Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2025
Sammendrag
No abstract has been registered
Sammendrag
No abstract has been registered
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.
Sammendrag
No abstract has been registered
Sammendrag
No abstract has been registered
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
Urban agriculture has the potential to contribute to more sustainable cities, but its impacts are complex and varied. By implementing robust monitoring systems, cities can better understand the true effects of urban farming initiatives. This evidence can then inform smarter policies and more effective urban planning strategies.
Forfattere
Anne B. NilsenSammendrag
NIBIO produces Green Structure Maps (GSM) for Norway that cover built-up areas, including cabin areas. GSM is a hybrid product based on information from remote sensing data and detailed national vector datasets such as roads, water, buildings, and land use. GSM contains 8 classes: Ground, Shrub, Tree, Grey, Road, Water, Building, and Agriculture. QGIS is excellently suited for visual control of GSM. Based on the size of the dataset (number of polygons), a significant random sample of each class is selected to check whether it is correctly classified. You can organize the map layers into different themes, set up QGIS with multiple map windows showing different themes and zoom levels, and use existing plugins to jump from polygon to polygon and compare with aerial images and code whether the classification is correct or not - quickly and efficiently. More comprehensive statistics can then be calculated, and the results can be compared against the requirements to determine if the GSM meets the standards.
Sammendrag
No abstract has been registered
Forfattere
Ioanna S. Panagea Paul Quataert María Alonso-Ayuso Teresa Gómez de la Bárcena Maarten De Boever Mariangela Diacono Anna Jacobs Johannes L. Jensen Felix Seidel Daria Seitz Heide Spiegel Thijs Vanden Nest Axel Don Greet RuysschaertSammendrag
No abstract has been registered