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  1. Article ; Online: Assessing Error Correlations in Remote Sensing-Based Estimates of Forest Attributes for Improved Composite Estimation

    Sarah Ehlers / Svetlana Saarela / Nils Lindgren / Eva Lindberg / Mattias Nyström / Henrik J. Persson / Håkan Olsson / Göran Ståhl

    Remote Sensing, Vol 10, Iss 5, p

    2018  Volume 667

    Abstract: Today, non-expensive remote sensing (RS) data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as ... ...

    Abstract Today, non-expensive remote sensing (RS) data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.
    Keywords airborne LiDAR ; Composite estimators ; forest inventory ; SPOT-5 HRG ; TanDEM-X ; Science ; Q
    Subject code 310 ; 333
    Language English
    Publishing date 2018-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Contributions to the biodiversity of Vietnam – Results of VIETBIO inventory work and field training in Cuc Phuong National Park

    Virginia Duwe / Lien Vu / Thomas von Rintelen / Eckhard von Raab-Straube / Stefan Schmidt / Sinh Nguyen / Thong Vu / Tu Do / Truong Luu / Vuong Truong / Vanessa Di Vincenzo / Olga Schmidt / Falko Glöckler / Regine Jahn / Robert Lücking / Katharina von Oheimb / Parm von Oheimb / Sandra Heinze / Nelida Abarca /
    Sarah Bollendorff / Thomas Borsch / Eliana Buenaventura / Huong Dang / Thuy Dinh / Hai Do / Sarah Ehlers / Jörg Freyhof / Sofía Hayden / Peter Hein / Tuan Hoang / Duc Hoang / Son Hoang / Harald Kürschner / Wolf-Henning Kusber / Han Le / Trang Le / Mattes Linde / Wolfram Mey / Hiep Nguyen / Man Nguyen / Minh Nguyen / Dat Nguyen / Tu Nguyen / Vu Nguyen / Michael Ohl / Gerald Parolly / Tan Pham / Phu Pham / Katharina Rabe

    Biodiversity Data Journal, Vol 10, Iss , Pp 1-

    2022  Volume 28

    Abstract: VIETBIO [Innovative approaches to biodiversity discovery and characterisation in Vietnam] is a bilateral German-Vietnamese research and capacity building project focusing on the development and transfer of new methods and technology towards an integrated ...

    Abstract VIETBIO [Innovative approaches to biodiversity discovery and characterisation in Vietnam] is a bilateral German-Vietnamese research and capacity building project focusing on the development and transfer of new methods and technology towards an integrated biodiversity discovery and monitoring system for Vietnam. Dedicated field training and testing of innovative methodologies were undertaken in Cuc Phuong National Park as part and with support of the project, which led to the new biodiversity data and records made available in this article collection.VIETBIO is a collaboration between the Museum für Naturkunde Berlin – Leibniz Institute for Evolution and Biodiversity Science (MfN), the Botanic Garden and Botanical Museum, Freie Universität Berlin (BGBM) and the Vietnam National Museum of Nature (VNMN), the Institute of Ecology and Biological Resources (IEBR), the Southern Institute of Ecology (SIE), as well as the Institute of Tropical Biology (ITB); all Vietnamese institutions belong to the Vietnam Academy of Science and Technology (VAST).The article collection "VIETBIO" (https://doi.org/10.3897/bdj.coll.63) reports original results of recent biodiversity recording and survey work undertaken in Cuc Phuong National Park, northern Vietnam, under the framework of the VIETBIO project. The collection consist of this “main” cover paper – characterising the study area, the general project approaches and activities, while also giving an extensive overview on previous studies from this area – followed by individual papers for higher taxa as studied during the project. The main purpose is to make primary biodiversity records openly available, including several new and interesting findings for this biodiversity-rich conservation area. All individual data papers with their respective primary records are expected to provide useful baselines for further taxonomic, phylogenetic, ecological and conservation-related studies on the respective taxa and, thus, will be maintained as separate datasets, including separate GUIDs also ...
    Keywords VIETBIO ; Vietnam ; biodiversity discovery ; species ; Biology (General) ; QH301-705.5
    Subject code 333
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Pensoft Publishers
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Data Assimilation in Forest Inventory

    Mattias Nyström / Nils Lindgren / Jörgen Wallerman / Anton Grafström / Anders Muszta / Kenneth Nyström / Jonas Bohlin / Erik Willén / Johan E. S. Fransson / Sarah Ehlers / Håkan Olsson / Göran Ståhl

    Forests, Vol 6, Iss 12, Pp 4540-

    First Empirical Results

    2015  Volume 4557

    Abstract: Data assimilation techniques were used to estimate forest stand data in 2011 by sequentially combining remote sensing based estimates of forest variables with predictions from growth models. Estimates of stand data, based on canopy height models obtained ...

    Abstract Data assimilation techniques were used to estimate forest stand data in 2011 by sequentially combining remote sensing based estimates of forest variables with predictions from growth models. Estimates of stand data, based on canopy height models obtained from image matching of digital aerial images at six different time-points between 2003 and 2011, served as input to the data assimilation. The assimilation routines were built on the extended Kalman filter. The study was conducted in hemi-boreal forest at the Remningstorp test site in southern Sweden (lat. 13°37′ N; long. 58°28′ E). The assimilation results were compared with two other methods used in practice for estimation of forest variables: the first was to use only the most recent estimate obtained from remotely sensed data (2011) and the second was to forecast the first estimate (2003) to the endpoint (2011). All three approaches were validated using nine 40 m radius validation plots, which were carefully measured in the field. The results showed that the data assimilation approach provided better results than the two alternative methods. Data assimilation of remote sensing time series has been used previously for calibrating forest ecosystem models, but, to our knowledge, this is the first study with real data where data assimilation has been used for estimating forest inventory data. The study constitutes a starting point for the development of a framework useful for sequentially utilizing all types of remote sensing data in order to provide precise and up-to-date estimates of forest stand parameters.
    Keywords data assimilation ; extended Kalman filter ; forestry ; image matching ; photogrammetric point clouds ; digital aerial images ; forest inventory ; Plant ecology ; QK900-989
    Subject code 333
    Language English
    Publishing date 2015-12-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

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