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Forests
Special Issues
Monitoring Forest Change Dynamic with Remote Sensing
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Monitoring Forest Change Dynamic with Remote Sensing

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 December 2024 | Viewed by 5813

Special Issue Editors

Prof. Dr. Gilson Alexandre Ostwald Pedro da Costa

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Guest Editor
Department of Informatics and Computer Science, Institute of Mathematics and Statistics (IME), Rio de Janeiro State University (UERJ), Rio de Janeiro 20550-013, RJ, Brazil
Interests: pattern recognition for remote sensing; image analysis; remote sensing applications; change detection
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Raul Queiroz Feitosa

E-Mail Website
Guest Editor
Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro 22451-040, RJ, Brazil
Interests: pattern recognition for remote sensing; image analysis; remote sensing applications; change detection
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Veraldo Liesenberg

E-Mail Website
Guest Editor
Department of Forest Engineering, Santa Catarina State University (UDESC), Florianópolis 88035-901, SC, Brazil
Interests: remote sensing applications using AI; retrieval of biophysical properties using AI; environmental modeling; spatial data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Claudio Almeida

E-Mail Website
Guest Editor
Monitoring Program for Amazon and Other Biomes, Brazilian National Institute for Space Research (INPE), São José dos Campos, São Paulo 2337-010, SP, Brazil
Interests: monitoring of Brazilian biomes; land use land cover change; landscape analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forests are home to the majority of the species on Earth and deliver key ecological services, such as producing timber and freshwater, storing carbon, and regulating the climate. To preserve these services, along with the biodiversity supported by the natural habitats provided, understanding the dynamics associated with the degradation and preservation of forests is of utmost importance.

Forest dynamics are driven by physical and biological forces and by anthropogenic pressures that conform and alter such ecosystems. Climate change, for instance, has an important effect on forest dynamics, as changes in temperature and precipitation levels can directly impact the success of vegetation and animal species.

Forest disturbances may change the composition and structure of the related ecological systems. They comprise natural disasters such as floods, landslides, wildfire, windthrow, and insect or fungus outbreaks, as well as anthropogenic activities such as logging, urbanization, or agriculture. Forest succession refers to the process of recovering from the effects of disturbances. The type of disturbance, the climate conditions, and the interactions among the local species affect the succession process.

In short, to understand the current and future role of forests on our planet, we need to be able to assess, monitor, and model the dynamics of changes in vegetated areas, considering both disturbance and degeneration, as well as succession and regeneration processes.

In this Special Issue, we invite the submission of papers that approach all aspects of forest dynamics assessed with remote sensing systems and respective processing techniques, including, but not limited to:

  • Ecosystem and vegetation dynamics: disturbance and recovery, ecosystem fragmentation, forest degradation, regeneration, and changes in the composition of species and vulnerability;
  • Biogeophysics changes: energy, biomass, carbon fluxes, and water resources;
  • Anthropogenic pressures: deforestation, illegal logging and mining, agricultural and livestock farming, shifting cultivation, and urban sprawl.

Prof. Dr. Gilson Alexandre Ostwald Pedro da Costa
Prof. Dr. Raul Queiroz Feitosa
Prof. Dr. Veraldo Liesenberg
Dr. Claudio Almeida
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • forest and savanna ecosystem dynamics
  • land use dynamics
  • climate change
  • carbon stock
  • biogeophysical cycles
  • deforestation
  • forest degradation
  • forest regeneration
  • flooding
  • forest fire

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Published Papers (4 papers)

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Research

32 pages, 49926 KiB  
Article
What Are the Variation Patterns of Vegetation and Its Influencing Factors in China from 2000–2020 from the Partition Perspective?
by Bing Guo, Mei Xu, Rui Zhang, Wei Luo and Jicun Yang
Forests 2024, 15(8), 1409; https://doi.org/10.3390/f15081409 - 11 Aug 2024
Viewed by 959
Abstract
China’s vegetation ecosystem has undergone profound changes, and there is an urgent need to explore the mechanisms behind vegetation changes in different ecological sub-regions and historical periods across China. Based on NDVI (normalized difference vegetation index) data, this study analyzed the spatial and [...] Read more.
China’s vegetation ecosystem has undergone profound changes, and there is an urgent need to explore the mechanisms behind vegetation changes in different ecological sub-regions and historical periods across China. Based on NDVI (normalized difference vegetation index) data, this study analyzed the spatial and temporal evolution patterns and driving mechanisms of six ecological sub-regions in China. The results showed that: (1) over the past 20 years, the vegetation coverage in mainland China showed a decreasing trend from east to west. (2) Over the past 20 years, the vegetation coverage of the six ecological sub-regions showed an increasing trend, with the highest increase in Central Southern China (0.0039) and the lowest increase in East China (0.002). (3) The gravity center of Northeast China showed a trend of migration to the northwest. The gravity center of North China, East China, and Central South China showed a trend of migration to the southwest, while that of Northwest and Southwest China showed a trend of migration to the southeast. (4) During the period from 2000 to 2020, vegetation cover levels showed an upward trend. (5) The lag time of vegetation types in different regions was different. (6) Precipitation was the dominant influencing factor in the evolution of vegetation in Northeast China, North China, Northwest China, and Southwest China. The dominant influencing factors of vegetation evolution in East China were land use and GDP (gross domestic product), while the dominant influencing factors of vegetation evolution in Central South China were precipitation and land use. Full article
(This article belongs to the Special Issue Monitoring Forest Change Dynamic with Remote Sensing)
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17 pages, 14015 KiB  
Article
A New Remote Sensing Index for Forest Dryness Monitoring Using Multi-Spectral Satellite Imagery
by Thai Son Le, Bernard Dell and Richard Harper
Forests 2024, 15(6), 915; https://doi.org/10.3390/f15060915 - 24 May 2024
Viewed by 1080
Abstract
Canopy water content is a fundamental indicator for assessing the level of plant water stress. The correlation between changes in water content and the spectral reflectance of plant leaves at near-infrared (NIR) and short-wave infrared (SWIR) wavelengths forms the foundation for developing a [...] Read more.
Canopy water content is a fundamental indicator for assessing the level of plant water stress. The correlation between changes in water content and the spectral reflectance of plant leaves at near-infrared (NIR) and short-wave infrared (SWIR) wavelengths forms the foundation for developing a new remote sensing index, the Infrared Canopy Dryness Index (ICDI), to monitor forest dryness that can be used to predict the consequences of water stress. This study introduces the index, that uses spectral reflectance analysis at near-infrared wavelengths, encapsulated by the Normalized Difference Infrared Index (NDII), in conjunction with specific canopy conditions as depicted by the widely recognized Normalized Difference Vegetation Index (NDVI). Development of the ICDI commenced with the construction of an NDII/NDVI feature space, inspired by a conceptual trapezoid model. This feature space was then parameterized, and the spatial region indicative of water stress conditions, referred to as the dry edge, was identified based on the analysis of 10,000 random observations. The ICDI was produced from the combination of the vertical distance (i.e., under consistent NDVI conditions) from an examined observation to the dry edge. Comparisons between data from drought-affected and non-drought-affected control plots in the Australian Northern Jarrah Forest affirmed that the ICDI effectively depicted forest dryness. Moreover, the index was able to detect incipient water stress several months before damage from an extended drought and heatwave. Using freely available satellite data, the index has potential for broad application in monitoring the onset of forest dryness. This will require validation of the ICDI in diverse forest systems to quantify the efficacy of the index. Full article
(This article belongs to the Special Issue Monitoring Forest Change Dynamic with Remote Sensing)
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27 pages, 9981 KiB  
Article
Study on the Spatiotemporal Evolution and Influencing Factors of Forest Coverage Rate (FCR): A Case Study on Yunnan Province Based on Remote Sensing Image Interpretation
by Renyi Yang, Yimei He, Changbiao Zhong, Zisheng Yang, Xian Wang, Mingjun Xu and Linlin Cao
Forests 2024, 15(2), 238; https://doi.org/10.3390/f15020238 - 26 Jan 2024
Cited by 1 | Viewed by 1228
Abstract
The study of the forest coverage rate (FCR) is related to the ecological environment and sustainable development goals (SDGs) of a region. In light of the lack of an organic integration method of “spatiotemporal evolution, correlation analysis, and change prediction” and the lack [...] Read more.
The study of the forest coverage rate (FCR) is related to the ecological environment and sustainable development goals (SDGs) of a region. In light of the lack of an organic integration method of “spatiotemporal evolution, correlation analysis, and change prediction” and the lack of a methodology that integrates methods of “remote sensing (RS) and GIS, multi-phase LUCC, and construction of econometric models” in the research methods at present, this study focus on Yunnan, a typical border province located in China with a relatively fragile “innate” ecological environment, as the research area. Based on the interpretation of land use/land cover (LULC) data retrieved from seven periods RS images (1990, 1995, 2000, 2005, 2010, 2015, and 2020), the spatiotemporal evolution of FCR in 129 counties was analyzed. Complementary research methods, such as the spatial econometric model, geographically weighted regression (GWR), and the geographic detector (GD), are used to reveal the influencing factors of FCR. Finally, this study predicts the FCRs of 129 counties in Yunnan from 2025 to 2050. The FCR in Yunnan presents an increasing trend year by year, increasing from 28.96% in 1990 to 49.05% in 2020. In addition, it exhibits spatial agglomeration characteristics with fewer values in the east and more in the west. The analysis of influencing factors show that the increases in the per capita GDP, land utilization rate, and annual average temperature, and the implementation of the Conversion of Cultivated Land into Forest Project (CCFP) will significantly improve the FCR, while the increases in the population density land reclamation rate, the proportion of construction land area, and the proportion of soil erosion land area will significantly reduce the FCR. Furthermore, the FCR is influenced by multiple factors, and the relative factors observed not only show significant spatial differences, but also present complex and diverse patterns, with the additional characteristics of being interwoven and overlapping. This study contributes to expanding and improving the methods and pathways of exploring the spatiotemporal evolution characteristics of FCR in ecologically fragile areas using RS methods, providing a reference for increasing FCR and improving the ecological environment’s quality in Yunnan Province and other ecologically fragile areas. Full article
(This article belongs to the Special Issue Monitoring Forest Change Dynamic with Remote Sensing)
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20 pages, 4382 KiB  
Article
Analysis of Eco-Environmental Quality of an Urban Forest Park Using LTSS and Modified RSEI from 1990 to 2020—A Case Study of Zijin Mountain National Forest Park, Nanjing, China
by Fang Ren, Jiaoyang Xu, Yi Wu, Tao Li and Mingyang Li
Forests 2023, 14(12), 2458; https://doi.org/10.3390/f14122458 - 17 Dec 2023
Cited by 2 | Viewed by 1663
Abstract
Evaluating the long-term urban forest ecological environmental quality (EEQ) and analyzing the drivers of its spatiotemporal changes can provide a scientific basis for making long-term urban forest planning decisions. Taking into account the characteristics of urban forest parks with low area proportions of [...] Read more.
Evaluating the long-term urban forest ecological environmental quality (EEQ) and analyzing the drivers of its spatiotemporal changes can provide a scientific basis for making long-term urban forest planning decisions. Taking into account the characteristics of urban forest parks with low area proportions of construction land and bare land, high vegetation coverage, and serious forest disturbances, we constructed a modified urban forest park EEQ evaluation index based on a remote sensing ecological index named MRSEI, which is composed of the Landsat enhanced vegetation index (EVI), wetness, land surface temperature (LST), and forest disturbance index (FDI). We selected the Nanjing Zijin Mountain National Forest Park as the study area, used landsat time series stack (LTSS) remote sensing images from 1990 to 2020 as the main data source, and adopted the suggested modified MRSEI, the Theil-Sen median method, and the Hurst index to evaluate the EEQ to analyze its spatiotemporal variations and its driving factors in the study area. The main research results were as follows: (1) the EEQ of Zijin Mountain showed an up-and-down, overall slowly increasing trend from 1990 to 2020, while the spatial auto-correlation coefficient showed an overall decreasing trend; (2) the area percentage of the EEQ-persistent region accounted for 78.69%, and the anti-sustainable region accounted for 21.31%; (3) the spatial centers of the EEQ in the study area were mainly concentrated on the middle and upper part of the southern slope of Zijin Mountain, moving southward from 1990 to 2020; (4) the analysis of drivers showed that climate factors, forest landscape structure, forest disturbances, and forest growth conditions were the main driving factors affecting the EEQ in the study area. These results provide a research framework for the analysis of EEQ changes over a long-term period in the urban forest parks of China. Full article
(This article belongs to the Special Issue Monitoring Forest Change Dynamic with Remote Sensing)
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