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Forests · 2024 ·Vol. 15 ·期 7 ·1193 · IF 2.4

Influence of Slope Aspect and Position on Xylem Formation Dynamics in Subtropical Chinese Fir Plantations

Yingni Huang,Qianlin Li,Chunmei Bai,Wendi Zhao,Diego Ismael Rodríguez-Hernández,Xiali Guo

Recent studies on the intra-annual dynamics of trees were mainly focused on mature trees in natural forests; however, less is known about how topography (e.g., slope’s position and aspect) shape the intra-annual xylem formation dynamics of young trees in plantation forests. We monitored intra-annual xylem formation dynamics of 6-year-old Chinese fir (Cunninghamia lanceolata(Lamb.)) trees across two different aspects (northeast and southwest) and three different positions (upper, middle, and lower) of the slope in a planted forest in subtropical China. We found that the intra-annual xylem formation of trees on the northeast slope aspect (176.98 ± 34.52 cells) was significantly higher than that on the southwest slope aspect (140.19 ± 36.07 cells) due to the higher growth rate (0.67 ± 0.11 cells/day vs. 0.53 ± 0.10 cells/day). In the middle slope position, xylem formation (187.89 ± 19.81 cells) was also significantly higher than that of the upper (147.35 ± 29.08 cells) and lower slope positions (140.51 ± 48.36 cells), resulting from higher growth rate rather than longer growing season length. Our study demonstrated that intra-annual xylem formation dynamics of Chinese fir were altered by different topographic features and therefore encourage the implementation of management strategies that consider different slope aspects and positions to maximize forest productivity.

CAS / MDL: 1330-20-7 92-31-9
研究领域: 林学 · 生态学
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Landslides · 2019 ·Vol. 16 ·期 7 ·1313-1324 · IF 4.252

Using Sentinel-2 time series to detect slope movement before the Jinsha River landslide

Yang Wentao,Wang Yunqi,Sun Shao,Wang Yujie,Ma Chao

Detecting slope movement before landslides occur in mountain regions is crucial for disaster reduction. In October 2018, a gigantic landslide occurred on the Jinsha River, causing dammed-lake breach flood 500 km downstream. In this work, we used 25 Sentinel-2 images from November 2015 to August 2018 to explore the capability of this high temporal resolution optical images in detecting slope movement before the Jinsha River landslide. Normalized difference vegetation index (NDVI) was calculated to composite temporal profiles using all Sentinel-2 images. With this NDVI time series, unsupervised K-means classifier was applied to initially classify the study area and find the best thresholds for automatically extracting landslide scars in the image series. These extracted landslide scars were validated using interpreted results from two high spatial resolution images of similar dates in 2015 (user’s accuracy 89.7%, producer’s accuracy 83.6%) and 2018 (user’s accuracy 90.8%, producer’s accuracy 74.9%). After validation, extracted landslide scars of different years were counted and displayed in an RGB composite image to highlight slope movement. In addition, monotonous decrease/increase of NDVI was also observed, indicating continuous expansion of landslide scarps and movement of landslide head along the slope on the landslide surface. This work demonstrated the capability of Sentinel-2 time series images to capture slope movement with short revisit time at low cost. By incorporating other environmental information (such as elevation), this proposed method has the potential to consistently map pre-landslide slope movements over a large region.

研究领域: 遥感地质学 · 环境灾害监测 · 地理信息系统 · 山地灾害防治 · 地球观测
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