Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2025
Sammendrag
Urban green structures (UGS) play important roles in enhancing urban ecosystems by providing benefits such as mitigating the urban heat island effect, improving air quality, supporting biodiversity, and aiding in stormwater management. Accurately mapping UGS is important for sustainable urban planning and management. Traditional methods of mapping such as manual mapping, aerial photography interpretation and pixel-based classification have limitations in terms of coverage, accuracy, and efficiency. Object-based image analysis (OBIA) has gained prominence due to its ability to incorporate both spectral and spatial information making it particularly effective for classification of high-resolution satellite data. This paper reviews the application of OBIA on satellite images for UGS mapping, focusing on various data sources, popular segmentation methods, and classification techniques, highlighting their respective advantages and limitations. Key segmentation methodologies discussed include multi-resolution segmentation and watershed segmentation. For classification, the review covers machine learning techniques such as random forests, support vector machines, and convolutional neural networks, among others. Several case studies highlight the successful implementation of OBIA in diverse urban environments by demonstrating improvements in classification accuracy and detail. The review also addresses the challenges associated with OBIA, such as dealing with heterogenous urban landscapes, data sources and with OBIA methods itself. Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. By providing a detailed analysis of the current state-of-the-art in object-based UGS mapping, this review aims to guide future research and practical applications in UGS management.
Forfattere
Céline ReboursSammendrag
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Anna Birgitte MilfordSammendrag
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Nina TrandemSammendrag
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Sammendrag
Urban agriculture is often considered a tool to increase the economic, social and environmental sustainability of cities and city food systems. However, sustainability is difficult to measure, resulting in debate about how sustainable urban agriculture truly is. There is therefore a lack of incentive to promote urban agriculture or protect existing initiatives that are threatened by development pressure on urban land. Monitoring the sustainability impact of urban agriculture could provide evidence and enable politicians and decision makers to make informed decisions about whether and where to prioritise different forms of urban agriculture above competing interests. We used case examples from five European cities to identify the challenges involved in monitoring urban agriculture, from selecting indicators and gathering data, to using the results. We found large differences in approach in terms of what topics to monitor and who was responsible, who gathered the data and when, what data was recorded and how they were stored, and how findings were disseminated or published. Based on these experiences, we recommend stronger involvement of existing interest groups and educational institutions in monitoring urban agriculture, and promotion of convenient tools for data collection by citizen science and for long-term data storage.
Sammendrag
The timing of migration is fundamental for species exploiting seasonally variable environments. For ungulates, earlier spring migration is expected with earlier vegetation green-up. However, other drivers, such as access to agricultural farmland and variation in local conditions, are also known to affect migration. We investigated the timing of spring migration for 96 male and 201 female red deer (Cervus elaphus) using a long-term dataset (2005–2020). Overall, the timing of migration was mainly characterized by large individual variability between and within years (95% range 6 April to 18 June). The spring migration timing was, as expected, later with colder winter and spring conditions (North Atlantic Oscillation (NAO) winter and April indices) and later peak vegetation green-up (NDVI), with a five-day delay in green-up causing a migration delay of 1.2 days. Timing was also influenced by local conditions in summer and winter home ranges. Red deer with greater access to farmland and a more variable topography (hence variable plant phenology) in winter delayed migration. Similarly, individuals with higher-elevation summer ranges (with delayed onset of plant growth) also delayed migration. Our analyses highlight that the timing of red deer migration is determined by multiple drivers affecting foraging conditions in the landscape, indicative of considerable phenotypic plasticity.
Forfattere
Anders NielsenSammendrag
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Bolette BeleSammendrag
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