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
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Margit Oami Kollstrøm Ulrike Böcker Anne Kjersti Uhlen Annbjørg Kristoffersen Jon Arne Dieseth Erik Tengstrand Shiori KogaAbstract
No abstract has been registered
Authors
Alexander N. Hristov André Bannink M Battelli Alejandro Belanche M.C. Cajarville Sanz G Fernandez-Turren F Garcia Arjan Jonker D.A. Kenny Vibeke Lind S.J. Meale D Meo Zilio Camila Muñoz David Pacheco Nico Peiren Mohammad Ramin L Rapetti Angela Schwarm Sokratis Stergiadis Katerina Theodoridou E.M. Ungerfeld S van Gastelen D.R. Yanez-Ruiz S.M. Waters Peter LundAbstract
No abstract has been registered
Abstract
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.
Authors
Mostafa Hoseini Helle Ross Gobakken Stephan Hoffmann Csongor Horvath Johannes Rahlf Jan Bjerketvedt Stefano Puliti Rasmus AstrupAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Jian Liu Faruk Djodjic Barbro Ulén Helena Aronsson Marianne Bechmann Lars Bergström Tore Krogstad Katarina KyllmarAbstract
No abstract has been registered
2024
Abstract
Introducing the MARCHES project approach in modelling the nitrogen transport within the Zelivka catchment using the SWAT+ model during a stakeholder meeting