Sensibilité des observables radars à la variabilité temporelle et à la configuration géométrique de forêts tempérées et tropicales à partir de mesure de proximité haute-résolution

L'augmentation importante de la population mondiale, et par conséquent de ses besoins, exerce une pression de plus en plus importante sur les surfaces forestières. L'outil le mieux adapté au suivi des forêts, à l'échelle du globe, est la télédétection. C'est dans ce contexte que se situe ce travail de thèse, qui vise à améliorer l'estimation des paramètres biophysiques des arbres à partir de données de télédétection. L'originalité de ce travail a été d'étudier cette estimation des paramètres biophysiques en menant plusieurs études de sensibilité avec une démarche expérimentale sur des données expérimentales et sur des données simulées. Tout d'abord, l'étude s'est portée sur des séries temporelles de mesures de diffusiométrie radar obtenues sur deux sites : l'un constitué d'un cèdre en zone tempérée et l'autre d'une parcelle de forêt tropicale. Puis, cette étude de sensibilité a été poursuivie en imageant, avec une résolution élevée, plusieurs parcelles aux configurations différentes à l'intérieur d'une forêt de pin. Enfin, des données optiques et radars simulées ont été fusionnés afin d'évaluer l'apport de la fusion de données optique et radar dans l'inversion des paramètres biophysiques.The significant increase of the world population, and therefore its needs, pushes increasingly high in forest areas. The best tool for monitoring forest across the globe is remote sensing. It is in this context that this thesis, which aims to improve the retrieval of biophysical parameters of trees from remote sensing data, takes place. The originality of this work was to study the estimation of biophysical parameters across multiple sensitivity studies on experimental data and simulated data. First, the study focused on the time series of radar scatterometry measurements obtained on two sites: one characterized by a cedar in the temperate zone and the other by a forest plot of rainforest. Then, the sensitivity analysis was continued by imaging with high resolution, several forest plots with different configurations within a pine forest. Finally, simulated radar and optical data were combined to evaluate the contribution of optical and radar data fusion in the inversion of biophysical parameters.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

Digital Elevation Models: Terminology and Definitions

Digital elevation models (DEMs) provide fundamental depictions of the three-dimensional shape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record the interface between the atmosphere and the lithosphere using a discrete two-dimensional grid, with complexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere. The treatment of DEM surfaces, affected by these intervening spheres, depends on their intended use, and the characteristics of the sensors that were used to create them. DEM is a general term, and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) record the treatment of the intermediate surfaces. Several global DEMs generated with optical (visible and near-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars and products of satellite altimetry, share the common characteristic of a georectified, gridded storage structure. Nevertheless, not all DEMs share the same vertical datum, not all use the same convention for the area on the ground represented by each pixel in the DEM, and some of them have variable data spacings depending on the latitude. This paper highlights the importance of knowing, understanding and reflecting on the sensor and DEM characteristics and consolidates terminology and definitions of key concepts to facilitate a common understanding among the growing community of DEM users, who do not necessarily share the same background

Radar data sensitivity to the temporal variability and the geometrical configuration of temperate and tropical forests from in-situ high resolution measurements

L'augmentation importante de la population mondiale, et par conséquent de ses besoins, exerce une pression de plus en plus importante sur les surfaces forestières. L'outil le mieux adapté au suivi des forêts, à l'échelle du globe, est la télédétection. C'est dans ce contexte que se situe ce travail de thèse, qui vise à améliorer l'estimation des paramètres biophysiques des arbres à partir de données de télédétection. L'originalité de ce travail a été d'étudier cette estimation des paramètres biophysiques en menant plusieurs études de sensibilité avec une démarche expérimentale sur des données expérimentales et sur des données simulées. Tout d'abord, l'étude s'est portée sur des séries temporelles de mesures de diffusiométrie radar obtenues sur deux sites : l'un constitué d'un cèdre en zone tempérée et l'autre d'une parcelle de forêt tropicale. Puis, cette étude de sensibilité a été poursuivie en imageant, avec une résolution élevée, plusieurs parcelles aux configurations différentes à l'intérieur d'une forêt de pin. Enfin, des données optiques et radars simulées ont été fusionnés afin d'évaluer l'apport de la fusion de données optique et radar dans l'inversion des paramètres biophysiques.The significant increase of the world population, and therefore its needs, pushes increasingly high in forest areas. The best tool for monitoring forest across the globe is remote sensing. It is in this context that this thesis, which aims to improve the retrieval of biophysical parameters of trees from remote sensing data, takes place. The originality of this work was to study the estimation of biophysical parameters across multiple sensitivity studies on experimental data and simulated data. First, the study focused on the time series of radar scatterometry measurements obtained on two sites: one characterized by a cedar in the temperate zone and the other by a forest plot of rainforest. Then, the sensitivity analysis was continued by imaging with high resolution, several forest plots with different configurations within a pine forest. Finally, simulated radar and optical data were combined to evaluate the contribution of optical and radar data fusion in the inversion of biophysical parameters

Sensibilité des observables radars à la variabilité temporelle et à la configuration géométrique de forêts tempérées et tropicales à partir de mesure de proximité haute-résolution

The significant increase of the world population, and therefore its needs, pushes increasingly high in forest areas. The best tool for monitoring forest across the globe is remote sensing. It is in this context that this thesis, which aims to improve the retrieval of biophysical parameters of trees from remote sensing data, takes place. The originality of this work was to study the estimation of biophysical parameters across multiple sensitivity studies on experimental data and simulated data. First, the study focused on the time series of radar scatterometry measurements obtained on two sites: one characterized by a cedar in the temperate zone and the other by a forest plot of rainforest. Then, the sensitivity analysis was continued by imaging with high resolution, several forest plots with different configurations within a pine forest. Finally, simulated radar and optical data were combined to evaluate the contribution of optical and radar data fusion in the inversion of biophysical parameters.L'augmentation importante de la population mondiale, et par conséquent de ses besoins, exerce une pression de plus en plus importante sur les surfaces forestières. L'outil le mieux adapté au suivi des forêts, à l'échelle du globe, est la télédétection. C'est dans ce contexte que se situe ce travail de thèse, qui vise à améliorer l'estimation des paramètres biophysiques des arbres à partir de données de télédétection. L'originalité de ce travail a été d'étudier cette estimation des paramètres biophysiques en menant plusieurs études de sensibilité avec une démarche expérimentale sur des données expérimentales et sur des données simulées. Tout d'abord, l'étude s'est portée sur des séries temporelles de mesures de diffusiométrie radar obtenues sur deux sites : l'un constitué d'un cèdre en zone tempérée et l'autre d'une parcelle de forêt tropicale. Puis, cette étude de sensibilité a été poursuivie en imageant, avec une résolution élevée, plusieurs parcelles aux configurations différentes à l'intérieur d'une forêt de pin. Enfin, des données optiques et radars simulées ont été fusionnés afin d'évaluer l'apport de la fusion de données optique et radar dans l'inversion des paramètres biophysiques

Measure of Temporal Variation of P-Band Radar Cross Section and Temporal Coherence of a Temperate Tree.

International audienceThis paper deals with a ground experiment based on a P-band scatterometer that measured the evolution of the radar cross section (RCS) and coherence of a temperate tree in HV polarization, during four periods spread over nine months, over a cedar tree. Watering of the tree has limited influence in time on the RCS, i.e., limited to around 30 min, but impacts the coherence over a longer period of time. Analysis of the series shows that according to the season considered, clear daily cycles from 1 to 2 dB may appear on the coherence only (autumn) or on both coherence and RCS (spring), whereas in winter, they are absent on both results. It was analyzed in the literature that the variations in RCS are strongly correlated to the variations in the dielectric constant in trunks and branches. In addition, it was shown that the HV RCS presents seasonal trends with a yearly cycle of roughly 3 dB following similar trends reported for trunk moisture content time series

TOPOGRAPHY EFFECTS ON FOREST RADAR SCATTERING, CONSEQUENCES ON BIOMASS RETRIEVAL

4 pagesInternational audienceGround topography under vegetated area is liable to bring significant changes on radar backscattering and thereby on the associated standard retrieval algorithms dedicated to forest biomass. Within the framework of the ESA BIOMASS mission, this paper evinces the evolution of P-band polarimetric intensities with a tilted underlying ground. For that purpose, electromagnetic simulations have been achieved using our model MIPERS -- Multisatic Interferometric Polarimetric Electromagnetic model for Remote Sensing -- which theoretical specificities accounting for the topographic effects are herein described. Its originality lies mainly in the 3D characterization of the ground and the volume, as well as the coupling effects between both. This description is followed by a sensitivity analysis in order to further-on quantify the possible consequences on biomass retrieval, conducted with the two standard approaches, namely the P-HV intensity technique and the Pol-InSAR one assuming the RVoG model. This investigation have been also undertaken for a better understanding of experimental data, particularly with the BioSAR and the TropiSAR airborne campaigns over boreal and tropical forests

Best BiCubic Method to Compute the Planimetric Misregistration between Images with Sub-Pixel Accuracy: Application to Digital Elevation Models

In recent decades, an important number of regional and global digital elevation models (DEMs) have been released publicly. As a consequence, researchers need to choose between several of these models to perform their studies and to use these DEMs as third-party data to compute derived products (e.g., for orthorectification). However, the comparison of DEMs is not trivial. For most quantitative comparisons, DEMs need to be expressed in the same coordinate reference system (CRS) and sampled over the same grid (i.e., be at the same ground sampling distance with the same pixel-is-area or pixel-is-point convention) with heights relative to the same vertical reference system (VRS). Thankfully, many open tools allow us to perform these transformations precisely and easily. Despite these rigorous transformations, local or global planimetric displacements may still be observed from one DEM to another. These displacements or disparities may lead to significant biases in comparisons of DEM elevations or derived products such as slope, aspect, or curvature. Therefore, before any comparison, the control of DEM planimetric accuracy is certainly a very important task to perform. This paper presents the disparity analysis method enhanced to achieve a sub-pixel accuracy by interpolating the linear regression coefficients computed within an exploration window. This new method is significantly faster than oversampling the input data because it uses the correlation coefficients that have already been computed in the disparity analysis. To demonstrate the robustness of this algorithm, artificial displacements have been introduced through bicubic interpolation in an 11 × 11 grid with a 0.1-pixel step in both directionsThis validation method has been applied in four approximately 10 km × 10 km DEMIX tiles showing different roughness (height distribution). Globally, this new sub-pixel accuracy method is robust. Artificial displacements have been retrieved with typical errors (eb) ranging from 12 to 20% of the pixel size (with the worst case in Croatia). These errors in displacement retrievals are not equally distributed in the 11 × 11 grid, and the overall error Eb depends on the roughness encountered in the different tiles. The second aim of this paper is to assess the impact of the bicubic parameter (slope of the weight function at a distance d = 1 of the interpolated point) on the accuracy of the displacement retrieval. By considering Eb as a quality indicator, tests have been performed in the four DEMIX tiles, making the bicubic parameter vary between −1.5 and 0.0 by a step of 0.1. For each DEMIX tile, the best bicubic (BBC) parameter b* is interpolated from the four Eb minimal values. This BBC parameter b* is low for flat areas (around −0.95) and higher in mountainous areas (around −0.75). The roughness indicator is the standard deviation of the slope norms computed from all the pixels of a tile. A logarithmic regression analysis performed between the roughness indicator and the BBC parameter b* computed in 67 DEMIX tiles shows a high correlation (r = 0.717). The logarithmic regression formula b~σslope estimating the BBC parameter from the roughness indicator is generic and may be applied to estimate the displacements between two different DEMs. This formula may also be used to set up a future Adaptative Best BiCubic (ABBC) that will estimate the local roughness in a sliding window to compute a local BBC b~

TropiSCAT : a multi-frequency polinsar data campaign of acquisition for vegetation characterization

International audienc

Demonstrating that speciation of organic fraction does matter for source apportionment : use of specific primary and secondary organic markers

Organic aerosol (OA) is a major part of atmospheric fine particulate matter (PM), accounting for approximately 20-60% w/w of PM in the continental mid-altitudes. However, ambient OA remains poorly understood due to mixed source origins and processes (anthropogenic and biogenic, primary and secondary). The objective of this study was to refine source apportionment of PM10 OA by Positive Matrix Factorization (PMF) using specific primary and secondary organic molecular markers. PM10 samples were collected over a one year period (2013) at an urban station in Grenoble (France) every third day (24 h-basis sampling) on quartz filters, and an extended chemical characterization was performed (~216 species quantified) including specific primary organic markers i.e. levoglucosan, polyols (arabitol, mannitol), 1-nitropyrene (diesel emission), PAHs, alkanes, hopanes, etc. and secondary markers i.e. nitro- and oxy-PAHs, hydroxyglutaric acid (α-pinene secondary organic aerosol SOA), α-methyl glyceric acid (isoprene SOA), DHOPA (toluene SOA), etc. together with other PM chemical species such as OC/EC, Humic Like Substances (HuLiS), ions/cations (Na+, Mg2+, NH4+, Cl-, SO42-, NO3-), metals (Ba, Cu, Ti, Zn, Sb,...). Results showed that a better source apportionment of PM10 OA fraction was achieved using specific organic markers with additional sources resolved such as biogenic SOA, anthropogenic SOA, primary biogenic (fungi) and plant debris by comparison to more traditional PMF. More than 50% of OC seemed secondary in nature, and a high contribution of anthropogenic SOA was noticed in winter during a specific PM pollution event. Primary and secondary sources of HuLiS were also investigated in this study. Discussion will further underline the details of the chemical and temporal/seasonal profiles of each factor, and their relative contributions

Understanding of the chemical processes involving nitro- and oxy-PAHs in ambient air and evaluation of SOA PAH contribution on PM via annual and intensive field campaigns

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous compounds emitted by all combustion sources. They are of major health concern because of their carcinogenic, mutagenic and teratogenic properties and are therefore, regulated pollutants in ambient air. In the atmosphere, PAH oxidation through homogeneous and heterogeneous reactions may lead to the formation of oxy- and nitro- PAHs (Keyte et al., 2013). These latter species are also emitted concomitantly with PAHs during incomplete combustion processes. Oxy- and nitro-PAHs are potentially more toxic than their parent PAHs. The identification of the origins of oxy- and nitro-PAHs is challenging, due to the coexistence of their primary and/or secondary sources. These species are also of prime interest because they are, typically part of the secondary organic aerosol (SOA) generated from gaseous PAH oxidation, which is significant in urban environments (Chan et al., 2009). The objective of this work is to better understand the chemical processes involved in the formation of nitro- and oxy-PAHs based on ambient air field observations, to better understand the sources of these toxic compounds and to identify specific molecules that could further be used as molecular markers of PAH oxidation and SOA formation. Field measurements were performed over 1 year with samplings, every third day, of the gaseous and particulate (PM10) phases in Grenoble (2013) and at the SIRTA station (25 km SW from Paris city center) (2015). Intensive observations at SIRTA have been also performed with PM10 samples collected every 4-hour during a period of severe PM pollution event (PM>50 μg m-3 for several days) in March 2015, concomitantly with online measurements (e.g. ACSM, 7-Aethalometer). The study of the occurrence of nitro-, -oxy and parent PAHs in the atmosphere, the seasonal and diurnal variations of their concentrations and substance patterns and the assessment of the cancer risk induced by these compounds have been performed. Based on these observations combined with literature knowledge and an extended aerosol chemical characterization, specific molecules of PAH oxidation have been identified (Figure 1). These substances were then used in sourcereceptor models such as positive matrix factorization (PMF) to apportion the SOA contribution from PAH oxidation on PM10 mass