Coniferous Canopy BRF Simulation Based on 3-D Realistic Scene

It is difficulties for the computer simulation method to study radiation regime at large-scale. Simplified coniferous model was investigate d in the present study. It makes the computer simulation methods such as L-systems and radiosity-graphics combined method (RGM) more powerf ul in remote sensing of heterogeneous coniferous forests over a large -scale region. L-systems is applied to render 3-D coniferous forest scenarios: and RGM model was used to calculate BRF (bidirectional refle ctance factor) in visible and near-infrared regions. Results in this study show that in most cases both agreed well. Meanwhiie at a tree and forest level. the results are also good

A physiological Plant Growth Simulation Engine Based on Accurate Radiant Energy Transfer

We present a new model for plant growth simulation, taking into account the eco-physiological processes driving plant development with unprecedented fidelity. The growth model, based on a physiological analysis, essentially simulates the internal function of the plant, and has been validated against measured biological data with excellent results. We show how to account for the influence of light through photosynthesis, and thereby incorporate the effects of a given plant's immediate environment on its architecture, shape and size. Since biological matter is controlled by water transpiration and received radiant enery, the model requires efficient and accurate simulation of radiant energy exchanges. We describe a complete lighting simulation system tailored for the difficult case of plants, by adapting state-of-the-art techniques such as hierarchical instanciation for radiosity and general BRDF modeling. Our results show that (a) our lighting simulation system efficiently provides the required information at the desired level of accuracy, and (b) the plant growth model is extremely well calibrated against real plants and (c) the combined system can simulate many interesting growth situations with direct feedback from the environment on the plant's characteristics. Applications range from landscape simulation to agronomical and agricultural studies, and to the design of virtual plants responding to their environment

An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration

We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity

Remote sensing of leaf area index : enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.Ei saatavill

Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data

A synergistic algorithm for producing global leaf area index and fraction of absorbed photosynthetically active radiation fields from canopy reflectance data measured by MODIS (moderate resolution imaging spectroradiometer) and MISR (multiangle imaging spectroradiometer) instruments aboard the EOS-AM 1 platform is described here. The proposed algorithm is based on a three-dimensional formulation of the radiative transfer process in vegetation canopies. It allows the use of information provided by MODIS (single angle and up to 7 shortwave spectral bands) and MISR (nine angles and four shortwave spectral bands) instruments within one algorithm. By accounting features specific to the problem of radiative transfer in plant canopies, powerful techniques developed in reactor theory and atmospheric physics are adapted to split a complicated three-dimensional radiative transfer problem into two independent, simpler subproblems, the solutions of which are stored in the form of a look-up table. The theoretical background required for the design of the synergistic algorithm is discussed

Latvusarkkitehtuuri ja sen rooli lajien välisessä vuorovaikutuksessa boreaalisissa sekametsissä

This thesis concerns crown architecture and its role in species interactions in mixed forests. The species specific growth patterns make plastic tree architecture respond in different manner to different environments modifying their influence to neighbours. The main aims were to separate the effect of neighbour species identity from the abundance, size and proximity of the neighbours in between-tree competition and to link crown architecture with hydraulic architecture by identifying the associated within-tree variation of crown traits. The empirical part of the work was based on digitising three-dimensional (3D) crown architecture and measuring xylem anatomy. Digitising allowed the development of crown architecture models for Betula pendula (Roth.) and Pinus sylvestris (L.). The models were further applied to simulate light transmission in mixed stands. Crown architecture of the studied species responded to increased competition intensity primarily by reducing branch number and size. Proportional biomass distribution to foliage and main branches over the stem increased in young B. pendula with increasing competition intensity, whereas Pinus sylvestris used the opposite strategy. In addition to competition intensity, crown architecture of the studied species showed plastic responses to the species identity of neighbouring trees. Lower overall growth but added height growth indicating stronger competition was found in mixtures of B. pendula and Pinus sylvestris compared to monocultures. Both species-specific effects on resource gradients and non-resource signals remain plausible explanations for this result: B. pendula transmitted more light than Pinus sylvestris at simulated dense stands. Hydraulic architecture was shown to be interlinked with crown architecture as the conduit diameter varied as a function of tree compartment, branching hierarchy, leaf area and distance from the apex. The results suggest that the use of detailed tree structure models and species-specific competition analysis is useful in predicting and understanding growth in mixed boreal stands.Tutkin väitöskirjassani puiden latvuksen rakennetta ja sen roolia lajien välisessä vuorovaikutuksessa sekametsässä. Aiheesta tekee kiehtovan latvusrakenteen joustavuus eli puut vastaavat herkästi kasvuympäristössään tapahtuviin muutoksiin muokkaamalla rakennettaan. Kiinnostus puulajiston monimuotoisuutta suosivaa metsänkasvatusta kohtaan on kasvussa, mutta silti tiedämme melko vähän siitä, miten pääpuulajiemme latvusrakenne toimii kilpailtaessa elintilasta ja resursseista metsiköiden sisällä. Väitöskirjassani keskityin selvittämään miten puiden rungon, oksien ja versojen muodostama latvusrakenne muuttuu naapuripuista johtuvan kilpailun vaikutuksesta, ja onko muutoksissa naapuripuulajista johtuvia eroja. Halusin myös ymmärtää paremmin minkälainen suhde on latvuksen ulkoisella ja puuaineen sisäisellä rakenteella. Väitöskirjani tulokset osoittavat, että mänty ja koivu vastaavat molemmat latvuskilpailuun mm. kasvattamalla vähemmän ja pienempiä oksia, joissa lehdetön osuus oksan pituudesta kasvaa. Lajien välillä näyttää kuitenkin olevan eroa biomassan suhteellisessa jakautumisessa, sillä nuorilla koivuilla pääoksien osuus kokonaisbiomassasta kasvoi kilpailun lisääntyessä rungon kustannuksella, kun taas nuorilla männyillä rungon biomassaosuus kasvoi. Männyn ja koivun latvusrakenne muuttuu paitsi naapuripuiden koon, lukumäärän ja etäisyyden suhteen myös naapuruston pääpuulajin suhteen. Sekä mänty että koivu kasvoivat toistensa ympäröimänä enemmän pituutta, mutta niiden kokonaiskasvu oli alhaisempi verrattuna lajitovereiden ympäröimiin yksilöihin. Selvitimme tuloksen taustoja metsiköiden valaistussimulaatioiden avulla ja havaitsimme, että koivikko päästi tiheissä metsiköissä valoa latvuston läpi samanpituista männikköä enemmän, mutta harvemmissa metsiköissä tätä eroa ei ollut. Tulosten mukaan ennustettaessa latvusrakennetta ja kasvua, naapuripuiden lajityypillinen rakenne on otettava huomioon niiden kilpailuvaikutusta arvioitaessa. Tulokseni osoittavat myös, että puun solukoiden rakenne on yhteydessä ulkoiseen latvusrakenteeseen. Vesi kulkee puun sisällä juurista ylös haihduttaviin lehtiin vedenkuljetussoluista muodostuneissa putkimaisissa rakenteissa. Vedenkuljetussolujen läpimitta leveni odotetusti ylhäältä alaspäin etäisyyden funktiona. Tämän lisäksi solukoko pieneni ja solutiheys kasvoi hyppäyksenomaisesti siirryttäessä rungosta oksiin, pääoksista sivuhaaroihin ja koivun tapauksessa oksista lehtiruoteihin. Myös lehtiruodeissa solukoko vaihteli lehden pinta-alan funktiona. Näyttääkin siltä, että myös vedenkuljetussolukon rakenne heijastaa joustavan latvusrakenteen välityksellä kasvuympäristön tilaa kuten latvuskilpailua

Extraction of Vegetation Biophysical Structure from Small-Footprint Full-Waveform Lidar Signals

The National Ecological Observatory Network (NEON) is a continental scale environmental monitoring initiative tasked with characterizing and understanding ecological phenomenology over a 30-year time frame. To support this mission, NEON collects ground truth measurements, such as organism counts and characterization, carbon flux measurements, etc. To spatially upscale these plot-based measurements, NEON developed an airborne observation platform (AOP), with a high-resolution visible camera, next-generation AVIRIS imaging spectrometer, and a discrete and waveform digitizing light detection and ranging (lidar) system. While visible imaging, imaging spectroscopy, and discrete lidar are relatively mature technologies, our understanding of and associated algorithm development for small-footprint full-waveform lidar are still in early stages of development. This work has as its primary aim to extend small-footprint full-waveform lidar capabilities to assess vegetation biophysical structure. In order to fully exploit waveform lidar capabilities, high fidelity geometric and radio-metric truth data are needed. Forests are structurally and spectrally complex, which makes collecting the necessary truth challenging, if not impossible. We utilize the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model, which provides an environment for radiometric simulations, in order to simulate waveform lidar signals. The first step of this research was to build a virtual forest stand based on Harvard Forest inventory data. This scene was used to assess the level of geometric fidelity necessary for small-footprint waveform lidar simulation in broadleaf forests. It was found that leaves have the largest influence on the backscattered signal and that there is little contribution to the signal from the leaf stems and twigs. From this knowledge, a number of additional realistic and abstract virtual “forest” scenes were created to aid studies assessing the ability of waveform lidar systems to extract biophysical phenomenology. We developed an additive model, based on these scenes, for correcting the attenuation in backscattered signal caused by the canopy. The attenuation-corrected waveform, when coupled with estimates of the leaf-level reflectance, provides a measure of the complex within-canopy forest structure. This work has implications for our improved understanding of complex waveform lidar signals in forest environments and, very importantly, takes the research community a significant step closer to assessing fine-scale horizontally- and vertically-explicit leaf area, a holy grail of forest ecology

Modélisation de l'architecture des forêts pour améliorer la télédétection des attributs forestiers

The quality of indirect measurements of canopy structure, from in situ and satellite remote sensing, is based on knowledge of vegetation canopy architecture. Technological advances in ground-based, airborne or satellite remote sensing can now significantly improve the effectiveness of measurement programs on forest resources.The structure of vegetation canopy describes the position, orientation, size and shape of elements of the canopy.The complexity of the canopy in forest environments greatly limits our ability to characterize forest structural attributes. Architectural models have been developed to help the interpretation of canopy structural measurements by remote sensing. Recently, the terrestrial LiDAR systems, or TLiDAR ( Terrestrial Light Detection and Ranging ), are used to gather information on the structure of individual trees or forest stands.The TLiDAR allows the extraction of 3D structural information under the canopy at the centimetre scale.The methodology proposed in my Ph.D. thesis is a strategy to overcome the weakness in the structural sampling of vegetation cover.The main objective of the Ph.D. is to develop an architectural model of vegetation canopy, called L-Architect (LiDAR data to vegetation Architecture ), and to focus on the ability to document forest sites and to get information on canopy structure from remote sensing tools. Specifically, L-Architect reconstructs the architecture of individual conifer trees from TLiDAR data. Quantitative evaluation of L-Architect consisted to investigate (i) the structural consistency of the reconstructed trees and (ii) the radiative coherence by the inclusion of reconstructed trees in a 3D radiative transfer model. Then, a methodology was developed to quasi-automatically reconstruct the structure of individual trees from an optimization algorithm using TLiDAR data and allometric relationships. L-Architect thus provides an explicit link between the range measurements of TLiDAR and structural attributes of individual trees. L-Architect has finally been applied to model the architecture of forest canopy for better characterization of vertical and horizontal structure with airborne LiDAR data. This project provides a mean to answer requests of detailed canopy architectural data, difficult to obtain, to reproduce a variety of forest covers. Because of the importance of architectural models, L-Architect provides a significant contribution for improving the capacity of parameters' inversion in vegetation cover for optical and lidar remote sensing