedal grasslands. The sensitivity of the signal to biomass variation is high for dry biomass ranges less than 1 kg/m2 for totora, and less than 2 kg/m2 for bofedal. The corresponding biomass maps provided by inversion of SAR data are valuable information for livestock management for three critical periods: after the calving season (October–November), when animal pressure is most significant; toward the end of the rainy season (March–April), as an indicator of coming trends to promote the adoption of measures aimed at preventing shortages during the winter season; in the middle of the winter dry season (June–July), to adjust animal charge.

The TropiSAR Airborne Campaign in French Guiana: Objectives, Description, and Observed Temporal Behavior of the Backscatter Signal

The TropiSAR campaign has been conducted in August 2009 in French Guiana with the ONERA airborne radar system SETHI. The main objective of this campaign was to collect data to support the Phase A of the 7th Earth Explorer candidate mission, BIOMASS. Several specific questions needed to be addressed to consolidate the mission concept following the Phase 0 studies, and the data collection strategy was constructed accordingly. More specifically, a tropical forest data set was required in order to provide test data for the evaluation of the foreseen inversion algorithms and data products. The paper provides a description of the resulting data set which is now available through the European Space Agency website under the airborne campaign link. First results from the TropiSAR database analysis are presented with two in-depth analyses about both the temporal radiometric variation and temporal coherence at P-band. The temporal variations of the backscatter values are less than 0.5 dB throughout the campaign, and the coherence values are observed to stay high even after 22 days. These results are essential for the BIOMASS mission. The observed temporal stability of the backscatter is a good indicator of the expected robustness of the biomass estimation in tropical forests, from cross-polarized backscatter values as regarding environmental changes such as soil moisture. The high temporal coherence observed after a 22-day period is a prerequisite for SAR Polarimetric Interferometry and Tomographic applications in a single satellite configuration. The conclusion then summarizes the paper and identifies the next steps in the analysis.

Rice Mapping and Monitoring Using ENVISAT ASAR Data

Radar remote sensing technology has become an important method for stable and long-time rice monitoring for its capability to operate in all weather conditions. In this letter, ENVISAT advanced synthetic aperture radar (ASAR) alternative-polarization VV/HH data were used for rice monitoring in the Xinghua rice experiment site in the middle of Jiangsu Province. First, a threshold classification method was developed for mapping rice growth area according to the different characteristic of backscatter coefficients between paddy rice and other land surface objects. Then, relational models were built for retrieving rice growth parameters from ASAR images based on correlation analysis between backscatter coefficients and field measurements. Meanwhile, an optical multispectral image was used as ancillary data for rice parameters retrieval. As expected, the retrieved rice growth parameters were consistent with those of field measurements.

Accuracy assessment of a large-scale forest cover map of central Siberia from synthetic aperture radar

Russias boreal forests host 11% of the worlds live forest biomass. They play a critical role in Russias economy and in stabilizing the global climate. The boreal forests of central and western Siberia represent the largest unbroken tracts of forest in the world. The European Commission funded SIBERIA project aimed at producing a forest map covering an area of 1.2 million square kilometres. Three synthetic aperture radars (SAR) on board the European remote sensing satellites ERS-1 and ERS-2 and the Japanese Earth resources satellite JERS-1 were used to collect remote sensing data. Radar is the only sensor capable of penetrating cloud cover and imaging at night. An adaptive, model-based, contextual classification to derive ranked total growing stock volume classes suitable for large-scale mapping is described. The accuracy assessment of the Siberian forest cover map is presented. The weighted coefficient of agreement κw is calculated to quantify the agreement between the classified map and the reference data. First, the classified map is compared with Russian forest inventory data (κw = 0.72). The inherent uncertainty in the forest inventory data is simulated by allowing for fuzziness. The effect of uncertainty on the unweighted coefficient of agreement κ is stronger than that on the weighted coefficient of agreement κw. Second, the map is compared with a more reliable, independent posterior ground survey by Russian forestry experts (κw = 0.94). The follow-on project SIBERIA-II started in January 2002 and is striving to develop multisensor concepts for greenhouse gas accounting (www.siberia2.uni-jena.de).

Computer and remote‐sensing infrastructure to enhance large‐scale testing of individual‐based forest models

Global environmental change necessitates increased predictive capacity; for forests, recent advances in technology provide the response to this challenge. “Next-generation” remote-sensing instruments can measure forest biogeochemistry and structural change, and individual-based models can predict the fates of vast numbers of simulated trees, all growing and competing according to their ecological attributes in altered environments across large areas. Application of these models at continental scales is now feasible using current computing power. The results obtained from individual-based models are testable against remotely sensed data, and so can be used to predict changes in forests at plot, landscape, and regional scales. This model–data comparison allows the detailed prediction, observation, and testing of forest ecosystem changes at very large scales and under novel environmental conditions, a capability that is greatly needed in this time of potentially massive ecological change.

Sensitivity of X-, C-, and L-Band SAR Backscatter to Burn Severity in Mediterranean Pine Forests

Synthetic aperture radar (SAR) data at X-, C-, and L-bands have been investigated to determine the relationship between backscatter and forest burn severity over three sites in Spain. The dependence of SAR backscatter on local incidence angle and environmental conditions has been analyzed. At HH and VV polarizations, the backscatter increased with burn severity for X- and C-bands, whereas it decreased for L-band. Cross-polarized (HV) backscatter decreased with burn severity for all frequencies. Determination coefficients were used to quantify the relationship between radar backscatter and burn severity for given intervals of local incidence angle. For X- and C-band copolarized data, higher determination coefficients were observed for slopes oriented toward the sensors, whereas for cross-polarized data, the determination coefficients were higher for slopes oriented away from the sensor. At L-band, the association strength of cross-polarized data to burn severity was high for all local incidence angles. C- and L-band cross-polarized backscatter showed better potential for burn severity estimation in the Mediterranean environment when the local incidence angle is accounted for. The small dynamic range observed for X-band data could hinder its use in forests affected by fires.

Role of atmospheric circulation with respect to the interannual variability in the date of snow cover disappearance over northern latitudes between 1988 and 2003

[1] This paper analyzes the main spatial patterns in the dates of snow cover disappearance variability over northern latitudes between 1988 and 2003. The dates of snow cover disappearance were calculated using satellite passive microwave data from the Special Sensor Microwave/Imager. Spatial and temporal patterns were obtained using principal components analysis in the S mode. We identified eight components, each representing a large region characterized by homogeneous interannual variability in the dates of snow cover disappearance. We found that atmospheric circulation, summarized by means of teleconnection indices, had an important impact on the date of snow cover disappearance for most of these regions. A role is played by the Arctic Oscillation in western Siberia, the spring east Atlantic/west Russian pattern in central Siberia, and the Pacific North