Climate-Smart Forestry: Forest Monitoring in a Multi-Sensor Approach

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 393

Special Issue Editors


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Guest Editor
College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Longpan Road 159, Nanjing 210037, China
Interests: wireless transmission in the forestry; smart networking; wireless sensor networks

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Guest Editor
School of Forest Science, University of Eastern Finland, 80101 Joensuu, Finland
Interests: forest management; forest IT; remote sensing; GIS applications; terrain mobility
Special Issues, Collections and Topics in MDPI journals
College of Information Science and Technology & Artificial Intelligence, Nanjing Forestry University, Longpan Road 159, Nanjing 210037, China
Interests: intelligent non-destructive testing technology; smart sensors for forestry

Special Issue Information

Dear Colleagues,

Traditional forestry development and forest management face some challenges, such as extensive management and low resource utilization due to the lack of efficient information acquisition. With the development of information technology, a possibility emerges for the real-time monitoring and digital management of forestry. Some efforts have been devoted to using information technology to improve the accuracy of forest monitoring, enhance the timeliness of information transmission, and model forest resources effectively. The convergence of advanced sensor technologies, machine learning, and renewable energy is revolutionizing our ability to understand and protect forest ecosystems. What could the future of smart forests look like? How can we harness these technologies to address pressing challenges like climate change, biodiversity loss, and illegal logging? With this Special Issue, we compile research papers which use data from different sensors, platforms (satellite, airplane, unmanned aerial vehicle (UAVs)), 2D or 3D data, images or point clouds, optical or SAR/LiDAR data, and different spectral resolutions to address various aspects of forest monitoring: forest structure characterization, biomass/carbon sequestration estimations, fire extension and severity mapping, ecosystem recovery/degradation, forest health monitoring, invasive species mapping, early warning systems, and applications at various spatial or temporal scales.

Dr. Wanguo Jiao
Prof. Dr. Timo Tokola
Dr. Yin Wu
Guest Editors

Manuscript Submission Information

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Keywords

  • smart communications technology
  • wireless sensor networks
  • carbon mapping
  • smart sensing and detecting
  • measurement
  • point cloud computing
  • forest fires
  • forest management
  • plant phenotype monitoring

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Published Papers (1 paper)

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Research

17 pages, 3007 KiB  
Article
A Lightweight Stepwise SCMA Codebook Design Scheme for AWGN Channels
by Min Hua, Shuo Meng, Yue Juan, Borui Bian and Xiaoming Liu
Forests 2025, 16(2), 257; https://doi.org/10.3390/f16020257 - 30 Jan 2025
Viewed by 270
Abstract
Forests play a critical role in maintaining global ecological balance, regulating climate, and supporting biodiversity. Effective forest management and monitoring relies on the deployment of large-scale wireless sensor networks (WSNs) for real-time data collection, enabling the protection of ecosystems and the early detection [...] Read more.
Forests play a critical role in maintaining global ecological balance, regulating climate, and supporting biodiversity. Effective forest management and monitoring relies on the deployment of large-scale wireless sensor networks (WSNs) for real-time data collection, enabling the protection of ecosystems and the early detection of environmental changes. However, such massive deployments pose serious challenges with increasingly scarce radio resources. Sparse code multiple access (SCMA), a non-orthogonal multiple access (NOMA) technique, has been identified as a promising solution for facilitating wireless communications among numerous distributed sensors in large-scale WSNs with improved spectral efficiency. This is essential for application scenarios involving a substantial number of terminal devices, including forest monitoring and management. Codebook design is a critical issue for SCMA systems. It is closely related to the detection performance at the receiver, which in turn has a direct effect on the communication coverage or quality of service (QoS) for the terminal devices. This paper investigates the symbol error rate (SER) performance of SCMA systems over AWGN channels and derives its theoretical upper bound. The optimization objectives for each stage of codebook design are mathematically analyzed for a single resource element (RE), a single device, and multi-device, multi-RE scenarios. On this basis, a lightweight stepwise codebook design scheme is proposed in this paper. Simulation results demonstrate that the proposed codebooks can maintain fairness among devices while guaranteeing detection performance. Full article
(This article belongs to the Special Issue Climate-Smart Forestry: Forest Monitoring in a Multi-Sensor Approach)
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