Vegetation and Remote Sensing Phenology in Deciduous Forests

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: 31 October 2025 | Viewed by 1384

Special Issue Editors


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Guest Editor
College of Environment and Resources, College of Carbon Neutrality, State Key Laboratory of Subtropical Silviculture, Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A&F University, Hangzhou, China
Interests: forest ecosystem sensitivity and resilience; vegetation phenology; carbon dynamics

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Guest Editor
Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
Interests: temperate deciduous forest; tree phenology; shrub phenology; invasive species

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Guest Editor
Department of Geography, University of Kentucky, Lexington, KY 40506, USA
Interests: plant/vegetation phenology; bioclimatology; remote sensing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Environment and Resources, College of Carbon Neutrality, State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, China
Interests: vegetation phenology; carbon cycle of forest ecosystems

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Guest Editor
Academician Workstation for Big Data in Ecology and Environment, Environment Research Institute, Shandong University, Jinan, China
Interests: vegetation dynamics under global change; remote sensing application in eco-environment

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Guest Editor
Geospatial Sciences Center of Excellence, Geography and Geospatial Sciences, South Dakota State University, Brookings, SD 57007, USA
Interests: plant/land surface phenology; climate change; vegetation dynamic; global change ecology

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Guest Editor
College of Urban and Environmental Sciences, Peking University, Beijing, China
Interests: vegetation phenology; phenology modeling; climate change
Geospatial Sciences Center of Excellence, Department of Geography and Geospatial Sciences, South Dakota State University, Brookings, SD 57007, USA
Interests: land surface phenology; tropical forest long-term dynamics; human-climate interactions; satellite data-fusion; time series analysis

Special Issue Information

Dear Colleagues,

The primary objective of this Special Issue (SI) is to advance our understanding of deciduous forest ecosystems by examining the seasonal patterns and dynamics of vegetation growth, leaf emergence, flowering, and senescence, as well as its broader implications for ecosystem management, biodiversity conservation, and climate change mitigation. This SI aims to provide a comprehensive overview of the latest advancements in remote sensing technologies and methodologies that enable the precise monitoring and analysis of phenological events in deciduous forests. By bringing together cutting-edge research, we hope to foster new insights and strategies for sustaining these vital ecosystems in a changing world.

The articles within this SI can span a range of topics, from the development of novel algorithms for phenological metric extraction to the application of satellite data in tracking phenological changes across diverse regions. The contributions will highlight the efficacy of remote sensing in delineating the intricate dynamics of deciduous forests with an unprecedented level of detail and accuracy.

This SI encourages an interdisciplinary approach, inviting contributions from ecologists, geographers, remote sensing specialists, climatologists, and environmental scientists. The synergy of these diverse perspectives enriches our collective grasp of deciduous forest phenology and its broader ecological significance. As the field continues to evolve, we anticipate that the studies presented here will inspire further inquiry and innovation, contributing to the advancement of ecological and global change studies.

We invite submissions that explore innovative methodologies, case studies, and theoretical advancements in vegetation and remote sensing phenology. Topics of interest include, but are not limited to, new techniques for enhancing the accuracy of phenological data (such as the use of machine learning algorithms, big data analytics, or the fusion of multi-source remote sensing datasets), the impact of climate change on phenological shifts, and the integration of vegetation phenology with vegetation or climate models.

Dr. Rong Yu
Dr. Alison Donnelly
Dr. Liang Liang
Dr. Jingru Zhang
Dr. Shilong Ren
Dr. Shuai An
Dr. Weiguang Lang
Dr. Yu Shen
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • vegetation phenology
  • remote sensing
  • deciduous forests
  • precise monitoring
  • machine learning
  • big data analytics
  • multi-source remote sensing datasets

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Published Papers (1 paper)

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Research

21 pages, 13414 KiB  
Article
Estimation of Forest Phenology’s Relationship with Age-Class Structure in Northeast China’s Temperate Deciduous Forests
by Xiaoqing Zuo, Kaijian Xu, Wanwan Yu, Ping Zhao, Huaipeng Liu, Hailan Jiang, Anxin Ding and Yi Li
Forests 2024, 15(12), 2150; https://doi.org/10.3390/f15122150 - 5 Dec 2024
Viewed by 948
Abstract
Phenological changes in forests directly influence the spatiotemporal dynamics of carbon fixation and the carbon and water cycles in terrestrial ecosystems. Previous studies have shown that variations in biological factors (e.g., canopy height, leaf area, water use efficiency) can increase uncertainty in forest [...] Read more.
Phenological changes in forests directly influence the spatiotemporal dynamics of carbon fixation and the carbon and water cycles in terrestrial ecosystems. Previous studies have shown that variations in biological factors (e.g., canopy height, leaf area, water use efficiency) can increase uncertainty in forest phenology, and these variations are closely linked to tree species and forest age-class structure. However, the interaction mechanisms through which tree species and forest age-class structure influence phenological changes remain insufficiently explored. In this study, phenological changes and their interactions and response mechanisms to different dominant tree species and forest age-class structures were analyzed via Sentinel-2 normalized difference vegetation index (NDVI) time series data from 2020 and 2021 across 480 typical deciduous forest plots in northeastern China. The results were as follows: (1) There were significant differences (p < 0.05) in the intra-annual phenological responses of temperate deciduous landscapes to the interaction between tree species and forest age-class structure. (2) The indirect effect of forest age-class structure through tree species on phenology exceeded the indirect effect of tree species through forest age-class structure, with a difference of 30.77%–35.09%. (3) When the dominant tree species and forest age-class structure were not distinguished, phenological differences in temperate forests ranged from 3 to 41 days and 2 to 23 days, respectively. This study highlights the differential impacts of key biological factors and their interactions on regional forest phenology, offering valuable insights into how these factors influence forest landscapes and providing a theoretical basis for improving forest management strategies. Full article
(This article belongs to the Special Issue Vegetation and Remote Sensing Phenology in Deciduous Forests)
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