Assessing the impact of storm surge flooding on coastal pine forests using a vegetation index

Niwa, Hideyuki; Kamada, Masao; Morisada, Sin; Ogawa, Midori

doi:10.1007/s11355-022-00525-7

Cited by 5 publications

(1 citation statement)

References 16 publications

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“…For example, while traditional methods for vegetation coverage research, such as spatio-temporal analysis and geostatistical methods, have been widely adopted, they also have certain limitations. The implementation of these methods is limited by topography and other natural conditions, resulting in difficult data acquisition, high time cost, and low efficiency [25][26][27]. In recent years, there have been fast advancements in remote sensing technology, and the Google Earth Engine platform (GEE) has given researchers a strong tool for quickly accessing, processing, and analyzing data on vegetation coverage worldwide.…”

Section: Introductionmentioning

confidence: 99%

Response of Vegetation Coverage to Climate Drivers in the Min-Jiang River Basin along the Eastern Margin of the Tibetan Plat-Eau, 2000–2022

Liu,

Gu,

Wang

et al. 2024

Forests

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Ecological zonation research is typically conducted in the eastern margin of the Tibetan Plateau. In order to enhance the structure and function of regional ecosystems and monitor their quality, it is crucial to investigate shifts in the coverage of vegetation and the factors that contribute to these shifts. The goal of this study is to assess the spatial and temporal variations in vegetation covering and the partitioning of its drivers in the Minjiang River Basin on the eastern edge of the Tibetan Plateau between 2000 and 2022. The Mann-Kendall test, Hurst index, Theil-Sen median trend analysis, and other techniques were used to look at the features of temporal and geographical changes in regional vegetation coverage as well as potential development trends. The climatic influences leading to the spatial differentiation of vegetation NDVI (Normalized Difference Vegetation Index) were quantified through partial and complex correlation analyses of NDVI with temperature and precipitation. The results of the study showed that (1) the NDVI of the watershed performed well with a stable upward trend, indicating that the vegetation growth was generally good; (2) the spatial analysis showed that the coefficient of variation of the NDVI reached 0.092, which highlighted the stability of the vegetation change in the region; (3) the future development trend of the vegetation coverage in the watershed is low, and there is a certain degree of ecological risk; and (4) the main driver of the vegetation coverage is the non-climate factor, distributed in most parts of the watershed; (5) the climate driver shows localized influence, especially concentrated in the southwest, downstream and part of the upstream areas of the watershed.

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Section: Introductionmentioning

confidence: 99%