Isabelle Champion

Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer

Abstract Since microwave remote sensing techniques are insensitive to cloud cover, they can overcome this strong limitation of optical remote sensing. As in the optical domain, their use for monitoring vegetation canopies requires the development of suitable inversion algorithms. These would allow the estimation of variables such as LAI from radar data. This article investigates the possible use of a semiempirical water-cloud model in an inversion scheme. Using radar data obtained with a ground-based dual-frequency (C and X bands, 5.7 and 3.3 cm wavelength, respectively) scatterometer on experimental winter wheat fields, it is first verified that a semiempirical water-cloud model can adequately simulate the backscattering coefficients obtained over the growing season, as a function of LAI and surface soil moisture. Then it is shown that the model can be numerically inverted. This yields simultaneous estimation of LAI and surface soil moisture, the standard deviations of the residuals being respectively 0.64 m2 m−2 and 0.065 cm3 cm−3. Finally, the influence of radar measurement errors on the inversion scheme is quantified by means of a simulation study. This shows that a 1 dB accuracy of the radar is required for a 1 m2 m−2 precision of the estimated LAI.

Forest Height Inversion Using High-Resolution P-Band Pol-InSAR Data

In this paper, a high-resolution P-band Pol-InSAR data set acquired by the airborne RAMSES system over pine forest stands of different height is investigated. A significant penetration depth in all the polarimetric channels and a wide range of polarimetric phase center heights are observed, attesting of an interaction of the radar waves with different forest structural elements. The main objective of this paper concerns forest height inversion at P-band. First, forest-modeling assumptions are evaluated using a priori information, such as ground-level and forest height measurements. The full extend of the forest height is shown to be responsible of the volume decorrelation, and a significant orientation effect is clearly identified over the highest stands. As a consequence, the Oriented Volume over Ground model (OVoG) is determined to be the most appropriated model for the forest height inversion. At P-band, the ground contribution is present in all the polarimetric channels due to the important penetration at this frequency. To overcome this difficulty, a time-frequency optimization method based on sublook decomposition is developed to separate the pure ground and canopy contributions, allowing forest height estimation with OVoG with an rms error on the order of 2 m. In the last section of this paper, a sensitivity analysis of the inversion with respect to two important system parameters, the signal-to-noise ratio and the resolution, is presented, leading to a discussion on the inversion robustness in spaceborne conditions, where these system parameters are the most deteriorated as compared to airborne configurations.

Radar image texture as a function of forest stand age

Data on forest variables are required for environmental and forest management applications. Numerous authors have shown significant correlations between mean radar response intensity and forest variables (age, height or biomass) but few studies have explored the spatial characteristics of the radar response for varying forest states. In this Letter, variation in the most commonly used texture features is shown as a function of an indicator of forest growth (age) for a controlled homogeneous test site (monospecific, even‐aged forest, with identical sylvicultural practices and a sampling that covers all forest stages from sowing to harvest). Significant linear relationships between some texture features and stand age are observed. Moreover, the quality of some fits indicates that texture could be used instead of the usual intensity–age relationships that saturate for mature stands.

Sensitivity of the radar signal to soil moisture: variation with incidence angle, frequency, and polarization

This study focuses on the variations of the radar sensitivity to soil moisture (d/spl sigma//sup o//dm/sub /spl upsi//) with the radar configuration parameters (frequency, polarization, and angle). An analysis of variance shows that only the polarization significantly influences d/spl sigma//sup o//dm/sub /spl upsi//, which is larger at cross-polarization than at like-polarized configurations.

Retrieval of Forest Stand Age From SAR Image Texture for Varying Distance and Orientation Values of the Gray Level Co-Occurrence Matrix

Data on forest variables (e.g., biomass, trunk height, density) are necessary for environmental and forest management applications. It has been shown that texture can be used instead of the usual σo/age relationships at P-band to retrieve plantation forest parameters, but the analysis of σo spatial characteristics has not been fully explored. The aim of this letter is to investigate the relationships between stand age (which is correlated to forest variables) and texture descriptors calculated from statistics generated by the gray-level co-occurrence matrix for varying distance d, and orientation α, values used to calculate the matrix. Synthetic aperture radar images are P-band airborne data acquired by the ONERA RAMSES instrument over a controlled homogeneous test site located in the Landes region, France. It is found that texture descriptors contrast, inverse difference moment, homogeneity, and correlation are strongly influenced by the parameters (d, α) related to forest stand structure (forest rows, stand density) and image resolution. In contrast, energy and entropy are observed to be highly correlated to stand age and displayed a stable performance whatever the distance and orientation parameters (d, α), thus rendering them a good contender as an alternative to the usual σo based relationships applied to this type of forest.

Polar and PolInSAR analysis of pine forest at L and P band on high resolution data

A well known Pine forest has been investigated at L and P band on high resolution PolInSAR datasets. A previous polarimetric analysis has evaluated L and P band potential for the biomass estimation. It shows a good correlation with the polarimetric parameters at P band. The PolInSAR investigation at this frequency allows an identification of elementary scatterers and of an orientation effect linked to the forest vertical structure.

Contribution of textural information from TerraSAR-X image for forest mapping

This study evaluates the potential of High Resolution Spotlight TerraSAR-X image for forest type discrimination. Emphasis is put on textural analysis accessible with high resolution radar data. Textural attributes are extracted from GLCM matrices, wavelet, and Fourier Transform (i.e. FOTO method). Their contribution for classification is assessed by their performance through the SVM algorithm.

Statistical hypothesis test for maritime pine forest SAR images classification based on the geodesic distance

This paper introduces a new statistical hypothesis test for image classification based on the geodesic distance. We present how it can be used for the classification of texture image. The proposed method is then employed for the classification of Polarimetric Synthetic Aperture Radar images of maritime pine forests on both simulated data with the PolSARproSim software and real data acquired during the ONERA RAMSES campaign in 2004.

Multi-thematic exploitation of TerraSAR-X images in the context of the kalideos reference dataseis

This paper presents the use of TerraSAR-X images m the context of the Kalideos programme, which aims at providing the user community with time series of multi-spectral (optical and radar) and multi-resolution remote sensing imagery. 120 TerraSAR-X acquisitions are scheduled for three distinct thematics: volcano monitoring (Reunion island site), sugarcane crop monitoring (Reunion island site) and forest monitoring (Arcachon/Landes forest site). We describe here the advancement of these studies, focusing on sugarcane crop monitoring which is the most advanced one. These studies will serve as typical examples of multi-thematic use of TerraSAR-X imagery and demonstrate the relevance of TerraSAR-X imagery for the development of scientific reference datasets.

Review of Polarimetric Indicators for Forest Characterisation over Several Sites

Global warning is now known to be the major environmental issue mankind will have to face in the next decade. Monitoring of vegetation and biomass is clearly an essential piece of information required at all levels ranging from the scientific studies to understand and forecast, to the political world responsible for drafting remediation policies and evaluating their impact. Microwave remote sensing with the low-frequency SAR technique can provide a useful characterization of forest (spatial coverage, species, density, height...) at a global scale, relying on the all-weather imaging capabilities of SAR linked with the significant penetration of the low-frequency EM wave in the canopy. In this paper, we will review the potential polarimetric indicators and evaluate their performance over several types of forest. We will particularly focus on the impact of the topography and the influence of the weather conditions.