Abstract:Purpose
Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is … Show more
“…, 2021). Accurate data measurement and timely inventories obtained through precision forestry tools result in more reasonable and efficient decision-making (Hasan et al. , 2019).…”
PurposeThis article aims to compare the LiDAR handheld mobile laser scanner (HMLS) scans with traditional survey methods, as the tree gauge and the hypsometer, to study the efficiency of the new technology in relation to the accuracy of structural forest attributes estimation useful to support a sustainable forest management.Design/methodology/approachA case study was carried out in a high forest located in Tuscany (Italy), by considering 5 forest types, in 20 different survey plots. A comparative analysis between two survey methods will be shown in order to verify the potential limits and the viability of the LiDAR HMLS in the forest field.FindingsThis research demonstrates that LiDAR HMLS technology allows to obtain a large amount of valuable data on forest structural parameters in a short span of time with a high level of accuracy and with obvious impact in terms of organisational efficiency.Practical implicationsFindings could be useful for forest owners highlighting the importance of investing in science and technology to improve the overall efficiency of forest resources management.Originality/valueThis article adds to the current knowledge on the precision forestry topic by providing insight on the feasibility and effectiveness of using precision technologies for monitoring forest ecosystems and dynamics. In particular, this study fills the gap in the literature linked to the need to have practical examples of the use of innovative technologies in forestry.
“…, 2021). Accurate data measurement and timely inventories obtained through precision forestry tools result in more reasonable and efficient decision-making (Hasan et al. , 2019).…”
PurposeThis article aims to compare the LiDAR handheld mobile laser scanner (HMLS) scans with traditional survey methods, as the tree gauge and the hypsometer, to study the efficiency of the new technology in relation to the accuracy of structural forest attributes estimation useful to support a sustainable forest management.Design/methodology/approachA case study was carried out in a high forest located in Tuscany (Italy), by considering 5 forest types, in 20 different survey plots. A comparative analysis between two survey methods will be shown in order to verify the potential limits and the viability of the LiDAR HMLS in the forest field.FindingsThis research demonstrates that LiDAR HMLS technology allows to obtain a large amount of valuable data on forest structural parameters in a short span of time with a high level of accuracy and with obvious impact in terms of organisational efficiency.Practical implicationsFindings could be useful for forest owners highlighting the importance of investing in science and technology to improve the overall efficiency of forest resources management.Originality/valueThis article adds to the current knowledge on the precision forestry topic by providing insight on the feasibility and effectiveness of using precision technologies for monitoring forest ecosystems and dynamics. In particular, this study fills the gap in the literature linked to the need to have practical examples of the use of innovative technologies in forestry.
“…Similar to applications noted in SDGs 1 and 7, satellite imagery data have also been explored for sustainable forest management [200][201][202][203][204], i.e., identifying forest fire risk, monitoring deforestation, regional forest development planning and assisting forest management policy decision making, etc. Of relevance, the authors of [203] specifically focus on China, investigating the uses of Big Data in sustainable forest management, where they identify the relevant applications. The field of smart forestry is also addressed in [204], where the practical realization of Big Data analytics is examined.…”
The launch of the United Nations (UN) 17 Sustainable Development Goals (SDGs) in 2015 was a historic event, uniting countries around the world around the shared agenda of sustainable development with a more balanced relationship between human beings and the planet. The SDGs affect or impact almost all aspects of life, as indeed does the technological revolution, empowered by Big Data and their related technologies. It is inevitable that these two significant domains and their integration will play central roles in achieving the 2030 Agenda. This research aims to provide a comprehensive overview of how these domains are currently interacting, by illustrating the impact of Big Data on sustainable development in the context of each of the 17 UN SDGs.
“…Recently, studies have shown how big data integration contributes as a technological compliance for massive information analysis on the unsuspected risk to occur. The future will largely depend on the concept of "datafication" and technological progress in terms of its creation and participation, as machines will communicate with each other via data networks, thereby reducing human participation in the process (Hasan et al, 2019).…”
Section: Big Data Integration Technologiesmentioning
The 2030 agenda for sustainable development has embraced the importance of sustainable practices in the construction industry. Parallel to the Industry revolution 4.0, the construction industry needs to keep pace with technological advances in data management to keep pace with the revolution through the ability to process and extract value from data. This phenomenon attracts the requirement of Big Data (BD). The construction industry deals with large volumes of heterogeneous data, which is expected to increase exponentially following an intense use of modern technologies. This research presents a comprehensive study of the literature, investigating the potential application of BD integration in the construction industry. The adoption of such technologies in this industry remains at a nascent stage and lags broad uptake of these technologies in other fields. The Construction Industry is driving to boost its productivity through the implementation of data technologies; hence, significant research is needed in this area. Currently, there is a lack of deep comprehensive research on BD integration applications that provide insight for the construction industry. This research closes the gap and gives an overview of the literature. The discussion presented the current utilization, the issues, and ways for potential works along with the challenges companion with the implementation.
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