Search Results (159)

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs for bathymetry estimation, including raw reflectance, log-linear, and log-ratio transforms of the raw reflectance value in WV-2 images. In addition, we investigated the contribution of each spectral band and found that utilizing all eight spectral bands in WV-2 images offers the best solution for handling complex water quality conditions. We compared CatBoostOpt with linear regression (LR), support vector machine (SVM), random forest (RF), AdaBoost, gradient boosting, and deep convolutional neural network (DCNN). CatBoostOpt with log-ratio transformed reflectance achieved the best performance with an average root mean square error (RMSE) of 0.34 and coefficient of determination (${\mathrm{R}}^2$) of 0.87. Full article

The coexistence of cloud and snow is very common in remote sensing images. It presents persistent challenges for automated interpretation systems, primarily due to their highly similar visible light spectral characteristic in optical remote sensing images. This intrinsic spectral ambiguity significantly impedes accurate cloud and snow segmentation tasks, particularly in delineating fine boundary features between cloud and snow regions. Much research on cloud and snow segmentation based on deep learning models has been conducted, but there are still deficiencies in the extraction of fine boundaries between cloud and snow regions. In addition, existing segmentation models often misjudge the body of clouds and snow with similar features. This work proposes a Multi-scale Feature Mixed Attention Network (MFMANet). The framework integrates three key components: (1) a Multi-scale Pooling Feature Perception Module to capture multi-level structural features, (2) a Bilateral Feature Mixed Attention Module that enhances boundary detection through spatial-channel attention, and (3) a Multi-scale Feature Convolution Fusion Module to reduce edge blurring. We opted to test the model using a high-resolution cloud and snow dataset based on WorldView2 (CSWV). This dataset contains high-resolution images of cloud and snow, which can meet the training and testing requirements of cloud and snow segmentation tasks. Based on this dataset, we compare MFMANet with other classical deep learning segmentation algorithms. The experimental results show that the MFMANet network has better segmentation accuracy and robustness. Specifically, the average MIoU of the MFMANet network is 89.17%, and the accuracy is about 0.9% higher than CSDNet and about 0.7% higher than UNet. Further verification on the HRC_WHU dataset shows that the MIoU of the proposed model can reach 91.03%, and the performance is also superior to other compared segmentation methods. Full article

Harmony between humans and nature can be achieved by changing human perceptions and behavioral patterns towards natural resources. Cultural cognition can guide human behavior. By reviewing the development of grid–group culture theory, its classification methods, and its application to natural resource management, this study expects to gain a comprehensive understanding of the interactions between the worldviews, behavioral trends, and resource management practices of different types of people. By summarizing the application of the theory to multiple dimensions of natural resource management, the study finds the following: (1) changes in dominant cultural types at the same hierarchical level can change natural resource management strategies, and changes in cultural types of lower hierarchical groups are unable to drive policy changes; (2) the cultural types of policy followers in natural resource management are influenced by factors such as age, education, and gender, while natural resource policy (policy makers) cultural types are influenced by the natural resources themselves; (3) hierarchical natural resource management strategies are a more limited way of managing natural resources, at present. Egalitarianism is the ideal state of natural resource management, but the lack of economic efficiency considerations forces the egalitarian management approach to be ineffectively implemented. Full article

Our study investigates the drivers that foster the emergence of entrepreneurial responses to climate change among Indigenous communities. Indigenous peoples possess distinct worldviews and approaches to enterprise that prioritize community well-being and environmental stewardship over individual profit. Conventional entrepreneurship theories do not adequately capture Indigenous business approaches, leaving a limited understanding of how Indigenous communities merge traditional ecological knowledge with entrepreneurial activities to adapt to climate challenges. Through a systematic literature review (65 articles) and a case study of six Sri Lankan Vedda communities, we identified 15 key drivers that shape Indigenous climate-adaptive ventures and categorized them under five themes: (1) place-based relationships (resource stewardship, territorial connections, environmental risk factors); (2) intergenerational learning (traditional knowledge transfer, adaptation learning, collective experience); (3) community institutions (social networks, institutional support, overcoming the agency–structure paradox); (4) collective capacity (access to information, access to capital, community-oriented entrepreneurial traits); and (5) culturally aligned venture strategies (Indigenous business models, traditional products, local market relationships). Our study demonstrates how Vedda communities integrate entrepreneurship with cultural values to enhance climate resilience. Our research advances the field of Indigenous entrepreneurship while providing insights for policymakers and practitioners to support culturally appropriate climate adaptation strategies that enhance both community well-being and environmental sustainability. Full article

Background: Early Hearing Detection and Intervention (EHDI) programmes must partner effectively with families navigating complex circumstances. Adolescent parents (APs) in Teen Parent Units (TPUs) represent a dynamic group demonstrating resilience as they balance childcare, education, and their own developmental journeys. This study explores their understanding of infant hearing, sources of knowledge, and the development of an effective teaching tool. Methods: A qualitative study was conducted with AP learners at a TPU in Aotearoa, New Zealand. Following a period of relationship-building, three focus groups were held. Data were analysed using content analysis and reflexive thematic analysis. Results: AP learners demonstrated a strong awareness of multisensory interactions. Major sources of knowledge included their relational interactions with people they trusted (midwives and family members), rather than social media. Four key themes emerged in the teaching tool’s development: (1) the effectiveness of multimodal teaching tools, (2) the benefits of peer-supported group learning, (3) the impact of high strain, and (4) the importance of Te Ao Māori (a Māori worldview). Conclusions: This study highlights the importance of culturally grounded health interventions for families navigating complex life circumstances. Group-based learning fostered peer support, hands-on multimodal teaching was effective, and culturally relevant materials and pedagogies enhanced engagement. EHDI programs may more effectively support infants from families navigating complex circumstances by collaborating with trusted support people, integrating with wraparound care networks, utilising safe and familiar settings, and delivering interventions in an engaging and culturally appropriate manner. Full article

Photonic integrated interferometric imaging systems (PIISs) provide a compact solution for high-resolution Earth observation missions with stringent size, weight, and power (SWaP) constraints. As an indirect imaging method, a PIIS exhibits fundamentally different noise response characteristics compared to conventional remote sensing systems, and its imaging performance under practical operational scenarios has not been thoroughly investigated. The primary objective of this paper is to evaluate the operational capabilities of PIISs under remote sensing conditions. We (1) establish a signal-to-noise-ratio model for PIISs with balanced four-quadrature detection, (2) analyze the impacts of intensity noise and turbulent phase noise based on radiative transfer and turbulence models, and (3) simulate imaging performance with WorldView-3-like parameters. The results of the visibility signal-to-noise ratio (SNR) analysis demonstrate that the system’s minimum detectable fringe visibility is inversely proportional to the reciprocal of the sub-aperture intensity signal-to-noise ratio. When the integration time reaches 100 ms, the minimum detectable fringe visibility ranges between ${10}^{-2}$ and ${10}^{-3}$ (at 10 dB system efficiency). Imaging simulations demonstrate that recognizable image reconstruction requires integration times exceeding 10 ms for 10 cm baselines, achieving approximately 25 dB PSNR and 0.8 SSIM at 100 ms integration duration. These results may provide references for potential applications of photonic integrated interferometric imaging systems in remote sensing. Full article

Distinguishing vegetation types from satellite images has long been a goal of remote sensing, and the combination of multi-source and multi-temporal remote sensing images for vegetation classification is currently a hot topic in the field. In species-rich mountainous environments, this study selected four remote sensing images from different seasons (two aerial images, one WorldView-2 image, and one UAV image) and proposed a vegetation classification method integrating hierarchical extraction and object-oriented approaches for 11 vegetation types. This method innovatively combines the Random Forest algorithm with a decision tree model, constructing a hierarchical strategy based on multi-temporal feature combinations to progressively address the challenge of distinguishing vegetation types with similar spectral characteristics. Compared to traditional single-temporal classification methods, our approach significantly enhances classification accuracy through multi-temporal feature fusion and comparative experimental validation, offering a novel technical framework for fine-grained vegetation classification under complex land cover conditions. To validate the effectiveness of multi-temporal features, we additionally performed Random Forest classifications on the four individual remote sensing images. The results indicate that (1) for single-temporal images classification, the best classification performance was achieved with autumn images, reaching an overall classification accuracy of 72.36%, while spring images had the worst performance, with an accuracy of only 58.79%; (2) the overall classification accuracy based on multi-temporal features reached 89.10%, which is an improvement of 16.74% compared to the best single-temporal classification (autumn). Notably, the producer accuracy for species such as Quercus acutissima Carr., Tea plantations, Camellia sinensis (L.) Kuntze, Pinus taeda L., Phyllostachys spectabilis C.D.Chu et C.S.Chao, Pinus thunbergii Parl., and Castanea mollissima Blume all exceeded 90%, indicating a relatively ideal classification outcome. Full article

According to European organizations, intercultural competence is considered a prerequisite for achieving social cohesion. Even though its development calls for a lifelong learning approach, the formal education system has a primary task in its development through all school subjects, i.e., the entire school curriculum. In the last twenty years, international and European organizations have emphasized the importance of religious education in developing students’ intercultural competence. The Republic of Croatia has applied European recommendations in its educational documents and defined intercultural competence as one of the fundamental competencies in the national educational curriculum. The question arises of how religious education in the Republic of Croatia helps students achieve and develop intercultural competence concerning knowledge of other religions and worldviews. This paper is focused on Catholic Religious Education in primary and secondary education. Data are collected using semi-structured interviews among nine Catholic RE teachers in Zagreb County, Republic of Croatia. Qualitative research is based on findings of a quantitative survey conducted among Catholic religious education teachers in 2022. The research questions are: (1) Why are guest lectures and visits to religious communities less represented forms of learning in confessional Religious Education? (2) Which methods are used to develop specific dimensions of intercultural competence (conflict resolution, analytical and critical thinking, attitudes)? (3) Does interreligious learning lead to changes in students’ behaviour, and what are the obstacles to interreligious learning? This paper aims to examine the methodical approaches of RE teachers in the development of intercultural competence, as well as the obstacles they encounter in the process of imparting knowledge about other religions and worldviews within Catholic religious education. Results have shown that the teaching process remains at an informational level; the development of attitudes, critical thinking skills, and conflict-resolution skills is lacking. The absence of experiential learning can largely be attributed to external factors, such as administrative obstacles and teacher’s/parents’ attitudes. Full article

Indigenous wellness has been defined in varying contexts by diverse Indigenous Peoples. The existing indicators used to measure wellness are often defined from a Western perspective. Despite the rich conceptualizations of Indigenous wellness, there exists a notable gap in how it can be measured in contemporary contexts through an Indigenous lens. A scoping review methodology with the aim of identifying measures of wellness developed through Indigenous partnerships was carried out. We completed a systematic search in the following electronic databases: PubMed, CINAHL, Psych Info Academic Search Complete, SocIndex, and the Native Health Database. We then carried out a two-stage article screening process to identify eighteen relevant papers. Content analysis was then used to identify (1) the major categories for the partnership contexts utilized in the process for measuring Indigenous wellness and (2) the kinds of measures developed. Five main categories were characterized, including the following: (1) building relationships that uphold Indigenous worldviews is important, (2) a call for co-development protocols that weave multiple worldviews, (3) the need to increase awareness of the limitations in measuring Indigenous wellness, (4) community-specific context is important, and (5) a call for strengths-based indicators. Governments, organizations, and research partners are called upon to support the co-development of meaningful engagement protocols that privilege and reflect Indigenous voices and perspectives when measuring Indigenous wellness. Full article

Pan-sharpening aims to generate high-resolution multispectral (HRMS) images by combining high-resolution panchromatic (PAN) images with low-resolution multispectral (LRMS) data, while maintaining the symmetry of spatial and spectral characteristics. Traditional convolutional neural networks (CNNs) struggle with global dependency modeling due to local receptive fields, and Transformer-based models are computationally expensive. Recent Mamba models offer linear complexity and effective global modeling. However, existing Mamba-based methods lack sensitivity to local feature variations, leading to suboptimal fine-detail preservation. To address this, we propose a Conditional Skipping Mamba Network (CSMN), which enhances global-local feature fusion symmetrically through two modules: (1) the Adaptive Mamba Module (AMM), which improves global perception using adaptive spatial-frequency integration; and (2) the Cross-domain Mamba Module (CDMM), optimizing cross-domain spectral-spatial representation. Experimental results on the IKONOS and WorldView-2 datasets demonstrate that CSMN surpasses existing state-of-the-art methods in achieving superior spectral consistency and preserving spatial details, with performance that is more symmetric in fine-detail preservation. Full article

Humanity is currently in the midst of a number of serious ecological crises. Various scientific, philosophical, and religious ideas have been put forth in response to these global crises. Here, I suggest that the solutions to ecological problems can be best achieved when we undergo an essential change in our perspective on the existence and value of the natural world. In this regard, interreligious engagement and research, which address the multiple worldviews that emerge from individual religions and philosophies, have great potential to fundamentally transform our view of ecosystems. The problem is how to conduct such interreligious engagement and research, which has—unfortunately—to this point been overlooked. In this context, I propose the “four-step method of interreligious sympoiesis to address the ecological crisis”. This is a phenomenological–hermeneutic method that involves the following steps: (1) Suspension of Judgment (Epoché): the mind’s performing an epoché, which is taken as an ethical or religious vow; (2) Empathetic Reduction: the mind’s engaging in empathy with non-human beings; (3) Symbiotic Reduction: the mind’s envisioning of proper coexistence between humans and non-human beings in both minimal and maximal ways; (4) Interreligious Hermeneutical Synthesis: the arranging and synthesizing of the ideas obtained from the above reductions in a specific or comprehensive manner from an interreligious perspective. This paper aims to expound and defend these ideas. Full article

Mainstream approaches to nutrition typically focus on diet consumption, overlooking multi-dimensional aspects of nutrition that are important to American Indian/Alaska Native (AI/AN) communities. To address health challenges faced by AI/AN communities, strengths-based measures of nutrition grounded in community worldviews are needed. In collaboration with AI/AN communities in Baltimore and Minneapolis, we developed the Indigenous Nourishment Scales through three phases. Phase 1 involved focus group discussions with nine community-research council (CRC) members (n = 2) and four in-depth interviews (n = 4) to gather perspectives on existing models of nutrition. Phase 2 refined scales through two additional focus group discussions (n = 2) with a total of nine participants and two in-depth interviews (n = 2). Finally, in Phase 3, we held ten (n = 10) cognitive interviews with AI/AN community members to refine the scales. Participants appreciated the measures’ ability to provoke reflection on their relationship with nutrition and suggested adjustments to better capture cultural nuances, such as incorporating concepts like “being a good relative” to land. The Indigenous Nourishment Scales represent a departure from conventional approaches by encompassing multiple dimensions of nourishment, offering a framework that addresses epistemic injustices in nutrition measurement and grounds health measurement efforts directly in community perspectives and worldviews. Full article

Creating a global workforce is a driving need for our time. Higher education institutions are prioritizing helping students develop an awareness of their own and other cultures, as they are expected to participate in a diverse workforce. This study examines a large data set of learning assessment data for undergraduate students from an agriculture course focused on diversity and social justice, using the Beliefs, Events and Values Inventory (BEVI) instrument to assess the multicultural awareness development of the students. The study compared the impact of the medium of instruction (face-to-face versus online) in helping students develop multicultural awareness. The results revealed that students did not differ much in multicultural awareness across the medium of instruction. Moreover, to understand the multicultural awareness of the students in the pre-COVID period, during COVID and in the post-COVID period, the pre-test BEVI scores of the students were compared using ANOVA. The goal of this analysis was to capture the change in worldview of the students from the pre-COVID period to during COVID and post-COVID periods. The results revealed that pre-test BEVI scores for the pre-COVID period showed a lower degree of multicultural awareness than students during the COVID and post-COVID times. Also, there was no significant difference in the pre-test BEVI scores for the students in the COVID and post-COVID periods. Overall, the study makes important contributions to higher education literature as it reveals that (1) medium has negligible impact on the multicultural awareness of the students, and that (2) student worldviews have shifted significantly since the height of the global pandemic. Full article

This article describes the presence of a subliminal thesis—with conspiratorial and apocalyptic content—in the discourse of the Seventh-day Adventist tradition based on a documentary analysis of Adventist publications from the 1900s to the 1990s. The history of the development of this thesis is classified into three periods: (1) Proto-Adventist Subliminal Thesis, from 1900s to 1940s, with a discourse of anti-spiritualist emphasis; (2) Adventist Subliminal Thesis’ First Wave, from 1950s to 1960s, with a discourse of anti-media emphasis in the context of James Vicary’s experiments in the 1950s; and (3) Adventist Subliminal Thesis’ Second Wave, from 1970s to 1990s, with a discourse of conspiratorial emphasis in the context of the satanic panic of the 1980s and 1990s. The Adventist subliminal thesis is configured in a way of thinking that considers (1) the human being as a “mass-man” and culture as “mass culture”; (2) the media as having the power of manipulation and mental control; (3) adherence to moral panic phenomena as reactions to media threats to traditional values; and (4) the cosmic narrative of the Great Controversy as a worldview for understanding media messages and products as part of a satanic conspiracy. Full article

Increasingly, educators committed to the vision of Islamic schooling are expressing sentiments of moral dissonance. On the one hand, they choose Islamic schools because they aspire to affect hearts, nurture whole human beings, and grow spiritually while impacting their learners’ sense of higher purpose. On the other hand, they are up against an era of globalised educational reform, characterised by neoliberal-engendered market forces and neoliberal policy logic that promote performativity and efficiency. This narrows what counts as learning, technicises the art of teaching, and assumes all learning that counts is visible and measurable. The teacher education and ongoing professional learning that educators working in Islamic schools have access to remains bifurcated. It is unable to address how an educator committed to tarbiya as “soul-making” ought to navigate aspirations with realities. This paper serves as the introduction to a special issue (SI) dedicated to conceptualising why Islamically grounded teacher education is needed and what it may entail. This SI will also offer empirical studies related to existing Islamic teacher education and professional learning programmes that capture essential reflections for a burgeoning subfield of Islamic Education Studies. In this introduction specifically, the co-editors and a co-author colleague make three big moves to lay the foundations for Islamic teacher education, including (1) establishing urgency for why Islamic teacher education is needed, (2) conceptualising what makes teacher education “Islamic”, and (3) providing an example of one Islamic teacher education programme’s attempt to advance a coherent professional learning journey for Islamic school educators. Together, these three moves serve as an attempt to redress bifurcation and advance a contextually relevant in-road to teacher education that is rooted in an Islamic paradigm and worldview while conversant with contemporary debates in education. Full article