Assessment of forest damage caused by an ice storm using multi-temporal remote-sensing images: a case study from Guangdong Province

Since the 21st century, China has experienced rapid development, and the spatial and temporal changes in vegetation cover have become increasingly significant. Southern China is a representative region for human activities, climate change, and vegetation change, but the current human understanding of the interactions between vegetation and its influencing factors is still very limited. In our study, we use NDVI as the vegetation greenness data, land cover data, temperature, precipitation, downgradient shortwave radiation, and CO2 data to investigate the interrelationship among vegetation, climate change, and human activities in southern China. The changes and their consistency were studied by trend analysis and Hurst exponent analysis. Then, the contribution of each influencing factor from 2001 to 2020 was quantified by random forest. The results showed that the vegetation in southern China showed an overall rising trend, and areas with a continuous changing trend were concentrated in the Pearl River Delta, western Guangdong, and eastern Guangdong, with a growth rate of 0.02∼0.04%. The vegetation in northern Guangdong did not change significantly. The main factor of NDVI spatial variation in southern China is the land-use factor, accounting for 79.4% of the variation, while climate factors produce further differences. The contributions and lagged effects of NDVI factors on different land-use types and the lagged effects of different climate factors are different and are related to the climate and vegetation background in Sourthern China. Our study is useful in estimating the contribution of NDVI change by each considered factor and formulating environmentally friendly regional development strategies and promoting human–land harmony.

Section: Dynamic Trend and Consistency Of Vegetation Greennesssupporting

confidence: 86%

Changes in Vegetation Greenness and Their Influencing Factors in Southern China

Zhao

et al. 2022

“…First, significant positive correlations between the NDVI and temperature were observed across most areas (Figure 5a) and temperature was the dominant climatic factor for 73.42% of the study area (Figure 6), especially the northern NG and East MG eco-regions, in line with previous studies [9,33]. These regions are mostly mountainous areas with higher latitudes and elevations, and the temperature is relatively low in comparison with other eco-regions (Figure 1d), so vegetation growth is more sensitive to low temperatures [61]. The increasing temperature is widely believed to prolong the growing season with an earlier spring and a delayed autumn [62,63], thus promoting vegetation greenness in these heat-limited regions.…”

Section: Vegetation Trends and Their Climatic Driverssupporting

confidence: 86%

Climatic and Anthropogenic Contributions to Vegetation Changes in Guangdong Province of South China

Geng,

Zhou,

Zhang

et al. 2023

How to distinguish the relative role of climate change and human activities in vegetation dynamics has attracted increasing attention. However, most of the current studies concentrate on arid and semiarid regions, while the relative contributions of climate change and human activities to vegetation changes remain unclear in warm-humid regions. Based on the normalized difference vegetation index (NDVI) and climatic variables (temperature, precipitation, radiation) during 2001–2020, this study used the Theil–Sen median trend analysis, partial correlation analysis, and residual trend analysis to analyze the spatiotemporal pattern of vegetation trends, the response of vegetation to climate variations, and the climatic and anthropogenic contributions to vegetation dynamics in the warm and humid Guangdong Province of south China. Results showed that the NDVI in most areas exhibited an increasing trend. Changes in climatic variables displayed different spatial variations which, however, were not significant in most areas. Vegetation responded diversely to climate change with temperature as the most important climatic factor for vegetation improvement in most areas, while precipitation was the dominant climatic factor in the southern edge region and radiation was the dominant climatic factor in the central and western regions. Vegetation in most areas was influenced by both climate change and human activities, but the contribution rate of human activities was commonly much higher than climate change. The findings of this study are expected to enhance our understanding of the relative climatic and anthropogenic contributions to vegetation changes in warm-humid regions and provide a scientific basis for future ecological policies and ecosystem management in highly urbanized regions.

“…Natural disasters, such as snowstorms, ice storms, earthquakes, landslides, tornadoes, volcanoes, hurricanes, and other types of disasters, affect natural ecosystems in complex and profound ways [1][2][3][4]. Forest ecosystems are particularly disturbed by such disasters, with the effects including the decline in tree density, loss of forest cover, and the change of biodiversity [5,6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China

Yao

et al. 2020

Ice storms greatly affect the structure, dynamics, and functioning of forest ecosystems. Studies on the impact of such disasters, as well as the post-disaster recovery of forests, are important contents in forest biology, ecology, and geography. Remote-sensing technology provides data and methods that can support the study of disasters at the large-to-medium scale and over long time periods. This study took Chebaling National Nature Reserve in Guangdong Province, China, as the study area. First, field-survey data and remote-sensing data were comprehensively analyzed to demonstrate the feasibility of replacing the forest stock volume with the mean annual value of the Enhanced Vegetation Index (EVI), to study forest growth and change. We then used the EVI from 2007 to 2017, together with a variety of other remote-sensing and forest sub-compartment data, to analyze the impact of the 2008 ice storm and the subsequent post-disaster recovery of the forest. Finally, we drew the following conclusions: (1) Topography had a considerable effect on disaster impact and forest recovery in Chebaling. The forest at high altitudes (700–1000 m) and on steep slopes (25–40°) was seriously affected by this disaster but had a stronger post-disaster recovery ability. Meanwhile, the hardest-hit area for coniferous forest was higher and steeper than that for broad-leaved forest. (2) In the same terrain conditions, coniferous forests were less affected by the disaster than broad-leaved forests and showed less variation during the post-disaster recovery process. Nevertheless, broad-leaved forests had faster recovery rates and higher recovery degrees; (3) Under the influence of human activities, the recovery and fluctuation degree for planted forest in the post-disaster recovery process was significantly higher than that for natural forest. The study suggests that forest has high disaster resistance and self-recovery ability after the ice storm, and this ability has a strong correlation with the type of forest and the topographic factors such as elevation and slope. At the same time, human intervention can speed up the recovery of forests after disasters.