Zweitveröffentlichung
Refine
Year of publication
Document Type
- Article (165)
- Conference Proceeding (28)
- Other (12)
- Report (4)
- Book (3)
- Working Paper (3)
- Part of a Book (2)
- Contribution to a Periodical (2)
- Postprint (2)
- Part of Periodical (1)
Has Fulltext
- yes (223)
Is part of the Bibliography
- yes (223)
Keywords
- TMT (4)
- climate change (4)
- sustainability (4)
- Biodiversity (3)
- Central Asia (3)
- UAV (3)
- agroforestry (3)
- biodiversity (3)
- ecosystem services (3)
- sustainable development (3)
Institute
- Fachbereich Wald und Umwelt (86)
- Fachbereich Landschaftsnutzung und Naturschutz (58)
- Fachbereich Holzingenieurwesen (29)
- Centre for Econics and Ecosystem Management (16)
- Forschungszentrum [Nachhaltigkeit - Transformation - Transfer] (14)
- Biosphere Reserves Institute (13)
- Zentrale Hochschuleinrichtungen (8)
- Fachbereich Nachhaltige Wirtschaft (4)
- ZENAT (2)
- Nachhaltiges Tourismusmanagement M.A. (1)
To cope with the challenges in forest management that are contemporarily caused by climate change, data on current chemical and physical soil properties are more and more necessary. For this purpose, we present a further amalgam of depth functions and SCORPAN modelling to provide data at arbitrary depth layers. In this concept, regionalisation is split up into the modelling of plot totals and the estimation of vertical distributions. The intended benefits by splitting up are: consistency between estimates on plot level and depth layer level, avoidance of artificial depth gradients, straightforward interpretation of covariates in the sense of pedogenetic processes, and circumnavigation of the propagation of uncertainties associated with separation between horizons during field sampling. The methodology was tailored to the circumstances within the north-eastern lowlands and the utilisation of current inventory data of the National Forest Soil Inventory (NFSI) in Brandenburg (Germany). Using the regionalisation of soil organic carbon (SOC) as an example, the application is demonstrated and discussed in detail. The depth to groundwater table and terrain parameters related to the catchment area were the main factors in SOC storage. The use of kriging did not improve the model performance. The relative depth gradients of SOC were especially distinguished by tree species composition and stand age. We suppose that interesting fields of application may be found in scenario-based modelling of SOC and when SOC serves as a basis for hydrological modelling.
An important component of the National Forest Soils Inventory (NFSI) is the investigation of inorganic and organic pollutants. Forests are able to filter out large quantities of these substances from the atmosphere and incorporate them into the soil for a long time. The aim of this study was the integrative evaluation of organic and inorganic pollutant concentrations in forest soils in the state of Brandenburg, Germany. With the help of principle component analysis, the pollutant concentrations can essentially be explained by three significant environmental components, which explain 76% of the total variance of all pollutants examined within the scope of the NFSI. The first component characterizes the extent of the atmospheric pollution caused by flue gases and fly ash from lignite combustion in the 1970s and 1980s and is mainly charged by the organic pollutants HCB and PAH, and the elements arsenic and chromium. This component shows positive relation to both spatially interpolated calcium-deposition data from the 1980s (as an indicator for the dust emission from coal combustion) and crown defoliation data of pine stands from the forest condition survey in the early 1990s. The depositions of zinc and cadmium from industrial sources, vehicle traffic and the use of fertilizers in agriculture mainly characterize the second principle component. The use of the pesticides DDT and lindane in the early 1980s and the associated pollutants input into the forest soils are expressed by the third component. In expanding the term archiving function of soils, the results illustrate their particular importance for the long-term archiving of anthropogenic inputs and the associated potential stress factors for forests.
Calls for a “sustainable bioeconomy” have recently begun to proliferate in academic and political circles as an answer to global challenges such as the rapidly increasing world population and changing environmental conditions due to climate change. To build economies that rely on various sources of biomass rather than on fossil-based resources, bioeconomy policies highlight a need to explore ways in which productivity in agriculture can be increased. While the focus on productivity growth has largely been inspired by technology optimism and modernisation thinking, the local knowledge of farmers and other rural stakeholders – as a means of contributing to socially and ecologically more sustainable bioeconomy pathways – has frequently been sidelined. This perspective article proposes and discusses a participatory approach to strategy formulation and evaluation in agricultural transformation and bioeconomy development that is based on the methodological toolbox MARISCO (Adaptive MAnagement of vulnerability and RISk at COnservation sites). By offering a means of developing a comprehensive knowledge map, bringing together both insights and perspectives from diverse local stakeholders, this approach enables a systemic evaluation of the social and ecological effects of intervention strategies on the ground. The article outlines the benefits – and challenges – of such a systemic and participatory approach and briefly sketches how the results can be utilised in more sustainable governance processes in the development of bioeconomy strategies. We conclude that our adapted MARISCO methodology offers a viable tool to make more visible the perspectives and knowledge of biomass producers for policymakers and to contribute to a much-needed discursive shift in bioeconomy debates towards more holistic and inclusive perspectives.
The COVID-19 pandemic has jolted societies out of normality, possibly creating new conditions for sustainability transformations. What does this mean for sustainability research? Because of the scope of the crisis, researchers have been heavily involved: not only have they had to speed up the pace of scientific production to provide urgently needed COVID-19 knowledge, but they have also been affected citizens. For sustainability science, this calls for an experience-based reflection on the positionality and orientation of research aiming to support sustainability transformations. Twenty sustainability researchers discussed their sustainability research on COVID-19 in three workshops based on the following questions: How does the pandemic—and the measures taken to deal with it—affect sustainable development? What can we learn from the pandemic from the perspective of societal transformation? The present discussion paper emerged from this multidisciplinary exchange among sustainability researchers, considering five topics: impacts of the COVID-19 crisis on sustainability transformations; learning for sustainability transformations; the role of solidarity; governance and political steering; and the role of science in society. Our discussions led to a meta-level reflection on what sustainability research can learn from research on COVID-19 regarding topics and disciplinary angles, time dimensions, the role of researchers, and how adequate preparation for both crises and long-term transformations requires interdisciplinary interaction.
The charcoal stock in a forest company is controlled based on the theoretical capacity of the masonry ovens (input) and shipped trucks (output). During the year, the company must monitor the stock for the purposes of accountability reports. This study proposes a more efficient and equally precise survey method that overcomes the challenges of the common monitoring system in Brazil. During this study, a new monitoring method based on digital stereoscopy from UAV images was developed, implemented and evaluated. The results were compared with a traditional topographic survey. A masonry oven's complex containing eight charcoal heaps was flown and surveyed using a multi-engine UAV, with an integrated Global Navigation Satellite System (GNSS) and RTK equipment. Two stereoscopic processing methods were applied: (1) very low quality and (2) high quality to image alignment, reconstruction of the dense cloud, face count and in three-dimensional mesh creation. Low quality products showed geometric deformities when compared to high quality, but resulted in similar estimation to the topographic survey. The results indicated that the charcoal heaps' volume estimation using UAV derived orthomosaics can replace the conventional method of GNSS RTK surveys with considerable gains in stockpile volume accuracy, inventory frequency, and safety. In the case of high accuracy parameterization, improvements in geometric precision and accuracy are also produced.
High-resolution recording and forecasting of peatlands under forests in northeast Brandenburg (Germany) using remotely sensed data (Radar ALOS-PALSAR and Sentinel 1). Peatlands are important in terms of CO2 storage, water cycling, biochemical cycles, biodiversity, and ecosystem services. Peatlands are constantly altered and damaged due to agriculture and drainage. Thus it is crucial to manage them sustainably. How? First step – locating and quantifying them with geospatial data and remote sensing methods since locating and collecting data in field is highly expensive and arduous in terms of labour and time. Our MAIN RESEARCH QUESTION therefore is: Is it possible to generate a method to record the location of peatlands under forests at high resolution using RS?.
360° virtual forest tours (VFTs), created by state-of-the-art virtual reality technology, contribute to the progression of academic e-learning and forest management. The article proposes a conceptual framework for 360° VFT production and use to supplement field courses. Reflective insights into the authors’ own learning process in the production of 360° VFTs, and a consideration of the general challenges of the medium are also presented. To conclude, the article summarizes the advantages of 360° VFTs for forestry education in an academic context.
Application of Land Surface Temperature Analysis in Urban Green Spaces: Case Studies from South Asia
(2021)
This paper demonstrates the use of remote sensing in planning urban green spaces (UGSs). UGSs emerged as a popular solution to combat the effects of Urban Heat Island, especially in tropical cities. UGS projects often need to identify priority implementation areas due to limited funding for UGSs. This study includes two Asian cities, namely Phnom Penh (Cambodia) and Chittagong (Bangladesh). It is not comparative, but it has identified priority administrative areas for future UGSs in both cities. We used Landsat 8 data and the remote sensing technique Land Surface Temperature (LST) analysis using radiance, temperature brightness and emissivity. LST data were then intersected with the administrative boundaries of the study areas. The identification of priority administrative areas for UGS considered both the area coverage and the percentage of coverage in terms of maximum LST within the administrative units’ boundaries. The result found 8 and 10 administrative units to be hotspots for UGSs, for Phnom Penh and Chittagong respectively. The proposed method will be useful to both government and non-government organizations alike, especially in tropical countries.
The destruction of habitats has not only reduced biological diversity but also affected essential ecosystem services of the Central European cultural landscape. Therefore, in the further development of the cultural landscape and in the management of natural resources, special importance must be attached to the habitat demands of species and the preservation of ecosystem services. The study of ecosystem services has extended its influence into spatial planning and landscape ecology, the integration of which can offer an opportunity to enhance the saliency, credibility, and legitimacy of landscape ecology in spatial planning issues. Objective: This paper proposes a methodology to detect red deer habitats for e.g. huntable game. The model is established on remote sensing based value-added information products, the derived landscape structure information and the use of spatially and temporally imprecise in-situ data (e.g. available hunting statistics). In order to realize this, four statistical model approaches were developed and their predictive performance assessed. Methods: Altogether, our results indicate that based on the data mentioned above, modeling of habitats is possible using a coherent statistical model approach. All four models showed an overall classification of > 60% and in the best case 71,4%. The models based on logistic regression using preference data derived from 5-year hunting statistics, which has been interpreted as habitat suitability. The landscape metrics (LSM) will be calculated on the basis of the Global Forest Change dataset (HANSEN et al. 2013b ). The interpolation of landcover data into landscape-level was made with the software FRAGSTAT and the moving window approach. Correlation analysis is used to identify relevant LSM serving as inputs; logistic regression was used to derive a final binary classifier for habitat suitability values. Three model variations with different sets of LSM are tested using the unstandardized regression coefficient. Results lead to an insight of the effect of each LSM but not on the strength of the effect. Furthermore, the predicted outcome is rather difficult to interpret as different units and scales for each LSM are used. Hence, we calculated the fourth model using the standardized regression coefficient. It harmonized the measurement units of the LSM and thus allowed a better comparison, interpretation, and evaluation.Conclusion: Our research reveals that applying a statistical model using coarse data is effective to identify potential red deer habitats in a significant qualitative manner. The presented approach can be analogously applied to other mammals if the relevant structural requirements and empirical habitat suitability data (e.g. home range, biotopes, and food resources) are known. The habitat preferences of red deer are best described by LSM concerning area-relation and wildlifeedge relations. Most important are edges between meadows, pastures or agricultural field and forest, as well as short paths between those elements for food resources. A large proportion of forest is important for species survival and positively influences the occurrence of red deer. Outcomes help to understand species habitat relation and on which scale wildlife perceives the landscape. In addition, they support the practical habitat management and thus the overall species diversity.