The dynamics and main driving factors of coastal vegetation in Guangxi based on MODIS NDVI

Fangyan, 成方妍 Cheng; Shiliang, 刘世梁 Liu; Yijie, 尹艺洁 Yin; Yihe, 吕一河 Lü; Nannan, 安南南 An; Xinming, 刘昕明 Liu

doi:10.5846/stxb201509091866

Cited by 4 publications

(2 citation statements)

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“…In addition, human disturbance (grazing) was weakened, the wetland eco-hydrological environment improved, and consequently, the vegetation coverage gradually increased. There was a significant negative correlation between vegetation coverage and residential density (R 2 = −0.47, P < 0.01), which was consistent with Cheng's research conclusion (Cheng et al, 2017).…”

Section: Discussionsupporting

confidence: 88%

“…Remote sensing technology can overcome the limitations of a traditional community survey in temporal and spatial scales and complete the estimation of regional vegetation coverage. Most of the existing studies are based on different resolution and remote sensing imaging mechanisms, such as Landsat and MODIS (Okin et al, 2013;Cheng et al, 2017), GF-1 (Tao et al, 2019), radar (Liu L. et al, 2019), and other satellite data, to make estimates. However, few studies have combined wetland field surveys with remote sensing technology to describe patchy and spatial heterogeneity of vegetation coverage.…”

Section: Introductionmentioning

confidence: 99%

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Temporal and spatial characteristics of vegetation coverage and their influencing factors in the Sugan Lake wetland on the northern margin of the Qinghai–Tibet Plateau

Kang

Zhao

et al. 2023

Front. Ecol. Evol.

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Fractional vegetation cover (FVC) is an important indicator of the development or reversal of salt marsh due to its absence in arid desert areas. Many studies have emphasized the differences in factors that affect fractional vegetation cover (FVC) in different temporal and spatial scales. However, few studies have reported on the temporal and spatial variations in vegetation coverage and their response to climate and also on the hydrological environment in inland salt marsh wetlands. Accordingly, based on a wetland community survey, different types of data, such as meteorological data, hydrological data, and Landsat remote sensing image data, recorded during the period from 1990 to 2020 were collected. The characteristics of the spatial and temporal distribution of vegetation coverage in the Sugan Lake wetland over the past 30 years were analyzed using a binary pixel model. Furthermore, a quantitative analysis on the response of vegetation coverage to hydrological and meteorological factors was undertaken. The results of the present study showed that the dimidiate pixel model had a high simulation accuracy in retrieving the vegetation coverage in inland salt marsh wetlands. The vegetation coverage of the Sugan Lake wetland increased with each year from 1990 to 2020, and its annual average was 19.34%. The spatial distribution of vegetation coverage was patchy and decreased from the center to the edge of the wetland. Within the same period, the vegetation coverage showed an increasing trend in Quan-shui and He-hong areas and a decreasing trend in the Shan-hong area. Vegetation coverage was mainly affected by various factors, such as precipitation, lake area, surface runoff, groundwater depth, and residential density, respectively. It was significantly positively correlated with precipitation (R2 = 0.56, P < 0.01), lake area (R2 = 0.50, P < 0.01), air temperature (R2 = 0.46, P < 0.01), and river system density (R2 = 0.52, P < 0.01) and negatively correlated with groundwater depth (R2 =-0.57, P < 0.01) and residential density (R2 = −0.38, P < 0.05). Implicit in these findings are complex mechanisms of change in vegetation coverage that help prevent the degradation of vegetation in fragile ecosystems.

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Section: Discussionsupporting

confidence: 88%