Big Data and Remote Sensing for Smart Forestry
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 2527
Special Issue Editors
Interests: smart forestry; digital forest resources monitoring; landscape ecology; remote sensing; spatial analysis; geoprocessing techniques; ecological indicators
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; change detection; spatial analysis; multispectral data analysis; LiDAR data analysis; UAV data analysis; GIS
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; multispectral data analysis; hyperspectral data analysis; SAR data analysis; machine learning; image classification; geoprocessing; forest fire/post-fire analysis
Interests: land cover and land use change dynamics; satellite and UAV remote sensing; landscape analysis and interpretation; remote sensing of vegetation; geographic object-based image analysis; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Forestry, as a cornerstone of environmental sustainability, stands at the intersection of technological innovation and ecological preservation. In response to the pressing challenges of climate change and resource management, this Special Issue, “Big Data and Remote Sensing for Smart Forestry”, investigates the transformative role of data-driven solutions and remote sensing technologies in the realm of forestry. The aim of this Special Issue is to explore several pivotal themes:
Precision Forestry: cutting-edge technologies, such as unpiloted aerial vehicles (UAVs), mounting multispectral, thermal, or LiDAR sensors, as well as satellite imagery, enable precise large-scale measurement and monitoring of forests. These tools optimize dendrometric measurement campaigns and aid in assessing forest health, detecting pests, and predicting fire risks and effects with real-time data.
Ecosystem Modelling: advanced data analytics and remote sensing data inform complex ecosystem models. These models predict forest dynamics, carbon sequestration, and species distribution, guiding conservation and restoration efforts.
Forest Biodiversity: remote sensing and big data analytics support biodiversity monitoring, habitat assessment, and protection of endangered species, promoting sustainable forest ecosystems.
Sustainable Forest Management: balancing conservation and economic interests, the integration of big data and remote sensing optimizes timber harvesting, minimizes environmental impact, and ensures long-term forest sustainability.
Climate Change Mitigation: forests play a critical role in mitigating climate change by sequestering carbon. This Special Issue explores how these technologies quantify carbon stocks, track deforestation and afforestation, and support international climate agreements.
Papers will serve as a comprehensive resource for researchers, practitioners, and policymakers seeking to harness the potential of big data and remote sensing in advancing smart forestry practices. Contributions based on multidisciplinary approaches, resulting from collaboration between researchers and practitioners, and highlighting the effects of technological innovations on smart forestry are also welcome. Our collective aim is to promote sustainable forestry, safeguard forest ecosystems, and ensure a sustainable future for generations to come.
Dr. Francesco Solano
Dr. Salvatore Praticò
Dr. Giandomenico De Luca
Prof. Dr. Giuseppe Modica
Guest Editors
Manuscript Submission Information
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Keywords
- forestry technology
- remote sensing data
- big data analytics
- sustainable forest management
- ecosystem modeling
- climate change mitigation
- time-series monitoring of forest ecosystems
- multiscale and multi temporal analysis of forest landscapes
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