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As one of the world's most productive ecosystems, ecological land plays an important role in regional and global environments. Utilizing advanced optical and synthetic aperture radar (SAR) data for land cover/land use research becomes increasingly popular. This research aims to investigate the complementarity of fully polarimetric SAR and optical imaging for ecological land classification in the eastern coastal area of China.

Four polarimetric decomposition methods, namely, H/Alpha, Yamaguchi3, VanZyl3 and Krogager, were applied to Advanced Land Observing Satellite (ALOS) SAR image for scattering parameter extraction. These parameters were merged with ALOS optical parameters for subsequent classification using the object-based quick, unbiased, efficient statistical tree decision tree method.

The experimental results indicate that an improved classification performance was obtained in the decision level when merging the two data sources. In fact, unlike classification using only optical images, the proposed approach allowed to distinguish ecological land with similar spectrum but different scattering. Moreover, unlike classification using only polarimetric information, the integration of polarimetric and optical data allows to accurately distinguish reed from artemisia and sand from salt field and therefore achieve a detailed classification of the coastal area characteristics.

This research proposed an integrated classification method for coastal ecological land with polarimetric SAR and optical data. The object-based and decision-level fusion enables effective ecological land classification in coastal area was verified.

Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

Facilities managers have a host of skills to sustain the functionality of complex buildings, often not provided by them directly, but by the team of specialists they draw upon to effectively plan for the future, whether the resource be money, space or technology. Building intelligence presents a challenge in terms of understanding a wholly new approach to the building management. This paper asks if the intelligent building of today meets the needs of the facilities management team. Does it enable them to manage their asset more effectively? New technologies are converging that will enable a radically new approach to maintenance, enabling remote smart sensing or remote condition based monitoring (CBM). Some of the design and economic issues that arise from this radically new approach to managing built assets are highlighted and the possibilities for a maintenance environment, where wires, power cables and data loggers become a thing of the past, is described.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Supply of food from the early stages of societies was one of the most important needs of humans. Sustainable supply of food is a demand in modern societies. The agri-food market grows as the population rises every year. The increase in the demand side of the market is more than the growth of the supply side. The rate of using technology in the supply side is increasing rapidly. By using technology in some parts, the efficiency of production improved and caused more production while resources are the same. Availability of resources in different areas causes different ways of production and nurturing innovative technologies to maintain food security. Water, soil, climate change, and growth of population are drivers of using technology in food security. To depict the role of different technologies in the food industry, the authors have reviewed the role of the most important technologies in this field. Knowing the trends of changes in the industry will help to focus on the most important questions and solutions. Having a share in the global food market requires the major use of technology in production processes. In this chapter, the authors will review the most important trends of technology absorption in the food industry.

Heavy rainfall is one of the main causes of the degradation of historic rammed Earth architecture. For this reason, ensuring the conservation thereof entails understanding the factors involved in these risk situations. The purpose of this study is to research three past events in which rainfall caused damage and collapse to historic rammed Earth fortifications in Andalusia in order to analyse whether it is possible to prevent similar situations from occurring in the future.

The three case studies analysed are located in the south of Spain and occurred between 2017 and 2021. The hazard presented by rainfall within this context has been obtained from Art-Risk 3.0 (Registration No. 201999906530090). The vulnerability of the structures has been assessed with the Art-Risk 1 model. To characterise the strength, duration, and intensity of precipitation events, a workflow for the statistical use of GPM and GSMaP satellite resources has been designed, validated, and tested. The strength of the winds has been evaluated from data from ground-based weather stations.

GSMaP precipitation data is very similar to data from ground-based weather stations. Regarding the three risk events analysed, although they occurred in areas with a torrential rainfall hazard, the damage was caused by non-intense rainfall that did not exceed 5 mm/hour. The continuation of the rainfall for several days and the poor state of conservation of the walls seem to be the factors that triggered the collapses that fundamentally affected the restoration mortars.

A workflow applied to vulnerability and hazard analysis is presented, which validates the large-scale use of satellite images for past and present monitoring of heritage structure risk situations due to rain.

This article provides a broad overview of telecommunications and network‐related technologies. Topics covered include identification and review of network elements, analog and digital signals, synchronous and asynchronous transmission formats, transmission media and equipment, transmission techniques and characteristics, multiplexing, network types, access technologies, network architectures and topologies, local‐area network technologies and attributes, protocols and protocol issues, gateways, internetworking, local networking alternatives, equipment certification, and various aspects of network management. It is intended to provide the practicing professional in the field of library and information science with a broad, up‐to‐date technical review that might serve to support and facilitate further investigation of current developments in networks and networking. Although the broad range of topics is not treated in depth, numerous references are provided for further investigation.

The on‐going economic development of EU‐countries as well of the countries in the Central and Eastern (C&E) European region has been leading to a significant use of a great deal of natural resources as well as to noticeable environmental problems. Focuses on the project “Baltic environmental information dissemination system (BEIDS)” which has been acting as a focal point for the circulation of intelligent information on aspects of the marine environment among a sample of seven Baltic countries: Denmark, Finland, Germany, Sweden (EU) and Lithuania, Poland and Russia (non‐EU), contributing to networking and know‐how exchange, complementing efforts towards transregional cooperation in sustainable spatial planning on the basis of Baltic 21. The results reached to date include: increased awareness of matters related to sustainable development in the six participant countries; enhanced communication exchange and networking among the sampled nations; improved information flow and increased participation in events, activities and programmes across the Baltic Sea region. BEIDS is a prime example of the feasibility of using marine research as a tool for sustainable development and the results reached over the first two years are reviewed in this paper.

The primary objective of this study is to examine how students' technological factors affect remote access (RA) in smart learning (SL) environments. Additionally, the paper explores the moderating effect of students' technical skills (TS) on RA and SL.

The study applied a quantitative research approach and collected 125 valid questionnaires from students in Oman's higher education institutions (HEIs). A structural equation model (SEM) was employed for data analysis using the Smart PLS 4 version to examine the influence of technological factors on RA in SL environments.

It was found that the use of cloud-based RA in SL is influenced by students' use of technology, technology competitiveness and the availability of institutional software (IS). Moreover, students' TS were found to play a crucial role in moderating RA and SL, as well as technical knowledge (TK) and SL. These findings highlight the importance of technical competencies and software availability in shaping students' RA experiences.

The study's findings should be interpreted with caution due to the limited sample size, which may restrict the generalizability of the results.

The study suggests the technological learning capabilities of HEIs, which significantly improved by prioritizing critical technical factors, including knowledge and use of technology, availability of institutional software and RA antecedents in SL environments.

This paper offers practical and actionable directions for HEIs, universities, colleges and educators looking to incorporate technology into their practices in the dynamic and ever-evolving Fourth Industrial Era.

The study aims to develop recommendations for optimal Internet of things (IoT) based solutions for a smart precision irrigation automation platform using morphological thinking (MT). The smart irrigation system (SIS) can be applied for green roof and green wall (GRGW) design by studying the relationships and configurations that will be analyzed, listed and synthesized, representing “solutions spaces” and their possibilities.

The research examines studying various cases of SIS; and assessing and analyzing the identified case studies through a decision support system (DSS) considering several factors regarding IoT, plant characteristics, monitoring, irrigation system and schedule, climate, cost and sensors used.

To develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform.

The research paper analyzes and proposes a simultaneous solution to two conflicting problems. On the one hand, the paper proposes to apply greening of walls and roofs in hot arid regions, which will achieve greater environmental comfort. However, this is extremely difficult to implement in hot arid regions, since there is an objective problem – a lack of water. At the same time, the paper proposes the most rational approaches to organizing an irrigation system with the lowest water consumption and the highest efficiency for landscaping. Accordingly, this paper focuses on evaluating different types of SIS about the hot-arid climate in Qatar. The study aims to develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform, which can be applied for green wall and roof design.