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This paper explores teacher educators' endeavours to enhance their students' cultural competence in the context of Danish teacher education. It analyses how these endeavours resonate with the theoretical principles of critical multiculturalism and multicultural education. The study employed dyadic interviews as its primary method for data collection. The findings revealed that the educators felt constrained by the lack of awareness among politicians and policymakers of the significance of multicultural education, which made it difficult for them to develop in-depth knowledge and critical views on culture among students. The educators emphasized a need for a holistic approach that encompasses systemic changes and a shift in mindset toward critical multiculturalism in teacher education. This study calls for more institutional accountability to invest in preparing future teachers to work in multicultural classrooms.

Although the concepts of multicultural education and critical multiculturalism are well-known in Western societies, including Norway, research indicates that teachers often lack the necessary support and guidance to put these ideas into practice effectively. Through analysing individual interviews with twelve Norwegian student teachers, this paper explores their encounters with multicultural education in compulsory school settings. It aims to identify the ways in which the participating student teachers adjust their pedagogical strategies to integrate children’s diverse cultural and linguistic backgrounds into their education. The theoretical framework of the study includes multicultural education and critical multiculturalism, which are utilised to critically discuss the pedagogical strategies described by the student teachers. In summary, the findings reveal a complex interplay between the student teachers’ theoretical aspirations and the practical realities they meet during on-site schoolteacher training in Norwegian compulsory schools. While this study’s participants recognise the importance of embracing children’s diverse linguistic and cultural backgrounds, their capacity to implement their visions is often hindered by a lack of necessary support to develop knowledge about addressing complex issues, including power, inequality and social (in)justice.

ABSTRACT Understanding the habitat use of individuals can facilitate methods to measure the degree to which populations will be affected by potential stressors. Such insights can be hard to garner for marine species that are inaccessible during phases of their annual cycles. Here, we quantify the link between foraging habitat and behaviour in an aquatic bird of high conservation concern, the red‐throated diver (Gavia stellata) across three breeding populations (Finland, Iceland and Scotland) during their understudied moult period. Specifically, we quantify the relationship between feather isotope values (δ13C and δ15N) and diving behaviour, within and between populations, examining the use of intra‐depth zone (IDZ) dives as a proxy for benthic foraging. We found a strong positive relationship between both higher δ15N values and, to a lesser extent, δ13C values and the proportion of IDZ dives. This relationship was consistent across all three populations, but the baseline δ13C values varied between them, indicative of the populations' different moulting areas. Our results demonstrate that red‐throated divers continue to be generalist foragers after their breeding seasons, and that behavioural flexibility varies within and between populations. Furthermore, due to the existence of these relationships, we reveal the potential of stable isotope analysis as a standalone tool for monitoring changes in habitat use in this ecologically significant species. The approach may also apply to other generalist foragers that are known to use multiple foraging strategies (e.g., foraging benthically and pelagically), with implications for future conservation efforts.

Resumé På trods af at kulturel mangfoldighed giver forskellige muligheder og igangsætter positive ændringer i skolemiljøet, peger undersøgelser i Danmark på, at skolelærere ofte føler sig uforberedt på at skulle arbejde med elever med en transnational baggrund. Denne artikel præsenterer resultater fra et kvalitativt studie, der undersøger lærerstuderendes perspektiver på og erfaringer med undervisningsmetoder designet med fokus på elevernes kulturer og sprog. Undersøgelsens teoretiske ramme er baseret på teorier om multikulturel pædagogik og kulturelt ansvarlig didaktik. Det empiriske materiale består af individuelle interviews med i alt 14 studerende, der på dataindsamlingens tidspunkt (foråret 2022) nærmede sig afslutningen på deres læreruddannelse. Resultaterne indikerer, at læreruddannelsen ikke udruster de studerende med en dybtgående forståelse af undervisningsmetoder, der er velegnede til undervisning af elever med en transnational baggrund. Selvom de studerende havde visse kundskaber og idéer om integreringen af elevernes sprog i undervisningen, blev integreringen af kulturer betragtet som en udfordrende opgave. Abstract Although cultural diversity introduces various opportunities and brings positive changes to school environments, previous research in Denmark indicates that schoolteachers often feel unprepared to work with children of a transnational background. This article presents findings from a qualitative research project exploring Danish student teachers’ perspectives on and experiences with teaching methods designed with children’s cultural and linguistic diversity in mind. The theoretical framework of the study draws on the scholarship on multicultural education and culturally responsive teaching. The study participants were 14 students who, at the time of the study (spring 2022), were finishing their teacher education programme. The findings suggest that there is room for improvement in Danish teacher education to better equip students with a holistic understanding of teaching methods suitable for multicultural classrooms. The participants had some knowledge and ideas on integrating children’s languages, whilst integrating cultures was considered a significantly more difficult task.

The organisation and development strategies of youth soccer differ between Norway and Iceland. Whether this affect physical capacity is unknown. Thus, the first aim of the present study is to compare physical capacity between players from Iceland and Norway. Secondary aim is to assess associations between biological maturity and physical capacity in the Icelandic players since an association previously has been shown among the Norwegians. There were 48 U14 players from Iceland included and 103 players from Norway. Bone age (BA), measured with left-wrist x-ray, was used as an indicator of biological maturity. To measure physical capacity, 40 metre (m) linear sprint, standing long jump (SLJ), countermovement jump (CMJ), the Yo-Yo intermittent recovery test (IR1-test) and a maximal oxygen uptake test (VO2max) were used. Training load was assessed by questionnaire. The results showed that the Norwegian players ran faster (5.90 ± 0.38 vs. 6.37 ± 0.44 s, p

Abstract Lunar surface chemistry is essential for revealing petrological characteristics to understand the evolution of the Moon. Existing chemistry mapping from Apollo and Luna returned samples could only calibrate chemical features before 3.0 Gyr, missing the critical late period of the Moon. Here we present major oxides chemistry maps by adding distinctive 2.0 Gyr Chang’e-5 lunar soil samples in combination with a deep learning-based inversion model. The inferred chemical contents are more precise than the Lunar Prospector Gamma-Ray Spectrometer (GRS) maps and are closest to returned samples abundances compared to existing literature. The verification of in situ measurement data acquired by Chang'e 3 and Chang'e 4 lunar rover demonstrated that Chang’e-5 samples are indispensable ground truth in mapping lunar surface chemistry. From these maps, young mare basalt units are determined which can be potential sites in future sample return mission to constrain the late lunar magmatic and thermal history.

The paper is part of the qualitative research project Educational Aspirations, Opportunities and Challenges for Immigrants in University Education in Iceland, conducted in Iceland's three biggest universities. The main goal of the paper is to investigate immigrant students' experiences of communication with teachers during the learning process and their perspectives on multicultural group work. Furthermore, the paper explores immigrant students' experiences of learner-centred approach and culturally responsive teaching methods applied by some teachers. The data was collected through focus group interviews and qualitative, semi-structured individual interviews with immigrant students. The theoretical framework is mainly based on the constructivist theory, which emphasises the importance of communication and the learner-centred approach. Additionally, the theoretical framework includes multicultural education theory, which puts an emphasis on applying culturally responsive teaching methods in classrooms with diverse student populations. The analysis of the interviews revealed that the participants' experiences of communication with teachers and peers were mostly positive. However, culturally responsive teaching is still a rare phenomenon in Icelandic universities. When it comes to the participants' perspectives on group work, the experiences ranged from being highly positive to negative.

This study provides the first comprehensive examination of gender quota legislation for executive management positions, executive gender quotas (EGQs), in Icelandic listed companies, alongside the general public’s attitudes toward such measures. Iceland has been a global leader in gender equality, according to the World Economic Forum, for 15 years, yet progress in achieving gender balance in executive positions remains limited. This research aims to explore how board members in all listed companies in Iceland view EGQ legislation and assess the level of public support for such legislation. Despite the implementation of gender quota legislation for corporate boards, board gender quotas (BGQs), in 2010 aimed at promoting gender balance, significant gender disparities persist at the executive management level. This study reveals distinct attitudes toward EGQs, with men predominantly opposing such legislation and women showing more support, particularly when progress toward gender balance is seen as inadequate. The findings underscore the importance of ongoing dialogue and potential legislative actions to address persistent gender inequalities in leadership positions. This research marks a novel contribution to the discourse on gender quotas in corporate governance, highlighting the need for systemic changes to achieve genuine gender parity in executive management teams. This study presents the first findings on the views of board members and the public on gender quota legislation in executive management positions to close the gender gap in economic participation.

Pansharpening refers to the process of fusing multispectral (MS) images with panchromatic (PAN) images to obtain high-resolution multispectral (HRMS) images. However, due to the low correlation and similarity between MS and PAN images, as well as inaccuracies in spatial information injection, HRMS images often suffer from significant spectral and spatial distortions. To address these issues, a pansharpening method based on multimodal texture correction and adaptive edge detail fusion is proposed in this paper. To obtain a texture-corrected (TC) image that is highly correlated and similar to the MS image, the target-adaptive CNN-based pansharpening (A-PNN) method is introduced. By constructing a multimodal texture correction model, intensity, gradient, and A-PNN-based deep plug-and-play correction constraints are established between the TC and source images. Additionally, an adaptive degradation filter algorithm is proposed to ensure the accuracy of these constraints. Since the TC image obtained can effectively replace the PAN image and considering that the MS image contains valuable spatial information, an adaptive edge detail fusion algorithm is also proposed. This algorithm adaptively extracts detailed information from the TC and MS images to apply edge protection. Given the limited spatial information in the MS image, its spatial information is proportionally enhanced before the adaptive fusion. The fused spatial information is then injected into the upsampled multispectral (UPMS) image to produce the final HRMS image. Extensive experimental results demonstrated that compared with other methods, the proposed algorithm achieved superior results in terms of both subjective visual effects and objective evaluation metrics.

Background In anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), histopathological assessment of affected tissue is often necessary for diagnosis and assessment of disease extent. There is a requirement for validated non-invasive biomarkers to avoid the need for serial tissue biopsies.Methods A systematic review of scientific databases from 2012 until present was performed to identify studies fulfilling the inclusion criteria. Studies were assessed for quality using the Strengthening the Reporting of Observational Studies in Epidemiology checklist for cohort, case–control and cross-sectional studies and the Risk of Bias Assessment tool for Non-randomised Studies, or the Cochrane Risk of Bias tool 2.0 for randomised controlled trials. A descriptive synthesis of the data for non-invasive (blood-based or urinary) biomarkers of AAV-related disease activity and organ damage was performed.Results Twenty-two high quality studies were included. These articles reported the value of blood-based and urinary biomarkers including anti-neutrophil cytoplasmic antibodies, immune cells, complement factors, gene expression profiles, cytokines, chemokines and other proteins in the assessment of disease activity and/or organ damage in patients with AAV. Many of these biomarkers involve the alternative complement pathway, neutrophil activation and macrophage activation.Conclusion This is the first contemporary systematic review synthesising the value of non-invasive biomarkers of AAV-related disease activity and organ damage. The incorporation of individual markers in combined biomarker profiles might enhance clinical decision-making. Many unmet needs were identified; few studies involve oeosinophilic granulomatosis with polyangiitis and patients with childhood-onset AAV. Further validation of the candidate biomarkers is warranted in large prospective studies to bridge the existing knowledge gaps and apply precision health to systemic vasculitis.

This study leverages a graph-based genetic algorithm (GB-GA) for the design of efficient nitrogen-fixing catalysts as alternatives to the Schrock catalyst, with the aim to improve the energetics of key reaction steps. Despite the abundance of nitrogen in the atmosphere, it remains largely inaccessible due to its inert nature. The Schrock catalyst, a molybdenum-based complex, offered a breakthrough but its practical application is limited due to low turnover numbers and energetic bottlenecks. The genetic algorithm in our study explores the chemical space for viable modifications of the Schrock catalyst, evaluating each modified catalyst’s fitness based on reaction energies of key catalytic steps and synthetic accessibility. Through a series of selection and optimization processes, we obtained fully converged catalytic cycles for 20 molecules at the B3LYP level of theory. From these results, we identified three promising molecules, each demonstrating unique advantages in different aspects of the catalytic cycle. This study offers valuable insights into the potential of generative models for catalyst design. Our results can help guide future work on catalyst discovery for the challenging nitrogen fixation process.

This paper explores and compares student teachers’ experiences and perspectives on culturally responsive assessment in compulsory schooling in Denmark and Iceland. The study’s theoretical framework draws on scholarship on culturally responsive assessment. The data was derived from fourteen interviews with Danish student teachers and ten interviews with Icelandic student teachers. As per the selection criteria, all participants had to be in the final stages of their education process, meaning they had completed their on-site schoolteacher training and most courses in their teacher education programme. During the interviews, the participants reflected on pre-instructional, formative, and summative assessment practices with cultural diversity in mind. Furthermore, they discussed the importance of assessing children’s well-being. In both countries, the participants demonstrated positive attitudes towards cultural diversity and expressed awareness of considering children’s cultural and linguistic backgrounds when assessing them. On the other hand, most participants expressed criticism of teacher education programmes for lacking attention to the topic of culturally responsive assessment, which resulted in their rudimentary understanding of the theoretical underpinnings.

Lava flows pose a hazard in volcanic environments and reset ecosystem development. A succession of dated lava flows provides the possibility to estimate the direction and rates of ecosystem development and can be used to predict future development. We examine plant succession, soil development and soil carbon (C) accretion on the historical (post 874 AD) lava flows formed by the Hekla volcano in south Iceland. Vegetation and soil measurements were conducted all around the volcano reflecting the diverse vegetation communities on the lavas, climatic conditions around Hekla mountain and various intensities in deposition of loose material. Multivariate analysis was used to identify groups with similar vegetation composition and patterns in the vegetation. The association of vegetation and soil parameters with lava age, mean annual temperature, mean annual precipitation and soil accumulation rate (SAR) was analysed. Soil carbon concentration increased with increasing lava age becoming comparable to concentrations found on the prehistoric lavas. The combination of a sub-Arctic climate, gradual soil thickening due to input of loose material and the specific properties of volcanic soils allow for continuing accumulation of soil carbon in the soil profile. Four successional stages were identified: initial colonization and cover coalescence (ICC) of Racomitrium lanuginosum and Stereocaulon spp. (lavas 600 years); and highland conditions/retrogression (H/R) by tephra deposition (70−860 years). The long time span of the SC stage indicates arrested development by the thick R. lanuginosum moss mat. The progression from SC into VPD was linked to age of the lava flows and soil depth, which was significantly deeper within the VPD stage. Birch was growing on lavas over 600 years old indicating the development towards birch woodland, the climax ecosystem in Iceland.

The empirical line (EL) calibration method is commonly used for atmospheric correction of remotely sensed spectral images and recovery of surface reflectance. The current EL-based methods are applicable to calibrate only single images. Therefore, the use of the EL calibration is impractical for imaging campaigns, where many (partially overlapped) images are acquired to cover a large area. In addition, the EL results are unconstrained and an undesired reflectance with negative values or larger than 100% can be obtained. In this paper, we use the standard EL model to formulate a new generalized empirical line (GEL) model. Based on the GEL, we present a novel method for simultaneous and constrained calibration of multiple images. This new method allows for calibration through multiple image constrained empirical line (MIcEL) and three additional calibration modes. Given a set of images, we use the available ground targets and automatically extracted tie points between overlapping images to calibrate all the images in the set simultaneously. Quantitative and visual assessments of the proposed method were carried out relatively to the off-the-shelf method quick atmospheric correction (QUAC), using real hyperspectral images and field measurements. The results clearly show the superiority of MIcEL with respect to the minimization of the difference between the reflectance values of the same object in different overlapping images. An assessment of the absolute accuracy, with respect to 11 field measurement points, shows that the accuracy of MIcEL, with an average mean absolute error (MAE) of ∼11%, is comparable with respect to the QUAC.

The classification of hyperspectral images (HSIs) is an essential application of remote sensing and it is addressed by numerous publications every year. A large body of these papers present new classification algorithms and benchmark them against established methods on public hyperspectral datasets. The metadata contained in these research papers (i.e., the size of the image, the number of classes, the type of classifier, etc.) present an unexploited source of information that can be used to estimate the performance of classifiers before doing the actual experiments. In this article, we propose a novel approach to investigate to what degree HSIs can be classified by using only metadata. This can guide remote sensing researchers to identify optimal classifiers and develop new algorithms. In the experiments, different linear and nonlinear prediction methods are trained and tested by using data on classification accuracy and metadata from 100 HSIs classification papers. The experimental results demonstrate that the proposed ensemble learning voting method outperforms other comparative methods in quantitative assessments.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

Morphological attribute profiles are multilevel decompositions of images obtained with a sequence of transformations performed by connected operators. They have been extensively employed in performing multi-scale and region-based analysis in a large number of applications. One main, still unresolved, issue is the selection of filter parameters able to provide representative and non-redundant threshold decomposition of the image. This paper presents a framework for the automatic selection of filter thresholds based on Granulometric Characteristic Functions (GCFs). GCFs describe the way that non-linear morphological filters simplify a scene according to a given measure. Since attribute filters rely on a hierarchical representation of an image (e.g., the Tree of Shapes) for their implementation, GCFs can be efficiently computed by taking advantage of the tree representation. Eventually, the study of the GCFs allows the identification of a meaningful set of thresholds. Therefore, a trial and error approach is not necessary for the threshold selection, automating the process and in turn decreasing the computational time. It is shown that the redundant information is reduced within the resulting profiles (a problem of high occurrence, as regards manual selection). The proposed approach is tested on two real remote sensing data sets, and the classification results are compared with strategies present in the literature.

Random Forest (RF) is a widely used classifier to show a good performance of hyperspectral data classification. However, such performance could be improved by increasing the diversity that characterizes the ensemble architecture. In this paper, we propose a novel ensemble approach, namely rotation random forest via kernel principal component analysis (RoRF-KPCA). In particular, the original feature space is first randomly split into several subsets, and KPCA is performed on each subset to extract high order statistics. The obtained feature sets are merged and used as input to an RF classifier. Finally, the results achieved at each step are fused by a majority vote. Experimental analysis is conducted using real hyperspectral remote sensing images to evaluate the performance of the proposed method in comparison with RF, rotation forest, support vector machines, and RoRF-PCA. The obtained results demonstrate the effectiveness of the proposed method.

With the continuous development of modern remote sensing satellite technology, high-resolution (HR) remote sensing image data have gradually become widely used. However, due to the vastness of areas that need to be monitored and the difficulty in obtaining HR images, most monitoring projects still rely on low-resolution (LR) data for the regions being monitored. The emergence of remote sensing image super-resolution (SR) reconstruction technology effectively compensates for the lack of original HR images. This paper proposes an Improved Enhanced Super-Resolution Generative Adversarial Network (IESRGAN) based on an enhanced U-Net structure for a 4× scale detail reconstruction of LR images using NaSC-TG2 remote sensing images. In this method, in-depth research has been performed and consequent improvements have been made to the generator and discriminator within the GAN network. Specifically, before introducing Residual-in-Residual Dense Blocks (RRDB), in the proposed method, input images are subjected to reflective padding to enhance edge information. Meanwhile, a U-Net structure is adopted for the discriminator, incorporating spectral normalization to focus on semantic and structural changes between real and fake images, thereby improving generated image quality and GAN performance. To evaluate the effectiveness and generalization ability of our proposed model, experiments were conducted on multiple real-world remote sensing image datasets. Experimental results demonstrate that IESRGAN exhibits strong generalization capabilities while delivering outstanding performance in terms of PSNR, SSIM, and LPIPS image evaluation metrics.

Investigations of the geomorphological fingerprints of palaeo‐ice streams are essential for enhancing our understanding of ice‐stream behaviour. Cross‐cutting flowsets of palaeo‐ice streams, during and following the Last Glacial Maximum, have been suggested in northeast Iceland based on the mapping of streamlined subglacial bedforms (SSBs). To increase our understanding of the dynamics of the Icelandic Ice Sheet (IIS) during deglaciation, we investigate transverse ridges, together with glacifluvial and ice‐marginal landforms, within the largest flowset. The main emphasis is on the transverse ridges, which are primarily interpreted as ribbed moraines – the first to be described in Iceland. Morphological data are combined with sedimentological analyses of the ribbed moraines. Our results show that the ribbed moraines are composed of pre‐existing material, often exhibiting a base of stratified glacifluvial sediments draped with subglacial till. Deformation and thrust structures within both units suggest compressional flow during the formation of the ridges. Our results suggest the ribbed moraines develop due to velocity gradients under the lateral shear margin of an ice stream based on their distribution and often oblique orientation in relation to SSBs. The ribbed moraines superimpose and thus post‐date the SSBs, signifying the waning stage of ice streaming. We suggest that the ridges formed during ice‐stream shutdown following the Younger Dryas and/or Preboreal re‐advances. Eskers and ice‐marginal landforms imply channelized water drainage during the final deglaciation interrupted by short‐lived re‐advances. This study has implications for the style of deglaciation associated with ice streaming in the northeastern part of the IIS. We characterize the role of ribbed moraines within the ice sheet and identify directions for future work. [ABSTRACT FROM AUTHOR]

Understanding the habitat use of individuals can facilitate methods to measure the degree to which populations will be affected by potential stressors. Such insights can be hard to garner for marine species that are inaccessible during phases of their annual cycles. Here, we quantify the link between foraging habitat and behaviour in an aquatic bird of high conservation concern, the red‐throated diver (Gavia stellata) across three breeding populations (Finland, Iceland and Scotland) during their understudied moult period. Specifically, we quantify the relationship between feather isotope values (δ13C and δ15N) and diving behaviour, within and between populations, examining the use of intra‐depth zone (IDZ) dives as a proxy for benthic foraging. We found a strong positive relationship between both higher δ15N values and, to a lesser extent, δ13C values and the proportion of IDZ dives. This relationship was consistent across all three populations, but the baseline δ13C values varied between them, indicative of the populations' different moulting areas. Our results demonstrate that red‐throated divers continue to be generalist foragers after their breeding seasons, and that behavioural flexibility varies within and between populations. Furthermore, due to the existence of these relationships, we reveal the potential of stable isotope analysis as a standalone tool for monitoring changes in habitat use in this ecologically significant species. The approach may also apply to other generalist foragers that are known to use multiple foraging strategies (e.g., foraging benthically and pelagically), with implications for future conservation efforts. [ABSTRACT FROM AUTHOR]

Although a few ringing recoveries indicate that Icelandic breeding Purple Sandpipers Calidris maritima remain in Iceland through the year, there was the possibility that some spend the non-breeding season outside Iceland. To obtain a better understanding of their movements, 22 breeding adults (mainly males) were colour-ringed and tagged with geolocators in Arctic Tern Sterna paradisaea colonies on heathland adjacent to the coast of the Melrakkaslétta in northeast Iceland during 2019 and 2022. Counts, including searches for the colour-ringed birds, were also made on the coast beside the breeding areas through one non-breeding season (2019/20). Based on the recovery of 13 geolocators from males, 11 remained in northeast Iceland for the autumn moult, whilst two moved to northwest Iceland. By mid-winter, only five remained in northeast Iceland, and the rest wintered in the northwest and west of Iceland. Observations of colour-ringed birds confirmed that some remained close to their breeding area in autumn before dispersing to other parts of Iceland for winter. There was no evidence that Icelandic breeding birds left Iceland. Birds that wintered in the northwest and west of Iceland, returned to the northeast mainly during April. Counts during the non-breeding season along the shore adjacent to the breeding areas exceeded the number that could be accounted for by the local breeding population, indicating an influx of wintering birds from elsewhere. [ABSTRACT FROM AUTHOR]

The concept of sustainability has been widely recognized as a pivotal objective for future growth. Therefore, it is imperative to incorporate the principles of sustainability into policies and plans, particularly in land use and agri-food production, sectors often associated with negative environmental impacts. Addressing all three pillars of sustainability—environmental, economic, and social—is essential, within the contexts of agri-food production and land use. Consequently, sustainable rural development is also critical. This study utilizes Iceland as a case to examine whether and how sustainability goals are translated from national policies to municipal plans, which represent the governance level closest to implementation. The research employs content analysis of national policies and municipal plans, utilizing grounded theory to code the content. The findings indicate that while the concept of sustainability is embedded in Icelandic policies and goals, there is a tendency to overlook the economic and social dimensions. Additionally, the study reveals a limited application of sustainability principles in rural development and agri-food production. Recognizing the "wicked" nature of sustainability, which complicates its implementation, is crucial for advancing from goal setting to effective action. [ABSTRACT FROM AUTHOR]

An improved understanding of the geographical unevenness of the global energy transition is important. The concept of ‘sociotechnical imaginaries’ has been used extensively for understanding how desired technology futures are envisioned and differentially articulated in various contexts. Supplementing this, the concept of ‘nature imaginaries’ is proposed in this article, to specifically address collective moral visions of human/nature relations that underwrite discourses and actions by various actors. Nature plays an active role in both types of imaginaries. Their complex interactions play a part in how energy transitions unfold. The article uses this framework for a description of the energy situation in Iceland, and its largely successful transition towards renewable energy through the development of hydropower and geothermal resources. Particular sociotechnical and nature imaginaries, sometimes opposed to each other, are discernible. The article argues that the analysis of conflicting imaginaries at work in specific energy transitions might help in identifying leverage points from where it is possible to work in a small way towards a global transition.

The eleven papers in this special section serve as a tribute to Professor David A. Landgrebe who is known for his work in the fundamentals of multispectral image processing and analysis. The papers are grouped into three categories: historical and future developments, methodological advancements, and survey and review.

Abstract Migratory species have geographically separate distributions during their annual cycle, and these areas can vary between populations and individuals. This can lead to differential stress levels being experienced across a species range. Gathering information on the areas used during the annual cycle of red‐throated divers (RTDs; Gavia stellata) has become an increasingly pressing issue, as they are a species of concern when considering the effects of disturbance from offshore wind farms and the associated ship traffic. Here, we use light‐based geolocator tags, deployed during the summer breeding season, to determine the non‐breeding winter location of RTDs from breeding locations in Scotland, Finland, and Iceland. We also use δ15N and δ13C isotope signatures, from feather samples, to link population‐level differences in areas used in the molt period to population‐level differences in isotope signatures. We found from geolocator data that RTDs from the three different breeding locations did not overlap in their winter distributions. Differences in isotope signatures suggested this spatial separation was also evident in the molting period, when geolocation data were unavailable. We also found that of the three populations, RTDs breeding in Iceland moved the shortest distance from their breeding grounds to their wintering grounds. In contrast, RTDs breeding in Finland moved the furthest, with a westward migration from the Baltic into the southern North Sea. Overall, these results suggest that RTDs breeding in Finland are likely to encounter anthropogenic activity during the winter period, where they currently overlap with areas of future planned developments. Icelandic and Scottish birds are less likely to be affected, due to less ship activity and few or no offshore wind farms in their wintering distributions. We also demonstrate that separating the three populations isotopically is possible and suggest further work to allocate breeding individuals to wintering areas based solely on feather samples.

The analysis of multi-temporal remote-sensing images is one of the main applications in Earth’s observation and monitoring. In this paper, we present a Matlab toolbox for change detection analysis of optical multi-temporal remote-sensing data in which unsupervised approaches, iterative principal component analysis (ITPCA), and iteratively reweighted multivariate alteration detection (IR-MAD) are implemented and optimized. The optimization is represented by the implementation of novel pre- and post-processing strategies that aim to mitigate the side effects introduced by different acquisition conditions affecting change detection analysis. Special modules have been designed in order to decrease the required memory when large data sets are processed.

In this letter, we propose a new version of the rotation forest (RoF) method for the pixelwise classification of hyperspectral images. RoF, which is an ensemble of decision tree classifiers, uses random feature selection and data transformation techniques (i.e., principal component analysis) to improve both the accuracy of base classifiers and the diversity within the ensemble. Traditional RoF performs data transformation on the training samples of each subset. In order to further improve the performance of RoF, the data transformation is separately performed on each class, extracting sets of transformation matrices that are strictly dependent on the training samples of each single class. The approach, namely, class-separation-based RoF (RoFCS), is experimentally investigated on a hyperspectral image collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Experimental results demonstrate that the proposed methodology achieves excellent performances, in comparison with random forest and RoF classifiers.

Change vector analysis (CVA) is a simple yet attractive method to detect changes with remote sensing images. Since its first introduction in 1980, CVA has received increased attention from the remote sensing community, leading to the definition of several new methodologies based on the CVAs concept while extending its applicability. In this article, we provide an extensive review of CVA-based approaches in the context of land-cover change detection (LCCD). We first reviewed the development of the CVA-based LCCD method with remote sensing images, and some classical-related methods were discussed. Then, we analyze and compare the performance of five selected methods. The analysis was carried out on seven real datasets acquired by different sensors and platforms (e.g., Landsat, Quick Bird, and airborne) and spatial resolutions (from 0.5 to 30 m/pixel), with scenes from both urban and natural landscapes. The analysis shows several Moreover, comparing the detection accuracies of different methods implies that the content of an image scene still plays an important role when disregarding the unique preferences of different methods.