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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

To document

Abstract

Boreal forests are important carbon sinks and host a diverse array of species that provide important ecosystem functions.Boreal forests have a long history of intensive forestry, in which even-aged management with clear-cutting has been thedominant harvesting practice for the past 50–80 years. As a second cycle of clear-cutting is emerging, there is an urgentneed to examine the effects of repeated clear-cutting events on biodiversity. Clear-cutting has led to reduced numbers ofold and large trees, decreased volumes of dead wood of varied decay stages and diameters, and altered physical andchemical compositions of soils. The old-growth boreal forest has been fragmented and considerably reduced. Here,we review short- and long-term (≥50 years) effects of clear-cutting on boreal forest biodiversity in four key substrates:living trees, dead wood, ground and soil. We then assess landscape-level changes (habitat fragmentation and edge effects)on this biodiversity. There is evidence for long-term community changes af

To document

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.