Mapping individual trees from airborne multi-sensor imagery

Airborne multi-sensor imaging is increasingly used to examine vegetation properties. The advantage of using multiple types of sensor is that each detects a different feature of the vegetation, so that collectively they provide a detailed understanding of the ecological pattern. Specifically, Light Detection And Ranging (LiDAR) devices produce detailed point clouds of where laser pulses have been backscattered from surfaces, giving information on vegetation structure; hyperspectral sensors measure reflectances within narrow wavebands, providing spectrally detailed information about the optical properties of targets; while aerial photographs provide high spatial-resolution imagery so that they can provide more feature details which cannot be identified from hyperspectral or LiDAR intensity images. Using a combination of these sensors, effective techniques can be developed for mapping species and inferring leaf physiological processes at ITC-level. Although multi-sensor approaches have revolutionised ecological research, their application in mapping individual tree crowns is limited by two major technical issues: (a) Multi-sensor imaging requires all images taken from different sensors to be co-aligned, but different sensor characteristics result in scale, rotation or translation mismatches between the images, making correction a pre-requisite of individual tree crown mapping; (b) reconstructing individual tree crowns from unstructured raw data space requires an accurate tree delineation algorithm. This thesis develops a schematic way to resolve these technical issues using the-state-of-the-art computer vision algorithms. A variational method, called NGF-Curv, was developed to co-align hyperspectral imagery, LiDAR and aerial photographs.NGF-Curv algorithm can deal with very complex topographic and lens distortions efficiently, thus improving the accuracy of co-alignment compared to established image registration methods for airborne data. A graph cut method, named MCNCP-RNC was developed to reconstruct individual tree crowns from fully integrated multi-sensor imagery. MCNCP-RNC is not influenced by interpolation artefacts because it detects trees in 3D, and it detects individual tree crowns using both hyperspectral imagery and LiDAR. Based on these algorithms, we developed a new workflow to detect species at pixel and ITC levels in a temperate deciduous forest in the UK. In addition, we modified the workflow to monitor physiological responses of two oak species with respect to environmental gradients in a Mediterranean woodland in Spain. The results show that our scheme can detect individual tree crowns, find species and monitor physiological responses of canopy leaves

Interconnection of a Forest Growth Model and a Structural Model for Young Poplar Trees (Populus spp.)

Beim Anbau von schnellwachsenden Baumarten wie Pappel und Weide auf landwirtschaftlichen Flächen in Kurzumtriebsplantagen stellt die Standortwahl und die daran gebundene Ertragsprognose eine zentrale Entscheidung für den Bewirtschafter dar. In Verbindung mit dem Sortenaspekt besteht hier Forschungsbedarf zur Wechselwirkung von Standort und Genotyp hinsichtlich der Wuchsleistung. Ziel dieser Arbeit ist es, diese Fragestellungen auf mehreren Ebenen zu betrachten. Dazu wurde ein Multiskalen-Ansatz gewählt, in dessen Rahmen zwei Modellkomplexe entwickelt werden, um sie anschließend durch eine Schnittstelle zu verbinden. Der erste Komplex sieht dabei die Implementierung eines Ertragssimulators vor, der das einzelbaumbasierte Wachstum und die Mortalität in Abhängigkeit von Konkurrenz und Standortbedingungen abbildet. Die Datengrundlage hierfür stellen Zuwachsdaten aus dem vom BMEL geförderten ProLoc Verbundvorhaben dar. Dazu wird auf 18 Versuchsflächen zurückgegriffen, die auf einer breiten Amplitude standörtlicher Eigenschaften angelegt wurden. Nach einem einheitlichem Versuchsdesign wurden monoklonale Versuchsparzellen mit drei Pappel- und zwei Weidenklonen (interspezifisch gekreuzte Hybride) in zwei je dreijährigen Rotationen versuchstechnisch betreut und nach dem dritten Jahr auf den Stock gesetzt. Basierend auf der Vorlage des Waldwachstumssimulators BWINPro und der zugehörigen Programmbibliothek TreeGross werden mehrere Modelle parametrisiert, die neben den Überlebensraten nach der Pflanzung und dem Rückschnitt die Höhenzuwächse in der ersten und zweiten Rotation schätzen. Mit dem distanzunabhängigen Konkurrenzparameter “basal area of larger trees'' kann die Entwicklung innerhalb der Bestände abgebildet werden. Hinsichtlich der Wuchsleistung auf Standortebene stellen sich im Zuge der Variablenselektion die Parameter Pflanzdatum, nutzbare Feldkapazität, Bodenzahl, Niederschlagssumme im Mai und Juni und Mitteltemperatur im Juni und Juli als entscheidend heraus. Zur Schätzung des Höhenzuwachses und der Überlebensrate nach Rückschnitt wird die Baumhöhe vor der Ernte als unabhängige Variable genutzt. Der Faktor Klon deutet innerhalb der Modelle zwar auf Unterschiede in den Wachstumsvorgängen hin, Wechselwirkungen mit Standortvariablen können jedoch nicht festgestellt werden. Fehlende Variablen wie der durchschnittliche Gesamtzuwachs des Ertrags der Trockenmasse in t_atro ha^-1 a^-1 werden über zusätzliche am Datensatz parametrisierte Funktionen geschätzt. Die Einzelmodelle werden zu einem Simulationsablauf verbunden und die Gesamtschätzgüte überprüft. In der ersten Rotation können gute Ergebnisse erzielt werden mit quadrierten Korrelationen der beobachteten und geschätzten Bestandesmittelhöhen von 0.79. In der zweiten Rotation nimmt die Schätzgüte jedoch auf 0.53 ab. Es finden sich vereinzelte Standorte mit starken Abweichungen, als problematisch werden die Tiefe der Bodenbeprobung und fehlende erweiterte Informationen über den Wasserhaushalt vermutet. Der zweite Modellkomplex beinhaltet ein Strukturmodell, für das sich auf die Pappel-Genotpyen und die zweite Rotation beschränkt wird. Zunächst wurden mehrere Messmethoden identifiziert, die geeignet sind, die Baumarchitektur in Form von Geometrie und Topologie der oberirdischen holzigen Biomasse sowie die Morphologie der Belaubung hinsichtlich der Blattarchitektur und Blattform zu bestimmen. Für die Verzweigungsarchitektur wurden ein manuelles Verfahren und ein semi-automatisches Verfahren mit einem elektromagnetischen Digitizer zur Bestimmung der Astkrümmung gewählt und angewandt. Die Blattarchitektur wurde mit einem manuellen Verfahren gemessen. Die Blattform konnte per Digitalisierung von eingesammelten Blättern bestimmt werden. Im Zuge der Analyse der gewonnenen Daten werden mehrere Modelle parametrisiert. Hierdurch können für Apikal- und Lateralknospen die Austriebswahrscheinlichkeiten sowie die Dimension und Orientierung im Raum von sich bildenden Trieben geschätzt werden. Innerhalb der Modelle wird nach Haupt- und Nebenstämmen, Verlängerungs- und Seitentrieben, Lang- und Kurztrieben und innerhalb der Seitentriebe nach sylleptischen sowie regulären Trieben differenziert. Der Ausgangspunkt ist hier die Schätzung die Internodienanzahl je Trieb, die über die Trieblänge wiederum andere Parameter wie den Verzweigungswinkel und die Krümmung beeinflusst. Weitere Faktoren, die mehreren Modellen zugrunde liegen, sind das Alter und die Verzweigungsordnung sowie der genotypische Einfluss. Parameter wie die Belaubung und die Blattgröße lassen sich mitunter durch die relative Höhe am Baum schätzen. Die Blattform wiederum wird durch Konturpunkte bestimmt, deren Koordinaten in Abhängigkeit von der Blattlänge berechnet werden. Im Rahmen der Analyse dieser Modelle stellen sich geringe Unterschiede in der Struktur zwischen den Klonen heraus. Ausnahmen stellen die Krümmung und Verzweigungswinkel der Seitentriebe für einen der Klone dar, bei dem die Modelle den beobachtbaren schlankeren Habitus gut reproduzieren. Deutliche Unterschiede ergeben sich auch bei den Blattformen, die die Blattformen der zugrundeliegenden Elternspezies der Hybride wiedergeben. Die einzelnen Modellfunktionen werden anschließend als Gesamt-Strukturmodell in der Modellplattform GroIMP implementiert. Das erhaltene Modell kann in Jahresschritten die Entwicklung der Baumstruktur für jeden der drei Klone abbilden. Wahlweise können beliebig große Bestände simuliert werden, die durch stochastische Komponenten im Modell über eine realitätsnahe Variabilität der Baumgrößen verfügen. Die Verbindung der beiden Modellkomplexe wird durch eine Schnittstelle realisiert, die den Import von Einzelbaumdaten aus dem Ertragsmodell in das Strukturmodell vorsieht. Zwei weitere Modelle werden parametrisiert, um für das Strukturmodell die Internodienanzahl aus der Trieblänge als jährliche Höhenzuwächse des Ertragsmodells ermitteln zu können und das Wachstum der Nebenstämme an den Hauptstamm anzupassen. Darüber hinaus können die vom Ertragssimulator erzeugten Ausfälle in den Beständen berücksichtigt werden. Zukünftige Forschungsarbeiten werden zeigen, inwiefern das hier entwickelte Ertragsmodell durch eine Validierung mit Daten aus anderen Versuchen weiterentwickelt werden kann, um auch tiefere Bodenschichten mit einzubeziehen. Das Strukturmodell könnte durch Einbau eines Physiologiemoduls zu einem vollständigen Funktions-Struktur-Pflanzenmodell ausgebaut werden. Durch die Erweiterung der Schnittstelle zur Rückgabe von Daten vom Strukturmodell zum Ertragsmodell wäre auch eine Verbesserung der Schätzgüte z.B. durch erweiterte Möglichkeiten zur Modellierung der Konkurrenzverhältnisse vorstellbar.When planting fast-growing tree species such as poplars and willows on agricultural land in short rotation coppice plantations, site selection and the associated yield potential pose a central decision for the practitioner. In connection with the cultivar aspect there has been a need for research on the interaction between site and genotype in terms of growth performance. The aim of this work is to examine these questions on several levels. For this purpose, a multi-scale approach was chosen in the framework of which two model complexes are developed which are then connected by an interface. The first model complex incorporates the implementation of a yield simulator which depicts single tree based growth and mortality as a function of competition and site conditions. The data basis for this is growth data from the joint research project ProLoc funded by the BMEL. For this purpose, 18 trial sites are chosen which were initiated on a broad amplitude of environmental conditions. Following a uniform experimental design, monoclonal trial plots with three poplar and two willow clones (interspecific crossed hybrids) were supervised in two tri-annual rotations and cut back after the third year. Based on the model of the forest growth simulator BWINPro and the associated TreeGross program library, several models are parameterized which, in addition to the survival rates after planting and harvest, estimate the height increment in the first and second rotation. With the distance-independent competition index ``basal area of larger trees'' the development within the stands can be predicted. Regarding the growth performance on the site level, the parameters of planting date, available water capacity, German agricultural soil quality rating, sum of precipitation in May and June and mean temperature in June and July are identified as influential by variable selection. To estimate the height increment and survival after pruning, tree height before harvest is regarded as an independent variable. The factor clone indicates differences in the growth processes within the models but interactions with site variables can not be determined as significant. Missing variables such as the mean annual increment in dry matter yield in oven-dry tons ha^-1 a^-1 are estimated by additional functions parameterized with the dataset. The individual models are connected to a simulation procedure and the overall predictive power is assessed. Good results can be achieved for the first rotation with squared correlations of the observed and estimated mean stand height of 0.79. However, in the second rotation the estimation quality decreases to 0.53. There are single sites with considerable deviations. The depth of the soil sampling and missing extended information on the water supply are suspected as problematic here. The second model complex includes a structural model focused on the poplar genotypes and the second rotation. First, several measuring methods were identified which are deemed suitable for determining the tree architecture in terms of geometry and topology of the above-ground woody biomass, as well as the morphology of foliage in terms of leaf architecture and leaf shape. For the branch architecture, a manual method and a semi-automatic method with an electromagnetic digitizer for determining branch curvature have been selected and employed. The leaf architecture was measured by a manual method. The leaf shape could be determined by digitizing collected leaves. After analyzing the obtained data, several models are parameterized. As a result, the probability of bud growth and the dimensions and orientation in space of developing shoots can be estimated for apical and lateral buds. The models differentiate between main and minor stems, prolongation and lateral shoots, long and short shoots and, within the lateral shoots, sylleptic and regular shoots. The starting point here is the estimation of the number of internodes per shoot which in turn influences other parameters such as the branch angle and the curvature through the shoot length. Other factors underlying several models are the age, branch order and the genotypic influence. Parameters such as foliage and leaf size can mainly be estimated by the relative height with regard to the absolute tree height. The leaf shape in turn is determined by contour points whose coordinates are calculated as a function of the leaf blade length. As part of the analysis of these models, only slight differences in the structure between the clones are found. Exceptions are the curvature and branching angles of the lateral shoots for one of the clones, for which the models reproduce the observable slender habitus. Significant differences also occur in the leaf shape which reflect the leaf shapes of the underlying parent species of the hybrids. The individual model functions are then implemented into a structural model in the model platform GroIMP. The resulting model can simulate the development of the tree structure for each of the three clones in annual steps. Arbitrarily large stands can be simulated that have realistically varying tree sizes through stochastic components in the model. The interconnection of the two model complexes is realized through the import of single tree data from the yield model into the structural model. Two further models are parameterized to determine the number of internodes from the shoot length as annual height increment of the yield model for the structural model and to modify the growth of the minor stems in dependence of the main stem growth. Additionally, the single tree mortality generated by the yield simulator is incorporated into the structural model. Further research will show whether it is possible to improve the yield model by validation with data from other experiments to include deeper soil layers here. The structural model could be extended to a complete functional structural plant model by incorporating a physiology module. By extending the interconnection to return data from the structural model to the yield model, the predictive power could be improved, for example by means of extended possibilities for modeling the within-stand competition dynamics

Journal of Telecommunications and Information Technology, 2010, nr 2

kwartalni

Forestry Applications of Unmanned Aerial Vehicles (UAVs) 2019

Unmanned aerial vehicles (UAVs) are new platforms that have been increasingly used in the last few years for forestry applications that benefit from the added value of flexibility, low cost, reliability, autonomy, and capability of timely provision of high-resolution data. The main adopted image-based technologies are RGB, multispectral, and thermal infrared. LiDAR sensors are becoming commonly used to improve the estimation of relevant plant traits. In comparison with other permanent ecosystems, forests are particularly affected by climatic changes due to the longevity of the trees, and the primary objective is the conservation and protection of forests. Nevertheless, forestry and agriculture involve the cultivation of renewable raw materials, with the difference that forestry is less tied to economic aspects and this is reflected by the delay in using new monitoring technologies. The main forestry applications are aimed toward inventory of resources, map diseases, species classification, fire monitoring, and spatial gap estimation. This Special Issue focuses on new technologies (UAV and sensors) and innovative data elaboration methodologies (object recognition and machine vision) for applications in forestry

Model checking and compositional reasoning for multi-agent systems

Multi-agent systems are distributed systems containing interacting autonomous agents designed to achieve shared and private goals. For safety-critical systems where we wish to replace a human role with an autonomous entity, we need to make assurances about the correctness of the autonomous delegate. Specialised techniques have been proposed recently for the verification of agents against mentalistic logics. Problematically, these approaches treat the system in a monolithic way. When verifying a property against a single agent, the approaches examine all behaviours of every component in the system. This is both inefficient and can lead to intractability: the so-called state-space explosion problem. In this thesis, we consider techniques to support the verification of agents in isolation. We avoid the state-space explosion problem by verifying an individual agent in the context of a specification of the rest of the system, rather than the system itself. We show that it is possible to verify an agent against its desired properties without needing to consider the behaviours of the remaining components. We first introduce a novel approach for verifying a system as a whole against specifications expressed in a logic of time and knowledge. The technique, based on automata over trees, supports an efficient procedure to verify systems in an automata-theoretic way using language containment. We show how the automata-theoretic approach can be used as an underpinning for assume-guarantee reasoning for multi-agent systems. We use a temporal logic of actions to specify the expected behaviour of the other components in the system. When performing modular verification, this specification is used to exclude behaviours that are inconsistent with the concrete system. We implement both approaches within the open-source model checker MCMAS and show that, for the relevant properties, the assume-guarantee approach can significantly increase the tractability of individual agent verification.Open Acces

The consideration of forestry effects in wind energy resource assessment

Research focused on the reduction of uncertainties when considering the wind resource in the vicinity of forestry. This thesis examined the use of high density laser scanning technology to capture the structure of forest canopies along with the measurement of thermal effects using sonic anemometry. Methodologies were then developed to include these high quality data in Computational Fluid Dynamics software in order to allow the complex nature of forestry flows to be considered analytically

Pathogen diversity and host resistance in dieback disease of cocoa caused by Fusarium decemcellulare and Lasiodiplodia theobromae

Dieback disease caused by Fusarium and Lasiodiplodia species is a major threat to cocoa production in Ghana and elsewhere in West Africa. Current recommendations involve insecticide application to control mirid bugs whose feeding punctures provide entry points for these fungi. Little is known about the true identity of the causal pathogens of this disease. Earlier work implicated F. decemcellulare as the causal agent and more rarely L. theobromae (Cotterell, 1927; Crowdy, 1947). A total of 117 single spore fungal cultures was established from diseased cocoa stems imported from Ghana. On morphological grounds cultures could be designated as either Fusarium or Lasiodiplodia spp. The Fusarium cultures exhibited inter-isolate variability with respect to macroscopic appearance and macro-conidium morphology, suggesting the presence of more than a single species. The isolates were further characterised by PCR amplification and sequencing of the ITS region of rDNA and comparison with authentic reference cultures. Thirty-seven Fusarium isolates were identified to twenty F. chlamydosporum, nine F. solani and four isolates each of F. oxysporum and F. proliferatum. The thirty-six Lasiodiplodia isolates were identified to two species, twenty-seven L. pseudotheobromae and nine L. theobromae. In pathogenicity tests, F. chlamydosporum, F. oxysporum, F. proliferatum, F. solani and L. pseudotheobromae, previously unknown as pathogens of either cocoa or any member of the Malvaceae, caused significant wilting and dieback in Amelonado seedlings similar to that observed in the field. All isolates exhibited optimal growth at 30 ºC on PDA. Disease incidence in 29 and 15 cocoa germplasm lines in the laboratory and greenhouse, respectively, showed reproducible differences in their reaction to necrotic lesion and dieback infection. LCTEEN 37/F was one of the most susceptible genotypes. CATIE 1000, T85/799 and MXC 67 were the most tolerant and could be used in cocoa breeding programmes for resistance to dieback

Hydrology in Water Resources Management

This book is a collection of 12 papers describing the role of hydrology in water resources management. The papers can be divided s according to their area of focus as 1) modeling of hydrological processes, 2) use of modern techniques in hydrological analysis, 3) impact of human pressure and climate change on water resources, and 4) hydrometeorological extremes. Belonging to the first area is the presentation of a new Muskingum flood routing model, a new tool to perform frequency analysis of maximum precipitation of a specified duration via the so-named PMAXΤP model (Precipitation MAXimum Time (duration) Probability), modeling of interception processes, and using a rainfall-runoff GR2M model to calculate monthly runoff. For the second area, the groundwater potential was evaluated using a model of multi-influencing factors in which the parameters were optimized by using geoprocessing tools in geographical information system (GIS) in combination with satellite altimeter data and the reanalysis of hydrological data to simulate overflow transport using the Nordic Sea as an example. Presented for the third area are a water balance model for the comparison of water resources with the needs of water users, the idea of adaptive water management, impacts of climate change, and anthropogenic activities on the runoff in catchment located in the western Himalayas of Pakistan. The last area includes spatiotemporal analysis of rainfall variability with regard to drought hazard and use of the copula function to meteorologically analyze drought