Fractal Metrics and Connectivity Analysis for Forest and Deforestation Fragmentation Dynamics

Forests are critical ecosystems that regulate climate, preserve biodiversity, and support human livelihoods by providing essential resources. However, they are increasingly vulnerable due to the growing impacts of deforestation and habitat fragmentation, which endanger their value and long-term sustainability. Assessing forest and deforestation fragmentation is vital for promoting sustainable logging, guiding ecosystem restoration, and biodiversity conservation. This study introduces an advanced approach that integrates the Local Connected Fractal Dimension (LCFD) with near real-time (NRT) land use and land cover (LULC) data from the Dynamic World dataset (2017–2024) to enhance deforestation monitoring and landscape analysis. By leveraging high-frequency, high-resolution satellite imagery and advanced imaging techniques, this method employs two fractal indices, namely the Fractal Fragmentation Index (FFI) and the Fractal Fragmentation and Disorder Index (FFDI), to analyze spatiotemporal changes in the forest landscape and enhance deforestation monitoring, providing a dynamic, quantitative method for assessing forest fragmentation and connectivity in real time. LCFD provides a refined assessment of spatial complexity, localized connectivity, and self-similarity in fragmented landscapes, improving the understanding of deforestation dynamics. Applied to Nigeria’s Okomu Forest, the analysis revealed significant landscape transformations, with peak fragmentation observed in 2018 and substantial recovery in 2019. FFI and FFDI metrics indicated heightened disturbances in 2018, with FFDI increasing by 75.2% in non-deforested areas and 61.1% in deforested areas before experiencing rapid declines in 2019 (82.6% and 87%, respectively), suggesting improved landscape connectivity. Despite minor fluctuations, cumulative deforestation trends showed a 160.5% rise in FFDI from 2017 to 2024, reflecting long-term stabilization. LCFD patterns highlighted persistent variability, with non-deforested areas recovering 12% connectivity by 2024 after a 38% reduction in 2019. These findings reveal the complex interplay between deforestation and landscape recovery, emphasizing the need for targeted conservation strategies to enhance ecological resilience and connectivity. Fractal indices offer significant potential to generate valuable insights across multiple spatial scales, thereby informing strategies for biodiversity preservation and adaptive landscape management.

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Publication Details

Journal
Forests
Published
2025-02-11
DOI
https://doi.org/10.3390/f16020314
Citations
4
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
9.25

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article

Fractal Metrics and Connectivity Analysis for Forest and Deforestation Fragmentation Dynamics

Yumin Tan, Ahmed Wasiu Akande, Agus Suprijanto, Muhammad Kamran Lodhi et al.
4 citations
Forests
Ecology and Vegetation Dynamics Studies
9.25
article

Fractal Metrics and Connectivity Analysis for Forest and Deforestation Fragmentation Dynamics

Yumin Tan, Ahmed Wasiu Akande, Agus Suprijanto, Muhammad Kamran Lodhi, Isiaka Lukman Alage, Hamed Jimoh Olugbenga
article en
4 citations

Abstract

Forests are critical ecosystems that regulate climate, preserve biodiversity, and support human livelihoods by providing essential resources. However, they are increasingly vulnerable due to the growing impacts of deforestation and habitat fragmentation, which endanger their value and long-term sustainability. Assessing forest and deforestation fragmentation is vital for promoting sustainable logging, guiding ecosystem restoration, and biodiversity conservation. This study introduces an advanced approach that integrates the Local Connected Fractal Dimension (LCFD) with near real-time (NRT) land use and land cover (LULC) data from the Dynamic World dataset (2017–2024) to enhance deforestation monitoring and landscape analysis. By leveraging high-frequency, high-resolution satellite imagery and advanced imaging techniques, this method employs two fractal indices, namely the Fractal Fragmentation Index (FFI) and the Fractal Fragmentation and Disorder Index (FFDI), to analyze spatiotemporal changes in the forest landscape and enhance deforestation monitoring, providing a dynamic, quantitative method for assessing forest fragmentation and connectivity in real time. LCFD provides a refined assessment of spatial complexity, localized connectivity, and self-similarity in fragmented landscapes, improving the understanding of deforestation dynamics. Applied to Nigeria’s Okomu Forest, the analysis revealed significant landscape transformations, with peak fragmentation observed in 2018 and substantial recovery in 2019. FFI and FFDI metrics indicated heightened disturbances in 2018, with FFDI increasing by 75.2% in non-deforested areas and 61.1% in deforested areas before experiencing rapid declines in 2019 (82.6% and 87%, respectively), suggesting improved landscape connectivity. Despite minor fluctuations, cumulative deforestation trends showed a 160.5% rise in FFDI from 2017 to 2024, reflecting long-term stabilization. LCFD patterns highlighted persistent variability, with non-deforested areas recovering 12% connectivity by 2024 after a 38% reduction in 2019. These findings reveal the complex interplay between deforestation and landscape recovery, emphasizing the need for targeted conservation strategies to enhance ecological resilience and connectivity. Fractal indices offer significant potential to generate valuable insights across multiple spatial scales, thereby informing strategies for biodiversity preservation and adaptive landscape management.

ForestsVol. 16(2)
Zhejiang International Studies University (CN), University of Ilorin (NG), National Space Research and Development Agency (NG), Beihang University (CN)
Beihang University, China Scholarship Council
Openalex Percentile: Top 3%
Ecology and Vegetation Dynamics Studies
9.25
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