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The objective of this letter is to provide a better understanding of the impact of temporal decorrelation on the tomographic phase of the P-band synthetic aperture radar (SAR) mission BIOMASS, selected as the Seventh Earth Explorer by the European Space Agency. In the context of Phase A BIOMASS activities, the tropical forest site of Paracou, French Guiana, was illuminated at P-band during the airborne campaign TropiSAR 2009 and the ground-based campaign TropiScat 2011. P-band data from TropiSAR were used to generate a high-resolution 3-D reconstruction of the Paracou forest, whereas TropiScat data provided information about temporal correlation considering different time lags and different heights within the vegetation layer. The ensemble of the two datasets were used to generate a synthetic SAR data stack that emulates BIOMASS acquisitions over the Paracou forest site, accounting for BIOMASS geometry and resolution, as well as for the forest temporal decorrelation. Different data stacks were produced by varying the revisit time between two consecutive passes from 1 to 17 days. The resulting vertical structure reconstruction and forest height retrieval were observed to yield valuable results as long as the revisit time is 4 days or less. [ABSTRACT FROM PUBLISHER]

In this letter, we present the results from the ground-based European Space Agency campaign TropiScat, which is aimed at evaluating the temporal coherence at P-band in a tropical forest in all polarizations and at different heights within the vegetation layers. The TropiScat equipment has been operated since October 2011 at the Paracou field station, French Guiana, to continuously produce height–range images of the forest with a temporal sampling of 15 min. The forest temporal behavior can be then captured by analyzing the interferometric coherence between the images gathered at different times, considering time scales on the order of hours, days, and months. The results indicate that the vegetation is likely to undergo a significant motion during day hours due to wind and temperature changes, whereas it appears to be definitively more stable during night hours. This result appears to provide a very useful input to the Biomass Monitoring Mission for Carbon Assessment (BIOMASS), as it suggests that the performance over a tropical forest could be optimized by gathering acquisitions in early morning or night hours. The long-term temporal decorrelation has been then evaluated by considering dawn–dawn acquisitions to minimize the impact of wind gusts and by excluding rainy days in order to not confuse forest and system decorrelation. As a result, the temporal coherence at the ground level was found to stay high at about 0.8 at 27 days, whereas the temporal coherence at the canopy height was found to be about 0.8 at 4 days and about 0.65 at 27 days, indicating coherence sensitivity to height. [ABSTRACT FROM PUBLISHER]

It has been widely reported that tree leaves have tended to appear earlier in many regions of the northern hemisphere in the last few decades, reflecting climate warming. Satellite observations revealed an 8-day advance in leaf appearance date between 1982 and 1991 in northern latitudes. In situ observations show that leaf appearance dates in Europe have advanced by an average of 6.3 days from 1959 to 1996. Modelling of leaf appearance on the basis of temperature also shows a marked advance in temperate and boreal regions from 1955 to 2002. However, before 1955, reported studies of phenological variations are restricted to local scale. Modelling, ground observations and satellite observations are here combined to analyse phenological variations in Eurasian taiga over nearly a century. The trend observed by remote sensing consists mainly in a shift at the end of the 1980s, reflecting a shift in winter and spring temperature. In western boreal Eurasia, a trend to earlier leaf appearance is evident since the mid-1930s, although it is discontinuous. In contrast, the strong advance in leaf appearance detected over Central Siberia using satellite data in 1982–1991 is strengthened by late springs in 1983–1984; moreover, in this region the green-up timing has displayed successive trends with opposite signs since 1920. Thus, such strong trend is not unusual if considered locally. However, the recent advance is unique in simultaneously affecting most of the Eurasian taiga, the leaf appearance dates after 1990 being the earliest in nearly a century in most of the area. [ABSTRACT FROM AUTHOR]

This paper presents the use of time series of SAR images to map the flood temporal dynamics and the spatial distribution of vegetation over a large Amazonian floodplain. The region under study (3500 km2) presents a diversity of landscape units with open lakes, bogs, large meadows, savannahs, alluvial forests and terra firma forest, covered by 21 images acquired by J-ERS between 1993 and 1997. Ground data include in situ observations of vegetation structure and flood extent as well as water level records. Image analysis demonstrates that temporal variations of the radar backscatter can be used to monitor efficiently the flood extent regardless of the landscape units. Also, analysis of the backscatter temporal variation greatly reduces the confusion between smooth surfaces (e.g. open water bodies, bare soils) inherent to L-band backscatter. The mapping method is based on decision rules over two decision variables: 1) the mean backscatter coefficient computed over the whole time series; 2) the total change computed using an “Absolute Change” estimator. The first variable provides classification into rough vegetation types while the second variable yields a direct estimate of the intensity of change that is related to flood dynamics. The classifier is first applied to the whole time series to map the maximum and minimum flood extent by defining 3 flood conditions: never flooded (NF); occasionally flooded (OF); permanently flooded (PF). It also furnishes the broad land cover type: open water/bare soils/low vegetation/forest. The accuracy of the flood extent mapping shows a kappa value of 0.82. Then, the classifier is run iteratively on the OF pixels to monitor flood stages during which the occasionally flooded areas get submerged. The mapping accuracy is assessed on one intermediate flood stage, showing a precision in excess of 90%. The importance of the time sampling for flood mapping is discussed along with the influence of SAR backscatter accuracy and the number of images. Then general guidelines for floodplain mapping are presented. By combining water level reports with maps of different flood stages the flooding pattern can be retrieved along with the vegetation succession processes. It is shown that the spatial distribution of vegetation communities is governed by flood stress and can be modelled as a function of the mean annual exposure to floods. [Copyright &y& Elsevier]

Radiative transfer models have been widely used to interpret the radar backscatter from forested areas. Most of these models are based on an iterative solution of the radiative transfer equation, usually solved up to first or second order, thus taking into account single and double scattering. Although this method leads to results agreeing well with copolarized backscatter measurements, it produces less accurate estimates for horizontal-vertical (HV) polarization. This paper presents a radiative transfer backscatter model that accounts for multiple scattering by using the discrete ordinate and eigenvalue method applied to a layered medium. Using parameters derived from an architectural tree model, calculations at C- and L-band are compared with HV data acquired for a maritime pine forest in the southwest of France during the Spaceborne Imaging Radar-C missions. Good agreement is found at C-band for all values of forest biomass, and reasonable agreement at L-band for high biomass, when the soil backscatter plays a minor role. For low biomass, the L-band modeling is inadequate because of difficulties in estimating the soil backscatter. Comparison with calculations from a first-order radiative transfer model shows that multiple scattering is significant, especially at C-band. [ABSTRACT FROM AUTHOR]

This paper describes a modeling approach to interpret the C-band synthetic aperture radar (SAR) data from wheat canopies as provided by European Remote Sensing (ERS) satellites, RADARSAT, and the forthcoming Environmental Satellite/Advanced Synthetic Aperture Radar (ENVISAT/ASAR) satellite. At a first step, the results of a first-order modeling were compared to ERS data and scatterometer data over the growing season at two different test sites. The prediction by first-order approach was in disagreement with the data from stem extension stage to soft ripening stage. The first-order approach was found to overestimate the attenuation at vertical (V) polarization, resulting in a predicted backscattering coefficient one order of magnitude lower than that observed by the SAR system. To improve the prediction, a multiple-scattering modeling based on numerical solution of multiple-scattering Foldy-Lax equation was used. The multiple-scattering modeling provides better backscatter estimates at vertical-vertical (VV) polarization for both test sites. Then, the model is used to derive the prevailing interactions mechanisms at horizontal-horizontal (HH) and VV polarizations and 23° and 40° of incidence angle. Finally, the retrieval of crop parameters from C-band SAR data is addressed. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between C-band backscatter measurements and wheat biomass and the underlying soil moisture content. It aims to define strategies for retrieval algorithms with a view to using satellite C-band synthetic aperture radar (SAR) data to monitor wheat growth. The study is based on a ground-based scatterometer experiment conducted on a wheat field at the Matera site in Italy during the 2001 growing season. From March to June 2001, eight C-band scatterometer acquisitions at horizontal-horizontal and vertical-vertical polarization, with incidence angles ranging from 23° to 60°, were taken. At the same time, soil moisture, wheat biomass, and canopy structure were collected The paper describes the experiment and investigates the radar sensitivity to biophysical parameters at different polarizations and incidence angles, and at different wheat phenological stages. Based on the experimental results, the retrieval of wheat biomass and soil moisture content using Advanced Synthetic Aperture Radar data is discussed. [ABSTRACT FROM AUTHOR]

This paper aims to establish the joint roughness statistics for rms height s and correlation length i for agricultural bare soil fields and a variety of tillage conditions. To do so, we make use of a unique pan-European database of profile measurements covering five different sites and containing approximately 1.5 km of profile data. A preliminary assessment of the validity of the derived roughness statistics for electromagnetic scattering models is also carried out by comparing σ[sup 0] predictions obtained using the integral equation model with derived roughness statistics and European Remote Sensing 1 and 2 (ERS 1/2) synthetic aperture radar observations. The results are then summarized within the overall context of roughness description and we discuss the implications in terms of forward modeling and inversion. The limitations of s and l parameters as roughness descriptors are also underlined. [ABSTRACT FROM AUTHOR]

The objective of this paper is to quantify the impact of the type of surface-profiling instrument on the roughness measurements in radar remote sensing studies. Particularly, the use of mechanical profilers as compared to more precise laser profilers is investigated. The motivations for this study are twofold. First, simple and inexpensive mechanical profilers will probably still be used extensively for in situ ground measurements in the next few years, e.g., to investigate the use of multipolarization, multi-incidence angle satellite data, i.e., Advanced Synthetic Aperture Radar (ASAR) on-board the European Space Agency Environmental Satellite. Second, a great amount of roughness data have been acquired in the past by means of mechanical profilers and, to date, a quantification of the error budget affecting these measurements is still missing. The paper focuses on modeling and quantifying the measurement errors associated with profiles a few meters long. To determine the errors, we compare soil roughness measurements obtained using laser and mechanical profilers over agricultural surfaces with different roughness characteristics. The analyzed datasets consist of roughness measurements acquired over the Matera site (Italy) and the Marestaing site, near Toulouse (France), in 1998 and 2000, respectively. Analytical expressions for first and second statistical moments of roughness parameters as a function of different sources of measurement errors are derived and compared to experimental values. The results show that mechanical measurements, once appropriately calibrated, are in overall good agreement with laser measurements. Practical indications of the most appropriate profiler length and number of independent measurements to be recorded are also derived in the paper. [ABSTRACT FROM AUTHOR]

Presents a study on the relationships between very high frequency (VHF) data and biomass using data acquired by the Airborne Imaging Radar Coherent All-Radio Band Sensing (CARABAS) over two different pine plantation forests in southern France. Information on the test site and the CARABAS system; Description of the modeling work; Comparison between theoretical and experimental results; Use of VHF synthetic aperture radar for forest biomass mapping.

Presents information on a study which examined the physical background underlying the ERS response of forest and analysis of time series of ERS data. Data analysis and physical principles; Forest mapping algorithm used; Assessment of the methodology; Discussion and conclusion.

Presents information on a study which addressed the issue of soil roughness characterization in the case of agricultural fields having different tillage states. How to improve the portability and mechanical rigidity of the CESBIO-ESA laser profiler system; Test sites and data acquisition; Experimental results; Discussion and conclusion.

Analyzes multifrequency, polarimetric synthetic aperture radar data acquired during the second SIX-C/XSAR mission over the Matera (Italy) test site, in an effort to assess the possibility of extracting relevant information about surface roughness using polarimetry. What the methodology is expected to be of interest for; Description of ground data; Investigation of backscattering coefficients; How the polarization effect is investigated; Results obtained.

Assesses the use of European Remote Sensing Satellites ERS-1 Synthetic Aperture Radar (SAR) data to map rice growing areas and to retrieve rice parameters. Synthesis of experimental results at a tropical site with short cycle rice and a tropical site with long cycle rice; Method for rice fields mapping; Potential use of ERS-1 and RADARSAT data for rice monitoring.

In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering coefficients, σ0 and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as in situ precipitation and air temperature. The high temporal frequency of Sentinel-1 acquisitions (i.e., twelve days, or six, if both Sentinel-1A and B are combined over Europe) and the dual polarization configuration (VV and VH over most land surfaces) made a significant contribution. In particular, the radar backscattering coefficient ratio of VV to VH polarization, σ V V 0 / σ V H 0 , showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (r = 0.77) over stands of deciduous trees. These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than optical data. These observations will be quantitatively analyzed with the use of electromagnetic models in the near future. [ABSTRACT FROM AUTHOR]