Historical Dynamic Mapping of Eucalyptus Plantations in Guangxi during 1990–2019 Based on Sliding-Time-Window Change Detection Using Dense Landsat Time-Series Data

Li, Yiman; Liu, Xiangnan; Liu, Meiling; Wu, Ling; Zhu, Lihong; Huang, Zhi; Xue, Xiaojing; Tian, Lingwen

doi:10.3390/rs16050744

Cited by 5 publications

(2 citation statements)

References 56 publications

(86 reference statements)

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“…Land cover was mapped after obtaining NDVI images of the study area for 1989, 2003, 2010, and 2022. NDVI method offers several advantages for land cover mapping, including being more sensitive to vegetation (Patil et al, 2024;Li et al, 2024). Using this index, it becomes possible to differentiate areas with dense vegetation from those with sparse levels (Alexandre et al, 2024).…”

Section: Land Usementioning

confidence: 99%

Tourism Investment and Land Use Change in the Northern Piedmont of the Western High Atlas (1989-2022)

Ait Zamzami,

Elaanzouli,

Zahrani

et al. 2024

For. Geo.

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This study aimed to investigate the profound influence of tourism investment on the Northern Piedmont of the western High Atlas over 34 years in response to the escalating global trend of tourism-driven land-use changes, particularly in the Marrakesh region. In this context, the driving forces behind the significant transformation of agricultural land and bare soils into tourism-driven investments were evaluated as well as the critical role of accessibility in shaping spatial shifts. The method used high-resolution (10 m) satellite images from Spot 1 (1989), Spot 5 (2003 & 2010), and Sentinel 2 (2022) through remote sensing methods to investigate the historical land-use changes over 34 years. The results showed significant transformations in land-use based on the correlation between improved transportation infrastructure and the growth of tourism ventures, underscoring the role of roads and facilities as catalysts. The analysis suggested the need for reflection on the consequences of unregulated tourism growth, aiming to balance economic benefits with environmental and socio-cultural challenges in sensitive regions. Although tourism significantly contributed to economic development and employment opportunities, it also posed risks when not managed prudently. This underscored the need to strike a harmonious equilibrium between economic prosperity as well as preserving the unique natural beauty and cultural heritage of the region. The insights provided in this analysis had broader implications for responsible planning and management of tourism development in sensitive ecological and cultural regions. In conclusion, a thoughtful and sustainable approach was needed to safeguard the delicate balance between economic prosperity and environmental preservation.

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Section: Land Usementioning

confidence: 99%

Tourism Investment and Land Use Change in the Northern Piedmont of the Western High Atlas (1989-2022)

Ait Zamzami,

Elaanzouli,

Zahrani

et al. 2024

For. Geo.

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“…However, removing misclassified pixels depends on the window size [41]. This method is applied in various studies, including the analysis of eucalyptus plantation [42], change detection on the Earth's surface [43], and the dynamic inference of airport flight ground service networks [44].…”

Section: Introductionmentioning

confidence: 99%

Background Subtraction for Dynamic Scenes Using Gabor Filter Bank and Statistical Moments

Romero-González,

Córdova-Esparza,

Terven

et al. 2024

Algorithms

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This paper introduces a novel background subtraction method that utilizes texture-level analysis based on the Gabor filter bank and statistical moments. The method addresses the challenge of accurately detecting moving objects that exhibit similar color intensity variability or texture to the surrounding environment, which conventional methods struggle to handle effectively. The proposed method accurately distinguishes between foreground and background objects by capturing different frequency components using the Gabor filter bank and quantifying the texture level through statistical moments. Extensive experimental evaluations use datasets featuring varying lighting conditions, uniform and non-uniform textures, shadows, and dynamic backgrounds. The performance of the proposed method is compared against other existing methods using metrics such as sensitivity, specificity, and false positive rate. The experimental results demonstrate that the proposed method outperforms other methods in accuracy and robustness. It effectively handles scenarios with complex backgrounds, lighting changes, and objects that exhibit similar texture or color intensity as the background. Our method retains object structure while minimizing false detections and noise. This paper provides valuable insights into computer vision and object detection, offering a promising solution for accurate foreground detection in various applications such as video surveillance and motion tracking.

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Developing a New Method to Rapidly Map Eucalyptus Distribution in Subtropical Regions Using Sentinel-2 Imagery

Tang,

Jiang,

et al. 2024

Forests

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Eucalyptus plantations with fast growth and short rotation play an important role in improving economic conditions for local farmers and governments. It is necessary to map and update eucalyptus distribution in a timely manner, but to date, there is a lack of suitable approaches for quickly mapping its spatial distribution in a large area. This research aims to develop a uniform procedure to map eucalyptus distribution at a regional scale using the Sentinel-2 imagery on the Google Earth Engine (GEE) platform. Different seasonal Senstinel-2 images were first examined, and key vegetation indices from the selected seasonal images were identified using random forest and Pearson correlation analysis. The selected key vegetation indices were then normalized and summed to produce new indices for mapping eucalyptus distribution based on the calculated best cutoff values using the ROC (Receiver Operating Characteristic) curve. The uniform procedure was tested in both experimental and test sites and then applied to the entire Fujian Province. The results indicated that the best season to distinguish eucalyptus forests from other forest types was winter. The composite indices for eucalyptus–coniferous forest separation (CIEC) and for eucalyptus–broadleaf forest separation (CIEB), which were synthesized from the enhanced vegetation index (EVI), plant senescing reflectance index (PSRI), shortwave infrared water stress index (SIWSI), and MERIS terrestrial chlorophyll index (MTCI), can effectively differentiate eucalyptus from other forest types. The proposed procedure with the best cutoff values (0.58 for CIEC and 1.29 for CIEB) achieved accuracies of above 90% in all study sites. The eucalyptus classification accuracies in Fujian Province, with a producer’s accuracy of 91%, user’s accuracy of 97%, and overall accuracy of 94%, demonstrate the strong robustness and transferability of this proposed procedure. This research provided a new insight into quickly mapping eucalyptus distribution in subtropical regions. However, more research is still needed to explore the robustness and transferability of this proposed method in tropical regions or in other subtropical regions with different environmental conditions.

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Historical Dynamic Mapping of Eucalyptus Plantations in Guangxi during 1990–2019 Based on Sliding-Time-Window Change Detection Using Dense Landsat Time-Series Data

Cited by 5 publications

References 56 publications

Tourism Investment and Land Use Change in the Northern Piedmont of the Western High Atlas (1989-2022)

Tourism Investment and Land Use Change in the Northern Piedmont of the Western High Atlas (1989-2022)

Background Subtraction for Dynamic Scenes Using Gabor Filter Bank and Statistical Moments

Developing a New Method to Rapidly Map Eucalyptus Distribution in Subtropical Regions Using Sentinel-2 Imagery

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