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

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

Peer reviewe

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

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

Tree crown detection in high resolution optical and LiDAR images of tropical forest

International audienceTropical forests are complex ecosystems where the potential of remote sensing has not yet been fully realized. The increasing availability of satellite metric imagery along with canopy altimetry from airborne LiDAR open new prospects to detect individual trees. For this objective, we optimized, calibrated and applied a model based on marked point processes to detect trees in high biomass mangroves of French Guiana by considering a set of 1m pixel images including 1) panchromatic images from the IKONOS sensor 2) LiDAR-derived canopy 2D altimetry and 3) reflectance panchromatic images simulated by the DART-model. The relevance of detection is then discussed considering: (i) the agreement in space of detected crown centers locations with known true locations for the DART images and also the detection agreement for each pair of IKONOS and LiDAR images, and (ii) the comparison between the frequency distributions of the diameters of the detected crowns and of the tree trunks measured in the field. Both distributions are expected to be related due to the allometry relationships between trunk and crown

Simulating solar-induced chlorophyll fluorescence in a boreal forest stand reconstructed from terrestrial laser scanning measurements

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a suitable remote sensing proxy of photosynthesis at multiple scales. However, the relationship between fluorescence and photosynthesis observed at the leaf level cannot be directly applied to the interpretation of retrieved SIF due to the impact of canopy structure. We carried out a SIF modelling study for a heterogeneous forest canopy considering the effect of canopy structure in the Discrete Anisotropic Radiative Transfer (DART) model. A 3D forest simulation scene consisting of realistic trees and understory, including multi-scale clumping at branch and canopy level, was constructed from terrestrial laser scanning data using the combined model TreeQSM and FaNNI for woody structure and leaf insertion, respectively. Next, using empirical data and a realistic range of leaf-level biochemical and physiological parameters, we conducted a local sensitivity analysis to demonstrate the potential of the approach for assessing the impact of structural, biochemical and physiological factors on top of canopy (TOC) SIF. The analysis gave insight into the factors that drive the intensity and spectral properties of TOC SIF in heterogeneous boreal forest canopies. DART simulated red TOC fluorescence was found to be less affected by biochemical factors such as chlorophyll and dry matter contents or the senescent factor than far-red fluorescence. In contrast, canopy structural factors such as overstory leaf area index (LAI), leaf angle distribution and fractional cover had a substantial and comparable impact across all SIF wavelengths, with the exception of understory LAI that affected predominantly far-red fluorescence. Finally, variations in the fluorescence quantum efficiency (Fqe) of photosystem II affected all TOC SIF wavelengths. Our results also revealed that not only canopy structural factors but also understory fluorescence should be considered in the interpretation of tower, airborne and satellite SIF datasets, especially when acquired in the (near-) nadir viewing direction and for forests with open canopies. We suggest that the modelling strategy introduced in this study, coupled with the increasing availability of TLS and other 3D data sources, can be applied to resolve the interplay between physiological, biochemical and structural factors affecting SIF across ecosystems and independently of canopy complexity, paving the way for future SIF-based 3D photosynthesis models.Peer reviewe

The RAMI On-line Model Checker (ROMC): A web-based benchmarking facility for canopy reflectance models

The exploitation of global Earth Observation data hinges increasingly on physically-based radiative transfer (RT) models. These models simulate the interactions of solar radiation within a given medium (e.g., clouds, plant canopies) and are used to generate look-up-tables that are embedded into quantitative retrieval algorithms, such as those delivering the operational surface products for MODIS, MISR and MERIS. An assessment of the quality of canopy RT models thus appears essential if accurate and reliable information is to be derived from them. Until recently such an undertaking was a time consuming and labour intensive process that was made even more challenging by the general lack of absolute reference standards. Several years of benchmarking activities in the frame of the RAdiation transfer Model Intercomparison (RAMI) exercise have now led to the development of the RAMI On-line Model Checker (ROMC). The ROMC is a web-based tool allowing model developers and users to autonomously assess the performance of canopy RT models (http://romc.jrc.ec.europa.eu/). Access to the ROMC is free and enables users to obtain both statistical and graphical indications as to the performance of their canopy RT model. In addition to providing an overall indication of the skill of a given model to correctly match the reference data, the ROMC allows also for interactive comparison/evaluations of different model versions/submissions of a given user. AllROMCgraphs can be downloaded in PostScript format and come with a reference number for easy usage in presentations and publications. It is hoped that the ROMC will prove useful for the RT modeling community as a whole, not only by providing a convenient means to evaluate models outside the triennial phases of RAMI but also to attract participation in future RAMI activities

Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling

Methods to retrieve urban surface temperature (Ts) from remote sensing observations with sub-building scale resolution are developed using the Discrete Anisotropic Radiative Transfer (DART, Gastellu-Etchegorry, Grau and Lauret, 2012) model. Corrections account for the emission and absorption of radiation by air between the surface and instrument (atmospheric correction), and for the reflected longwave infrared (LWIR) radiation from non-black-body surfaces (“emissivity” correction) within a single modelling framework. The atmospheric correction a) can use horizontally and vertically variable distributions of atmosphere properties at high resolution (< 5 m); b) is applied here with vertically extrapolated weather observations and MODTRAN atmosphere profiles; and c) is a solution to ray tracing and cross section (e.g. absorption) conflicts (e.g. cross section needs the path length but it is typically unavailable during ray tracing). The emissivity correction resolves the reflection of LWIR radiation as a series of scattering events at high spatial (< 1 m) and angular (ΔΩ ≈ 0.02 sr) resolution using a heterogeneous distribution of radiation leaving the urban surfaces. The method is applied to a novel network of seven ground-based cameras measuring LWIR radiation across a dense urban area (extent: 420 m x 420 m) where a detailed 3-dimensional representation of the surface and vegetation geometry is used. Our unique observation set allows the method to be tested over a range of realistic conditions as there are variations in: path lengths, view angles, brightness temperatures, atmospheric conditions and observed surface geometry. For pixels with 250 (± 10) m path length the median (5th and 95th percentile) atmospheric correction magnitude is up to 4.5 (3.1 and 8.1) K at 10:10 on a mainly clear-sky day. The detailed surface geometry resolves camera pixel path lengths accurately, even with complex features such as sloped roofs. The atmospheric correction method evaluation, with simultaneous “near” (~15 m) and “far” (~155 m) observations, has a mean absolute error of 0.39 K. Using broadband approximations, the emissivity correction has clear diurnal variability, particularly when a cool and shaded surface (e.g. north facing) is irradiated by warmer (up to 17.0 K) surfaces (e.g. south facing). Varying the material emissivity with bulk values common for dark building materials (ε = 0.89 → 0.97) alters the corrected roof (south facing) surface temperatures by ~3 (1.5) K, and the corrected cooler north facing surfaces by less than 0.1 K. Corrected observations, assuming a homogeneous radiation distribution from surfaces (analogous to a sky view factor correction), differ from a heterogeneous distribution by up to 0.25 K. Our proposed correction provides more accurate Ts observations with improved uncertainty estimates. Potential applications include ground-truthing airborne or space-borne surface temperatures and evaluation of urban energy balance models

Anthropogenic Heat Flux Estimation from Space: Results of the first phase of the URBANFLUXES Project

H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. This will lead to the development of tools and strategies to mitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heat flux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the net change in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisit times and increase the value of EO data for scientific work and future emerging applications. These observations can reveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budget fluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity for space-borne observations to enable the development of operational services in the field of urban environmental monitoring and energy efficiency in cities. H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites)investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the UrbanEnergy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heatisland and consequently on energy consumption in cities. This will lead to the development of tools and strategies tomitigate these effects, improving thermal comfort and energy efficiency. In URBANFLUXES, the anthropogenic heatflux is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the netchange in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from EarthObservation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from theUEB closure. The project exploits Sentinels observations, which provide improved data quality, coverage and revisittimes and increase the value of EO data for scientific work and future emerging applications. These observations canreveal novel scientific insights for the detection and monitoring of the spatial distribution of the urban energy budgetfluxes in cities, thereby generating new EO opportunities. URBANFLUXES thus exploits the European capacity forspace-borne observations to enable the development of operational services in the field of urban environmentalmonitoring and energy efficiency in cities