1,721,061 research outputs found
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
No full textLarge-scale remote sensing reveals that tree mortality in Germany appears to be greater than previously expected
No full textGlobal warming poses a major threat to forests and events of increased tree mortality are observed globally. Studying tree mortality often relies on local-level observations of dieback while large-scale analyses are lacking. Satellite remote sensing provides the spatial coverage and sufficiently high temporal and spatial resolution needed to investigate tree mortality at landscape-scale. However, adequate reference data for training satellite-based models are scarce. In this study, we employed the first maps of standing deadwood in Germany for the years 2018–2022 with 10 m spatial resolution that were created by using tree mortality observations spotted in hundreds of drone images as the reference. We use these maps to study spatial and temporal patterns of tree mortality in Germany and analyse their biotic and abiotic environmental drivers using random forest regression. In 2019, the second consecutive hotter drought year in a row, standing deadwood increased steeply to 334 ± 189 kilohectar (kha) which corresponds to 2.5 ± 1.4% of the total forested area in Germany. Picea abies, Pinus sylvestris, and Fagus sylvatica showed highest shares of standing deadwood. During 2018–2021 978 ± 529 kha (7.9 ± 4.4%) of standing dead trees accumulated. The higher mortality estimates that we report compared to other surveys (such as the ground-based forest condition survey) can be partially attributed to the fact that remote sensing captures mortality from a bird’s eye perspective and that the high spatial detail (10 m) in this study also captures scattered occurrences of tree mortality. Atmospheric drought (i.e. climatic water balance and vapor pressure deficit) and temperature extremes (i.e. number of hot days and frosts after vegetation onset) were the most important predictors of tree mortality. We found increased tree mortality for smaller and younger stands and on less productive sites. Monospecific stands were generally not more affected by mortality than average, but only when interactions with damaging insects (e.g. bark beetles) occurred. Because excess tree mortality rates threaten many forests across the globe, similar analyses of tree mortality are warranted and technically feasible at the global scale. We encourage the international scientific community to share and compile local data on deadwood occurrences (see example: www.deadtrees.earth) as such a collaborative effort is required to help understand mortality events on a global scale
Trees with benefits: selected ecosystem services provided by trees in agroforestry systems
No full textThe threat of climate change is as real as ever and is already having numerous negative impacts on humans, while also contributing to the biodiversity crisis and the associated erosion of ecosystem services (ES). One of the many potential strategies for mitigating and adapting to climate change is a category of land management systems known as agroforestry. Agroforestry systems (AFS) combine agricultural production with trees or shrubs, which can provide a variety of ES and additional benefits compared to modern farming methods. Despite the growing interest in AFS in the context of climate change, knowledge on trees and shrubs in AFS is still limited. A greater knowledge of these woody structures could assist in the planning, optimisation and promotion of AFS. This dissertation aims to contribute to filling this knowledge gap. In this cumulative thesis, selected ES provided by trees in AFS were analysed for a number of tree species. In particular, carbon storage, provision of floral resources and tree shading were analysed exemplarily for a number of tree species, namely the common walnut (Juglans regia L.), the wild cherry (Prunus avium L.), the domestic apple (Malus domestica Borkh.) and the Simon's poplar (Populus simonii Carrière). Most of these analyses were based on terrestrial laser scanning (TLS) and consequent usage of quantitative structural models (QSMs). For this reason, additional analyses were carried out on these methods. The methodological analyses revealed both the limitations and the potential of TLS. It was shown that the quality of the TLS data, and hence the reconstructed QSMs and derived parameters, deteriorated dramatically with increasing distance between scanner and branches. This effect was particularly pronounced for thin branches. We also presented the combination of TLS data with thermal imagery, a promising data combination that could be used to analyse various ecophysiological processes. Using 3D thermal data, for example, we were able to demonstrate the cooling effect of soil water on stem temperatures. The studies analysing trees in AFS were grouped according to the investigated ES. The first group focused on carbon storage. In these studies, allometric functions were derived to estimate tree dimensions, biomass, carbon and nutrient content for walnut, cherry and poplar. These studies also introduced a new approach to estimate tree bark and wood volumes separately based on TLS data, QSMs and bark thickness models. In the second group, the floral resources of cherry trees were analysed and a new methodology for scaling the number of flowers from branch to tree level was presented. It was shown that larger trees produce a disproportionate number of flowers, and thus, nectar and pollen. The third group includes the description of a model for simulating the shade cast by trees, which was applied and validated on an apple tree. The approach is based on TLS data and QSMs of trees without foliage. Leaves were modelled on the QSMs to simulate shading throughout the year. The implementation of this approach represents an improvement over similar models in terms of functionality and calculation efficiency. Overall, this work demonstrates the wide variety of ES provided by trees in AFS and the great potential of TLS to analyse them. The analyses of different ES conducted here contribute to filling the knowledge gap concerning trees within AFS and provide valuable insights for the planning and optimisation of AFS. Our results show that carbon sequestration potential and provision of floral resources are strongly dependent on tree size, with larger trees providing disproportionately more of these ES. Although this relationship is well known for tree biomass, we are the first to confirm this relationship for the number of flowers per tree. In addition, several new methods were presented that demonstrate the potential of TLS for investigating AFS and could aid future research. Thus, this thesis makes an important contribution to current research, both in terms of content and methodology
Drone remote sensing for forest health monitoring
No full textForest health is critical for maintaining the multitude of ecosystem ser-vices that forests provide, including carbon sequestration, biodiversityconservation, water regulation, and soil conservation. The ability offorests to perform these functions is directly linked to their health con-dition, making forest health monitoring essential for sustainable forestmanagement and climate change mitigation. Traditional methods ofmonitoring forest health involve time-consuming and labor-intensive,sample-based ground observations. While valuable, these methodsare limited in scope and scalability and include highly subjectiveevaluations.This research addresses these limitations by exploring UncrewedAerial Vehicle (UAV)-based forest health monitoring as a viable alter-native. This dissertation is based on three articles that were preparedas part of a multi-year remote sensing research project at the BavarianState Institute of Forestry (LWF). In the course of the project, 235Level-1-Monitoring plots of the International Co-operative Programon Assessment and Monitoring of Air Pollution Effects on Forests (ICPForests) were surveyed with UAVs in parallel to the terrestrial inven-tories in the years 2020– 2022. In this way multispectral aerial imageswere collected and merged into a large long-term and cross-temporaltime-series dataset.The first article scopes the theoretical foundation of the work. Witha review that provides researchers and practitioners with an overviewof previous work related to forest health monitoring and that intro-duces the latest technology. To achieve this, 99 papers were evaluated,offering a broad perspective on advancements and methodologies inthe field of UAV-based forest health monitoring. The review identi-fied research gaps and trends to guide future research efforts anddirections.Based on this gathered knowledge, the subsequent articles built onthese insights to develop and test innovative UAV-based monitoringtechniques. Consequently, the research presented in the second articledescribes the development of an open-source data pipeline that aimsto link UAV data with field data of forest health assessments in astandardized and streamlined process. This contributed to the semi-automatic generation of training data for the training of deep learningmodels. In a large-scale flight campaign, multispectral UAV data from235 ICP Forests inventory plots in Bavaria were recorded annually overthe years 2020- 2022. The field data from the same inventory points ofthe related years were used as a reference to validate the aerial data.With the developed pipeline, more than 17,000 training samples of thefive major tree species occurring in Germany including their healthstatus, two genus classes as well as dead trees could be generated.In this way, we were able to classify 14 different classes with anaverage macro F1-score of 0.61 using the EfficientNet ConvolutionalNeural Network (CNN) architecture. The highest class-specific F1score besides the class of dead trees (0.97) was achieved by the classof healthy Picea abies (0.80).Originating from the same database, species-specific gradient-boosting models were trained. The results, presented in the thirdarticle, indicate that multispectral images captured by a drone closelymatch field data and allow for effective detection of physiologicalstress in trees. Surprisingly, in addition to the red, red-edge, and near-infrared bands, the blue band also proved to be a critical indicator oftree stress, with its effectiveness varying depending on factors suchas tree species, classification detail, and atmospheric conditions. Fur-thermore, the values averaged over three years per sample tree, alongwith the 5th and 25th percentiles of the data distribution, were foundto be particularly important because they provide a more compre-hensive understanding of tree stress patterns over time. The use ofpercentiles helps to capture the variability and extremes in the dataset,highlighting early signs of stress that may not be visible in averagevalues alone. The species-specific models were then trained based onthe spectral indices, resulting in good classification accuracies (MacroF1-Score between 0.492 and 0.769).In essence, this thesis examines the integration of traditional moni-toring methods with UAV-based remote sensing to enhance the effi-ciency and effectiveness of forest health assessments. Through casestudies and empirical data, the research demonstrates how dronescan identify stress responses in trees and provide insights into forestdynamics.The findings suggest that drone technology offers a significant ad-vancement in forest health monitoring, supporting the developmentof targeted conservation strategies and sustainable forest managementpractices. Compared to traditional methods, UAVs enable more ob-jective assessments through high-resolution, wall-to-wall mapping,providing full coverage of large areas at lower costs and with greaterefficiency. This approach has the potential to ensure that forests con-tinue to thrive, provide essential ecosystem services, and contribute tolong-term economic sustainability in the face of increasing environ-mental challenges
Linking Canopy Reflectance and Plant Functioning through Radiative Transfer Models
Full text linkVon den Tropen bis zur Tundra hat sich die Pflanzenwelt durch Anpassungen an lokale Umwelteinflüsse diversifiziert. Diese Anpassungen sind in der Funktionsweise der Pflanzen manifestiert, welche unter anderem Wachstum, Fortpflanzung, Konkurrenzfähigkeit oder Ausdauer beinhalten. Pflanzenfunktionen haben nicht nur direkten Einfluss auf die Artenzusammensetzung, sondern auch auf großräumige Prozesse wie Bio- und Atmossphäreninteraktionen oder Stoffkreisläufe. Folglich wurden viele Forschungsanstrengungen unternommen um Pflanzenfunktionen weiter zu verstehen und zu erfassen, z.B. darauf abzielend generalisierende Modelle von Pflanzenfunktionen zu entwickeln oder individuelle Pflanzenmerkmale als Indikatoren für Pflanzenfunktion zu identifizieren. Trotz der wissenschaftlichen Fortschritte fehlt ein vollständiges Bild der Funktionsvielfalt der Pflanzenwelt, sowohl in geographischer als auch funktioneller Hinsicht. Dies ist im Wesentlichen auf die Komplexität und die logistischen Einschränkungen bei der Messung von Pflanzenfunktionen im Feld zurückzuführen. Um dieses Bild zu vervollständigen wird insbesondere optischen Erdbeobachtungsdaten ein hohes Potenzial zugeschrieben. Optische Erdbeobachtungssensoren erfassen das vom Kronendach reflektierte Sonnenlicht. Letzteres wird durch verschiedene biochemische und strukturelle Pflanzenmerkmale (im Folgenden optische Merkmale) beeinträchtigt (z.B. Blattchlorophyllgehalt oder Blattwinkel). Das Abfangen und Absorbieren von Sonnenlicht ist die Grundlage des pflanzeneigenen Metabolismus und folglich liegt es Nahe, dass diese optischen Merkmale direkt mit Pflanzenfunktionen zusammenhängen. Der Zusammenhang dieser optische Merkmale mit Pflanzenfunktionen wurde jedoch noch nicht systematisch untersucht, und ebenso ist der Zusammenhang zwischen Pflanzenfunktion und Kronendachreflektion noch nicht vollständig untersucht. Die physikalischen Interaktionen von Licht und optischen Pflanzenmerkmalen sind bereits hinreichend verstanden und in Strahlungstransfermodellen (RTM) für Vegetationskronendächer formuliert. RTM können als prozessbasierte Modelle betrachtet werden, die die Reflektion des Kronendachs in Abhängigkeit von optische Merkmalen, dem Bodenhintergrund und der Sonnen-Sensorgeometrie modellieren. Das Ziel und die Innovation dieser Dissertation war die kausalen Zusammenhänge zwischen Kronendachreflektion und Pflanzenfunktion mittels RTM zu verstehen und zu nutzen. Es wurde gezeigt, dass für die Fernerkundung von Pflanzenfunktionen die Kopplung von Kronendachreflektion und Pflanzenfunktionen durch RTM mehrere Potentiale bietet: Erstens, ermöglichen RTM die Kartierung von Pflanzenmerkmalen. Innerhalb einer Fallstudie wurde gezeigt, dass eine Inversion von RTM mit hyperspektralen Daten eine Kartierung von optischen Merkmalen erlaubt, für die keine Felddaten zur Modellkalibrierung benötigt werden. Die kartierten Merkmale zeigten eine hohe Übereinstimmung mit Merkmalsausprägungen aus unabhängigen Datenbanken und spiegelten die im Feld gemessenen ökologischen Gradienten wider. Dies deutet darauf hin, dass RTM-Inversion als äußerst übertragbare Methode betrachtet werden kann, um räumliche Karten von Pflanzenmerkmalen zu erstellen, die als Proxies für Pflanzenfunktionen dienen können. Allerdings erfordert die Implementierung von RTM Inversionen fundierte Kenntnisse über die Prinzipien der Strahlentransfermodellierung und der zu untersuchenden Vegetationscharakteristiken. Zweitens, ermöglichen RTM die Untersuchung von Zusammenhängen zwischen Pflanzenfunktion und der Kronendachreflektion. In der vorliegenden Thesis wurden simulierte Kronendachspektren aus einem RTM verwendet, um den Beitrag der optischen Merkmale zu den spektralen Unterschieden zwischen Pflanzenfunktionstypen zu erfassen. Die Ergebnisse zeigten die dominanten Pflanzenmerkmale und die entsprechenden spektralen Charakteristiken die für eine fernerkundliche Unterscheidung der Pflanzenfunktion von großer Relevanz sind. Darüber hinaus wurde gezeigt, dass RTM-basierte Simulationen Einschränkungen von Fallstudien kompensieren und Kenntnisse über die Zusammenhänge von Pflanzenfunktionen, Pflanzeneigenschaften und Kronendachtreflektion erweitern können. Diese Kenntnisse bilden die Grundlage für die Entwicklung und Verbesserung von Sensoren und Algorithmen zur Fernerkundung von Pflanzenfunktionen. Drittens, erweitern RTM und die darin enthaltenen optischen Merkmale unsere Möglichkeiten Unterschiede in der Pflanzenfunktion zu verstehen und zu quantifizieren. Mit Hilfe von in-situ gemessenen Merkmalsausprägungen konnte gezeigt werden, dass die in RTM enthaltenen optischen Merkmale kausal mit primären Pflanzenfunktionen zusammenhängen. Dies wiederum bedeutet, dass die Reflexion des Kronendachs unmittelbar mit den primären Funktionen der Pflanze zusammenhängt (‘Reflektion folgt Funktion’). Darüber hinaus wurde festgestellt, dass optische Merkmale vergleichbare oder sogar höhere Korrelationen mit den verwendeten pflanzlichen Funktionsgradienten aufweisen als die in der Pflanzenökologie üblich verwendeten Merkmale. Entsprechend bieten RTM sowohl eine alternative Perspektive als auch ein Set von Pflanzenmerkmalen mit denen Unterschiede der Pflanzenfunktion charakterisiert und quantifiziert werden können. Diese Merkmale können somit als wertvolle Ergänzung oder Alternative zu den in der Pflanzenökologie üblichen Merkmalen dienen. Zusammengefasst zeigt diese Thesis, dass RTM unsere Möglichkeiten erweiterten können die funktionelle Vielfalt der globalen Vegetationsbedeckung weiter zu verstehen und zu erfassen und führt zukunftsrelevante Forschungspotentiale auf
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
