30 research outputs found

    The Rise of Metallurgy in Eurasia

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    "The Rise of Metallurgy in Eurasia is a landmark study in the origins of metallurgy. The project aimed to trace the invention and innovation of metallurgy in the Balkans. It combined targeted excavations and surveys with extensive scientific analyses at two Neolithic-Chalcolithic copper production and consumption sites, Belovode and Pločnik, in Serbia. At Belovode, the project revealed chronologically and contextually secure evidence for copper smelting in the 49th century BC. This confirms the earlier interpretation of c. 7000-year-old metallurgy at the site, making it the earliest record of fully developed metallurgical activity in the world. However, far from being a rare and elite practice, metallurgy at both Belovode and Pločnik is demonstrated to have been a common and communal craft activity. This monograph reviews the pre-existing scholarship on early metallurgy in the Balkans. It subsequently presents detailed results from the excavations, surveys and scientific analyses conducted at Belovode and Pločnik. These are followed by new and up-to-date regional syntheses by leading specialists on the Neolithic-Chalcolithic material culture, technologies, settlement and subsistence practices in the Central Balkans. Finally, the monograph places the project results in the context of major debates surrounding early metallurgy in Eurasia before proposing a new agenda for global early metallurgy studies.

    Forests for a Better Future Sustainability, Innovation and Interdisciplinarity

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    This book highlights the role of research in innovation and sustainability in the forest sector. The contributions included fall within the broad thematic areas of forest science and cover crucial topics such as biocontrol, forest fire risk, harvesting and logging practices, quantitative and qualitative assessments of forest products, urban forests, and wood treatments—topics that have also been addressed from an interdisciplinary perspective. The contributions also have practical applications, as they deal with the ecological and economic importance of forests and new technologies for the conservation, monitoring, and improvement of services and forest value

    Mapping and Monitoring Forest Cover

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    This book is a compilation of six papers that provide some valuable information about mapping and monitoring forest cover using remotely sensed imagery. Examples include mapping large areas of forest, evaluating forest change over time, combining remotely sensed imagery with ground inventory information, and mapping forest characteristics from very high spatial resolution data. Together, these results demonstrate effective techniques for effectively learning more about our very important forest resources

    Derivation of forest inventory parameters from high-resolution satellite imagery for the Thunkel area, Northern Mongolia. A comparative study on various satellite sensors and data analysis techniques.

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    With the demise of the Soviet Union and the transition to a market economy starting in the 1990s, Mongolia has been experiencing dramatic changes resulting in social and economic disparities and an increasing strain on its natural resources. The situation is exacerbated by a changing climate, the erosion of forestry related administrative structures, and a lack of law enforcement activities. Mongolia’s forests have been afflicted with a dramatic increase in degradation due to human and natural impacts such as overexploitation and wildfire occurrences. In addition, forest management practices are far from being sustainable. In order to provide useful information on how to viably and effectively utilise the forest resources in the future, the gathering and analysis of forest related data is pivotal. Although a National Forest Inventory was conducted in 2016, very little reliable and scientifically substantiated information exists related to a regional or even local level. This lack of detailed information warranted a study performed in the Thunkel taiga area in 2017 in cooperation with the GIZ. In this context, we hypothesise that (i) tree species and composition can be identified utilising the aerial imagery, (ii) tree height can be extracted from the resulting canopy height model with accuracies commensurate with field survey measurements, and (iii) high-resolution satellite imagery is suitable for the extraction of tree species, the number of trees, and the upscaling of timber volume and basal area based on the spectral properties. The outcomes of this study illustrate quite clearly the potential of employing UAV imagery for tree height extraction (R2 of 0.9) as well as for species and crown diameter determination. However, in a few instances, the visual interpretation of the aerial photographs were determined to be superior to the computer-aided automatic extraction of forest attributes. In addition, imagery from various satellite sensors (e.g. Sentinel-2, RapidEye, WorldView-2) proved to be excellently suited for the delineation of burned areas and the assessment of tree vigour. Furthermore, recently developed sophisticated classifying approaches such as Support Vector Machines and Random Forest appear to be tailored for tree species discrimination (Overall Accuracy of 89%). Object-based classification approaches convey the impression to be highly suitable for very high-resolution imagery, however, at medium scale, pixel-based classifiers outperformed the former. It is also suggested that high radiometric resolution bears the potential to easily compensate for the lack of spatial detectability in the imagery. Quite surprising was the occurrence of dark taiga species in the riparian areas being beyond their natural habitat range. The presented results matrix and the interpretation key have been devised as a decision tool and/or a vademecum for practitioners. In consideration of future projects and to facilitate the improvement of the forest inventory database, the establishment of permanent sampling plots in the Mongolian taigas is strongly advised.2021-06-0

    Climate-Smart Forestry in Mountain Regions

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    This open access book offers a cross-sectoral reference for both managers and scientists interested in climate-smart forestry, focusing on mountain regions. It provides a comprehensive analysis on forest issues, facilitating the implementation of climate objectives. This book includes structured summaries of each chapter. Funded by the EU’s Horizon 2020 programme, CLIMO has brought together scientists and experts in continental and regional focus assessments through a cross-sectoral approach, facilitating the implementation of climate objectives. CLIMO has provided scientific analysis on issues including criteria and indicators, growth dynamics, management prescriptions, long-term perspectives, monitoring technologies, economic impacts, and governance tools

    Quantitative Techniques in Participatory Forest Management

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    Forest management has evolved from a mercantilist view to a multi-functional one that integrates economic, social, and ecological aspects. However, the issue of sustainability is not yet resolved. Quantitative Techniques in Participatory Forest Management brings together global research in three areas of application: inventory of the forest variables that determine the main environmental indices, description and design of new environmental indices, and the application of sustainability indices for regional implementations. All these quantitative techniques create the basis for the development of scientific methodologies of participatory sustainable forest management

    Remote sensing technology applications in forestry and REDD+

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    Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion

    Puistute takseertunnuste hindamine aerolidari mÔÔtmisandmete pÔhjal hemiboreaalsetes metsades

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    A Thesis for applying for the degree of Doctor of Philosophy in Forestry.Forest management and planning requires up-to-date data, which commonly is acquired using field experts and ground measurements. Nowadays, more and more of data about forest stands is measured using remotely sensing methods. Most common methods include aerial photography and laser scanning from airplanes, also spectral measurements from satellites or even drone images and applications. This doctoral thesis focuses on developing applications and methods for utilising the airborne laser scanning (ALS) data that is freely available for the whole Estonia. The ALS measurements are carried out by the Estonian Land Board on a routine basis twice a year – in spring and summer. The first variable that was studied in this thesis was forest height. Based on the thesis, the most reliable method for forest height assessment was using the ALS point-cloud 80th height percentile (HP80). The small circular plot (radius of 15
30 m) and stand based studies showed high correlations with the field-measured forest heights and with great confidence it can be said, that ALS-based forest height estimations are close or even with higher accuracy, than field inspected. The second studied variable was standing wood volume. The ALS-based methods and models that were developed throughout this thesis used the idea, that standing wood volume is based on forest height and density. For this the HP80 and a threshold-based point count ratio was used (canopy cover - CC). ALS-based CC (CCALS) estimates were studied and compared with digital hemispherical photo based measurements. The results showed similar errors as were shown in other similar studies, with around 10-15% root mean square error (RMSE). The strongest correlation was shown using all echoes above a 1.3 metre threshold. Combining the CCALS and HP80 showed standing wood volume estimates with a similar error as we would receive from field measurements (<20%). The freely available multitemporal ALS data showed promising results for forest height growth monitoring and detecting small-scale disturbances. CCALS was shown to have strong predictive value, when compared with a four year difference in thinned and unthinned stands. The nation-wide ALS data can also be combined with forest height predictions from satellites, providing a faster update compared to the ALS data. Promising results were shown using the interferometric synthetic aperture radar (InSAR). Stand species maps generated using self-learning algorithms and satellite based spectral data can be used for developing species specific models of standing wood volume prediction. By combining these different datasets we can construct a nation-wide forest resource to help make better decisions for forest management and targeting fieldwork.Metsades majandamisotsuste langetamiseks ja metsamajanduslike tööde planeerimiseks on metsaomanikel vaja andmeid. HarjumuspĂ€raselt on andmete kogumiseks tehtud metsas maapealseid mÔÔtmisi. Viimastel aastakĂŒmnetel on metsade inventeerimiseks ĂŒha enam aga kasutatud mittekontaktseid mÔÔtmisi - lennukitelt tehtavad aerofotosid, laserskaneerimist, satelliitidelt tehtavaid kiirgusmÔÔtmisi vĂ”i viimastel aastatel ka droonidelt tehtud pilte. Antud doktoritöö on vĂ”tnud fookusesse aerolaserskaneerimise (ALS) andmete pĂ”hjal Eesti metsadesse sobilike rakenduste vĂ€ljatöötamise. ALS mÔÔtmisi teeb Eesti Maa-amet rutiinsete lendude kĂ€igus kaks korda aastas, nii kevadel kui ka suvel. Aastast 2008 alustatud mÔÔtmiste tulemusel on Eesti ĂŒks vĂ€heseid riike maailmas, kus on vabalt kasutada mitmekordselt kogu riiki kattev ALS andmestik. Doktoritöö tulemusel töötati vĂ€lja metsa kĂ”rguse hindamiseks sobilikud meetodid, kasutades selleks punktipilvede kĂ”rgusprotsentiile. Tugevamaid seoseid metsas proovitĂŒkkidel mÔÔdetud kĂ”rgustega nĂ€itas punktipilve 80-protsentiil (HP80) ja uuringute pĂ”hjal vĂ”ib vĂ€ita, et metsa kĂ”rguse mÀÀramine suvistelt aerolidari andmetelt on ligilĂ€hedane tĂ€psustele, mida saadakse metsas kohapeal mÔÔtes. Teine oluline tunnus, mida metsade majandamise planeerimisel silmas peetakse, on kasvava metsa tagavara. Teadustöö pĂ”hjal töötati vĂ€lja mudelite kujud ja metoodika, mille abil prognoositud tagavara oli sarnase veapiiriga, mis on lubatud metsas hinnanguid tegevatele taksaatoritele (<20%). VĂ€ljatöötatud ALS-pĂ”hine mudeli kuju jĂ€rgib loogikat, et metsa tagavara on otseselt seotud mÔÔdetud kĂ”rguse ja metsa tihedusega. Tihenduse hindamiseks aerolidari andmetelt kasutatakse nivoopĂ”hist punktide suhtearvu ehk nn katvushinnangut (CCALS). Katvushinnangu tĂ€psuse valideerimiseks ja tihedas metsas sobiva prognoosimeetodi vĂ€ljatöötamiseks tehti vĂ€limÔÔtmisi kasutades poolsfÀÀrikaameraid. PoolsfÀÀripiltide pĂ”hjal tehtud valideerimise tulemused andsid sarnaseid veahinnanguid, mida on ka varasemates teadusuuringutes esitletud (RMSE = 10
15%). Kahe sarnasest fenoloogilisest perioodist ALS andmestiku lahutamisel uuriti ka muutuste tuvastamise vĂ”imalikkust. Uuringud andsid paljulubavaid tulemusi metsade kĂ”rguskasvu hindamiseks ja CCALS osutus ka oluliseks tunnuseks vĂ€iksemate hĂ€iringute, nagu nĂ€iteks harvendusraie, tuvastamiseks. Kogu riiki katva ALS andmestiku kombineerimisel erinevate satelliitandmetega vĂ”i nĂ€iteks spektraalsete mÔÔtmiste pĂ”hjal tehtud puistu liigiliste koosseisu kaartidega on vĂ”imalik antud töös vĂ€lja pakutud meetodite abil anda igal aastal kogu Eesti metsaressursside ĂŒlevaade. Samuti on vĂ”imalik koostada vaid kaugseirevahendeid ja proovitĂŒkkidel lĂ€hendatud mudeleid kasutades eraldiste pĂ”hised takseerkirjeldused, mida siis taksaatorid saavad nĂ€iteks kasutada oma vĂ€litööde kavandamisel.  Publication of this thesis is supported by the Estonian University of Life Sciences

    LIDAR based semi-automatic pattern recognition within an archaeological landscape

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    LIDAR-Daten bieten einen neuartigen Ansatz zur Lokalisierung und Überwachung des kulturellen Erbes in der Landschaft, insbesondere in schwierig zu erreichenden Gebieten, wie im Wald, im unwegsamen GelĂ€nde oder in sehr abgelegenen Gebieten. Die manuelle Lokalisation und Kartierung von archĂ€ologischen Informationen einer Kulturlandschaft ist in der herkömmlichen Herangehensweise eine sehr zeitaufwĂ€ndige Aufgabe des Fundstellenmanagements (Cultural Heritage Management). Um die Möglichkeiten in der Erkennung und bei der Verwaltung des kulturellem Erbes zu verbessern und zu ergĂ€nzen, können computergestĂŒtzte Verfahren einige neue LösungsansĂ€tze bieten, die darĂŒber hinaus sogar die Identifizierung von fĂŒr das menschliche Auge bei visueller Sichtung nicht erkennbaren Details ermöglichen. Aus archĂ€ologischer Sicht ist die vorliegende Dissertation dadurch motiviert, dass sie LIDAR-GelĂ€ndemodelle mit archĂ€ologischen Befunden durch automatisierte und semiautomatisierte Methoden zur Identifizierung weiterer archĂ€ologischer Muster zu Bodendenkmalen als digitale „LIDAR-Landschaft“ bewertet. Dabei wird auf möglichst einfache und freie verfĂŒgbare algorithmische AnsĂ€tze (Open Source) aus der Bildmustererkennung und Computer Vision zur Segmentierung und Klassifizierung der LIDAR-Landschaften zur großflĂ€chigen Erkennung archĂ€ologischer DenkmĂ€ler zurĂŒckgegriffen. Die Dissertation gibt dabei einen umfassenden Überblick ĂŒber die archĂ€ologische Nutzung und das Potential von LIDAR-Daten und definiert anhand qualitativer und quantitativer AnsĂ€tze den Entwicklungsstand der semiautomatisierten Erkennung archĂ€ologischer Strukturen im Rahmen archĂ€ologischer Prospektion und Fernerkundungen. DarĂŒber hinaus erlĂ€utert sie Best Practice-Beispiele und den einhergehenden aktuellen Forschungsstand. Und sie veranschaulicht die QualitĂ€t der Erkennung von BodendenkmĂ€lern durch die semiautomatisierte Segmentierung und Klassifizierung visualisierter LIDAR-Daten. Letztlich identifiziert sie das Feld fĂŒr weitere Anwendungen, wobei durch eigene, algorithmische Template Matching-Verfahren großflĂ€chige Untersuchungen zum kulturellen Erbe ermöglicht werden. ResĂŒmierend vergleicht sie die analoge und computergestĂŒtzte Bildmustererkennung zu Bodendenkmalen, und diskutiert abschließend das weitere Potential LIDAR-basierter Mustererkennung in archĂ€ologischen Kulturlandschaften

    Dipterocarps protected by Jering local wisdom in Jering Menduyung Nature Recreational Park, Bangka Island, Indonesia

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    Apart of the oil palm plantation expansion, the Jering Menduyung Nature Recreational Park has relatively diverse plants. The 3,538 ha park is located at the north west of Bangka Island, Indonesia. The minimum species-area curve was 0.82 ha which is just below Dalil conservation forest that is 1.2 ha, but it is much higher than measurements of several secondary forests in the Island that are 0.2 ha. The plot is inhabited by more than 50 plant species. Of 22 tree species, there are 40 individual poles with the average diameter of 15.3 cm, and 64 individual trees with the average diameter of 48.9 cm. The density of Dipterocarpus grandiflorus (Blanco) Blanco or kruing, is 20.7 individual/ha with the diameter ranges of 12.1 – 212.7 cm or with the average diameter of 69.0 cm. The relatively intact park is supported by the local wisdom of Jering tribe, one of indigenous tribes in the island. People has regulated in cutting trees especially in the cape. The conservation agency designates the park as one of the kruing propagules sources in the province. The growing oil palm plantation and the less adoption of local wisdom among the youth is a challenge to forest conservation in the province where tin mining activities have been the economic driver for decades. More socialization from the conservation agency and the involvement of university students in raising environmental awareness is important to be done
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