Radar Remote Sensing For Vegetation With Special Reference To Nipah Delineation On Sir-A Image

ABSTRACT Active microwave is a promising tool for monitoring vegetation and agricultural crops: the biomass, the stage of growth and deviations from regular plant development due to stress and ivestation may be inferred from radar data. In order to do so, two main steps must be considered: the changes of the measured radar signals must be correlated to the backscattering coefficients of the targets, the latter of which must be defined towards the biomass and structure of the vegetation. The definition of such relationship is,not an easy task due to the large number of physical parameters which characterize the target (type of crop and soil, humidity, structure, slope, etc.) and the sensor (wavelength, polarization, shooting angle). Moreover, these parameters are interrelated. Two basic models and some experiments, especially with reference to a successful but unexplained attempt of Nipah delineation with SIR-A imagery is presented after three main levels of vegetation observation are defined and the main physical parameters for the backscattering process are reviewed Although the few experiments conducted to date show that imaging radar has the potential to provide useful information with regard to vegetation no concrete information exists with regard to optimum angle of incidence, frequency or polarization configuration Kata Kunci: radar remote - vegetatio

Geography with the environmental satellites

Coarse spatial resolution, high temporal frequency data from the earth polar orbiting (NOAA. HACMM, Nimbus, etc.) satellites and from the geostationary (GOES. Meteosat, and GMS) satellites are presented to demonstrate their utility for monitoring terrestrial and atmospheric processes. The main characteristics of these ,satellites and of the instruments on board are reviewed. In order to be useful for environmental assessments. the remotely sensed data must be processed (atmospheric and geometric corrections, etc.). The NOAA Center provides a wide range of already processed data. such as meteorological. oceanic, hydrologic and vegetation productso rough description of these preprocessed data is given in this article. Finally, some examples of applicotions in Southeast Asia and especially in Indonesia, are described, i.e.: agroecosystem, drought and oceanic monitoring. The paper concludes that coarse resolution, high temporal frequency ,satellite data are very valuable for environmental studies. the emphasis being laid on the improve. ment of the crop and drought assessment programmes

DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces

Modeling the radiative behavior and the energy budget of land surfaces is relevant for many scientific domains such as the study of vegetation functioning with remotely acquired information. DART model (Discrete Anisotropic Radiative Transfer) is developed since 1992. It is one of the most complete 3D models in this domain. It simulates radiative transfer (R.T.) in the optical domain: 3D radiative budget and remote sensing images (i.e., radiance, reflectance, brightness temperature) of vegetation and urban Earth surfaces, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (flux tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. Here, its potential is illustrated with the case of urban and tropical forest canopies. Moreover, three recent improvements in terms of functionality and operability are presented: account of Earth/Atmosphere curvature for oblique remote sensing measurements, importation of 3D objects simulated as the juxtaposition of triangles with the possibility to transform them into 3D turbid objects, and R.T. simulation in landscapes that have a continuous topography and landscapes that are non repetitive. Finally, preliminary results concerning two application domains are presented. 1) 2D distribution of the reflectance, brightness temperature and radiance measured by a geostationary satellite over a whole continent. 2) 3D radiative budget of natural and urban surfaces with a DART energy budget (EB) component that is being developed. This new model, called DARTEB, is intended to simulate the energy budget of land surfaces

A model-based performance test for forest classifiers on remote-sensing imagery

Ambiguity between forest types on remote-sensing imagery is a major cause of errors found in accuracy assessments of forest inventorymaps. This paper presents a methodology, based on forest plot inventory, ground measurements and simulated imagery, for systematically quantifying these ambiguities in the sense of the minimum distance (MD), maximum likelihood (ML), and frequency-based (FB) classifiers. The method is tested with multi-spectral IKONOS images acquired on areas containing six major communities (oak, pine, fir, primary and secondary high tropical forests, and avocado plantation) of the National Forest Inventory (NFI) map in Mexico. A structural record of the canopy and optical measurements (leaf area index and soil reflectance) were performed on one plot of each class. Intra-class signal variation was modelled using the Discrete Anisotropic Radiative Transfer (DART) simulator of remote-sensing images. Atmospheric conditions were inferred from ground measurements on reference surfaces and leaf optical properties of each forest type were derived from the IKONOS forest signal. Next, all forest types were simulated, using a common environmental configuration, in order to quantify similarity among all forest types, according to MD, ML and FB classifiers. Classes were considered ambiguous when their dissimilarity was smaller than intra-class signal variation. DART proved useful in approximating the pixel value distribution and the ambiguity pattern measured on real forest imagery. In the case study, the oak forest and the secondary tropical forest were both distinguishable from all other classes using an MD classifier in a 25 m window size, whereas pine and primary tropical forests were ambiguous with three other classes using MD. By contrast, only two pairs of classes were found ambiguous for the ML classifier and only one for the FB classifier in that same window size. The avocado plantation was confounded with the primary tropical forest for all classifiers, presumably because the reflectance of both types of forest is governed by a deep canopy and a similar shadow area. We confronted the results of this study with the confusion matrix from the accuracy assessment of the NFI map. An asset of this model-basedmethod is its applicability to a variety of sensor types, eco-zones and class definitions

A Procedure For Deriving Geo-Referenced Location For Digital Images

ABSTRACT Two systems of bilinear interpolation were studied in deriving a procedure for transforming geo-referenced grid locations to locations on maps defined by digital image column and line coordinates. Map data were from 1 : 50.000 Universal Transverse Mercator topographic charts. and digital data were from SPOT satellite dataprocessed to Level lb (CHES. 1979). corrected for Earth rotation and curvature and off-nadir viewing but without local control. Two independent data sets gave similar results: models with two independent variables gave prediccted errors of less than the dimensions of one pixel of the digital data. Models with one independent variable were inadequate for satisfactory transformations. Procedures for collecting and analyzing control data are presented. and trial models are shown and discussed. Kata Kunci.: deriving geo referenced - digital image

Diversity of 3D APAR and LAI dynamics in broadleaf and coniferous forests: Implications for the interpretation of remote sensing-based products

Forests substantially mediate the water and carbon dioxide exchanges between terrestrial ecosystems and the atmosphere. The rate of this exchange, including evapotranspiration (ET) and gross primary production (GPP), depends mainly on the underlying vegetation type, health state, and the composition of abiotic environmental drivers. However, the complex 3D structure of forest canopies and the inherent top-view perspective of optical and thermal remote sensing complicate remote sensing-based retrievals of biotic and abiotic factors that eventually determine ET and GPP. This study investigates the sensitivity of remote sensing approaches to 3D variation of abiotic and biotic environmental drivers. We use 3D virtual scenes of two structurally different Swiss forests and the radiative transfer model DART to simulate the 3D distribution of solar irradiance and reflected radiance in the forest canopy. These simulations, in combination with LiDAR data, are used to derive the absorbed photosynthetic active radiation (APAR) and the leaf area index (LAI) in 3D space. The 3D variation of both parameters was quantified and analyzed. We then simulated images of the top-of-canopy bi-directional reflectance factor (BRF) and compared them with the hemispheric-conical reflectance factor (HCRF) data derived from HyPlant airborne imaging spectrometer measurements. The simulated BRF data was used to derive APAR and LAI, and the results were compared to their respective 3D representations. We unravel considerable spatial differences between both representations. We discuss possible reasons for the disagreement, including a potential insensitivity of the inherent top-of-canopy view for the real 3D product dynamics and limitations of the processing of remote sensing data, especially the approximation of effective surface irradiance. Our results can help understanding sources of uncertainties in remote sensing based gas exchange products and defining mitigation strategies

Simulation-Based Evaluation of the Estimation Methods of Far-Red Solar-Induced Chlorophyll Fluorescence Escape Probability in Discontinuous Forest Canopies

Peer reviewe

Conception réalisation et mise en oeuvre d'un scintillomètre (influence de la vapeur d'eau dans la bande 940nm)

L'atmosphère et la surface terrestre interagissent en permanence par le biais des échanges d'énergie et de matière. Ces flux jouent un rôle important dans l'étude de l'hydrologie des surfaces ou de l'écologie terrestre, ou bien encore l'étude des phénomènes météorologiques et climatiques. En effet, ils représentent les conditions aux limites des différents compartiments du système Terre et la quantification de ces échanges à différentes échelles spatiales est indispensable pour les modèles de prévision. Les mesures de flux d'énergie sont très répandues pour des mesures très localisées, in situ et au sol. Cependant, peu d'instruments de mesures permettent d'obtenir des flux intégrés sur des distances de l'ordre de la centaine de mètres à quelques kilomètres, c'est-à-dire des distances correspondant à la représentativité des pixels des images satellitaires. On compte parmi eux les scintillomètres, instrument de mesure optique, permettant de calculer les flux intégrés de chaleur sensible à partir des mesures de paramètres caractérisant l'intensité turbulente de l'atmosphère tels que le paramètre de structure de l'indice de réfraction de l'air Cn . La présence de vapeur d'eau dans l'atmosphère peut cependant perturber le signal de ces instruments. L'objectif de ce travail est le développement et la mise en oeuvre d'un scintillomètre optique permettant de mettre en évidence la contribution de l'absorption par la vapeur d'eau sur les scintillations. Les études menées à partir du développement instrumental ne s'orienteront qu'autour de la bande d'absorption à 940nm, longueur d'onde d'émission de certains scintillomètres LAS (Large Aperture Scintillometer). Au début de ma thèse, un prototype de scintillomètre, type LAS, a été conçu de façon à maitriser complètement la technologie : partie optique électronique et le traitement du signal reçu. Celui-ci a ensuite été installé au-dessus d'un site de cultures dans les environs de Toulouse, au cours des années 2007 et 2008. Les résultats obtenus avec ce prototype ont permis d'optimiser le choix de la méthode de calcul H à partir du Cn , en fonction du rapport de Bowen (rapport du flux de chaleur sensible sur le flux de chaleur latente). Les variations de l'intensité lumineuse de l'onde, menant au Cn , sont principalement dues à des effets de réfraction et de dispersion, maissont aussi sensibles à l'absorption de la vapeur d'eau. Afin de quantifier l'influence de 'absorption sur le signal Cn , j'ai utilisé 2 approches : une première approche par filtrage numérique ( Gabor Transform'), et une seconde, par méthode chromatique. Cette dernière a nécessité de modifier considérablement le système optique du prototype LAS. Les résultats obtenus expérimentalement montrent que la contribution de l'absorption à la mesure du Cn est en moyenne assez faible, mais qu'elle peut prendre de forte valeur, principalement lors de faibles flux H. La quantification de l'absorption par méthode hromatique est pour l'instant limité au développement technique de l'instrument.Atmosphere, soil and vegetation are in interactions by the bias of energetic or matter exchanges. This latters have an important impact on hydrology, ecology, meteorology. Actually, they represent the boundary conditions of the Earth-Atmosphere system. Then, the quantification of these exchanges or fluxes is necessary to understand large scales phenomena and to improve forecasting models. Numerous devices are able to quantify these fluxes at local scales, but few are available to measure them over kilometres, which mean at the resolution of remote sensing datas. Amongst them, we can notice the scintillometers that are able to calculate sensible heat fluxes over distances from hundred meters to few kilometres. Actually, these devices are sensitive to variations of the refractive index of air, mainly due to turbulent eddies, defined by the structure parameter of refractive index : Cn . However, this measurement can be altered by the presence of water vapour in the air. Thus, the aim of this work is to design and make a scintillometer which is able to quantify the water vapour contribution on the Cn measurement. In this thesis, we will focus on this contribution in the 940nm band which is the wavelength of various scintillometers LAS (Large Aperture Scintillometers). At the beginning of my PhD thesis, un scintillometer prototype has been realised in order to master the technology : optics, electronics, signal processing This latter has been set up over crops at a few kilometres from Toulouse, between 2007 and 2008. Thanks to the results of this scintillometer, we optimize the choice on the Cn to H algorithm, according to the Bowen ratio ß (ratio of sensible to latent heat flux). Variations of the light beam, leading to the Cn , are mainly due to refraction and dispersion effect. However, absorption can be important. In order to quantify the contribution of absorption on the Cn , 2 methods are suggested : one based on signal processing aspect (Gabor filtering), and the second one on two wavelengths propagation. To realize this latter the optics and electronics of the device have been really modified. Results show that absorption contribution is small, but can be important for low H values. Finally, the quantification of absorption by two wavelengths approach is nowadays bounded to instrumental development.TOULOUSE-INP (315552154) / SudocSudocFranceF

Biomass prediction in tropical forests : the canopy grain approach

18 pagesThe challenging task of biomass prediction in dense and heterogeneous tropical forest requires a multi-parameter and multi-scale characterization of forest canopies. Completely different forest structures may indeed present similar above ground biomass (AGB) values. This is probably one of the reasons explaining why tropical AGB still resists accurate mapping through remote sensing techniques. There is a clear need to combine optical and radar remote sensing to benefit from their complementary responses to forest characteristics. Radar and Lidar signals are rightly considered to provide adequate measurements of forest structure because of their capability of penetrating and interacting with all the vegetation strata. However, signal saturation at the lowest radar frequencies is observed at the midlevel of biomass range in tropical forests (Mougin et al. 1999; Imhoff, 1995). Polarimetric Interferometric (PolInsar) data could improve the inversion algorithm by injecting forest interferometric height into the inversion of P-band HV polarization signal. Within this framework, the TROPISAR mission, supported by the Centre National d'Etudes Spatiales (CNES) for the preparation of the European Space Agency (ESA) BIOMASS program is illustrative of both the importance of interdisciplinary research associating forest ecologists and physicists and the importance of combined measurements of forest properties. Lidar data is a useful technique to characterize the vertical profile of the vegetation cover (e.g. Zhao et al. 2009) which in combination with radar (Englhart et al. 2011) or optical (e.g. Baccini et al. 2008; Asner et al. 2011) and field plot data may allow vegetation carbon stocks to be mapped over large areas of tropical forest at different resolution scales ranging from 1 hectare to 1 km². However, small-footprint Lidar data are not yet accessible over sufficient extents and with sufficient revisiting time because its operational use for tropical studies remains expensive. At the opposite, very-high (VHR) resolution imagery, i.e. approximately 1-m resolution, provided by recent satellite like Geoeye, Ikonos, Orbview or Quickbird as well as the forthcoming Pleiades becomes widely available at affordable costs, or even for free in certain regions of the world through Google Earth®. Compared to coarser resolution imagery with pixel size greater than 4 meters, VHR imagery greatly improves thematic information on forest canopies. Indeed, the contrast between sunlit and shadowed trees crowns as visible on such images (Fig. 1) is potentially informative on the structure of the forest canopy while new promising methods now exist for analyzing these fine scale satellite observations (e.g. Bruniquel-Pinel & Gastellu-Etchegorry, 1998; Malhi & Roman-Cuesta, 2008; Rich et al. 2010). Besides, we believe that there is also a great potential in similarly using historical series of digitized aerial photographs that proved to be useful in the past for mapping large extents of unexplored forest (Le Touzey, 1968; Richards, 1996) for quantifying AGB changes through time. This book chapter presents the advancement of a research program undertaken by our team for estimating high biomass mangrove and terra firme forests of Amazonia using canopy grain from VHR images (Couteron et al. 2005; Proisy et al. 2007; Barbier et al., 2010; 2011). We present in a first section, the canopy grain notion and the fundamentals of the Fourier-based Textural Ordination (FOTO) method we developed. We then introduce a dual experimental-theoretical approach implemented to understand how canopy structure modifies the reflectance signal and produces a given texture. We discuss, for example, the influence of varying sun-view acquisition conditions on canopy grain characteristics. A second section assesses the potential and limits of the canopy grain approach to predict forest stand structure and more specifically above ground biomass. Perspectives for a better understanding of canopy grain-AGB relationships conclude this work