The Wind-Sand Flux Structure of Grassland on the Northern Foot of Yinshan Mountain

2014 ◽  
Vol 668-669 ◽  
pp. 1530-1537
Author(s):  
Hong Tao Jiang ◽  
Chun Rong Guo ◽  
Chun Xing Hai ◽  
Shan Shan Sun ◽  
Yun Hu Xie ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Power Function ◽  
Exponential Function ◽  
Vertical Direction ◽  
Power Functions ◽  
Height Range ◽  
Sand Flux ◽  
Soil Flux ◽  
The Vertical Distribution ◽  
Better Than

Sand samplers were layed out in the grassland located in the northern foot of Yinshan Mountain for collecting soil flux samples from 0 to 1.5m height above the surface from Mar., 1, 2008 to Feb., 29, 2009.Exponential and Power functions were both used for describing vertical distribution of sand flux in the grassland, the results indicated that determination coefficient of Power function varied from 0.898 to 0.992 while 0.432 to 0.661 for exponential function. Power function is better than exponential function in describing the vertical distribution of both annual and seasonal soil flux, summer excluded. Annual cumulative percentage of each height was determined indirectly according to the power function mentioned above, the result indicated that up to 2m height,15-25% of soil flux concentrated with in 10cm above the surface,25-35% of soil flux concentrated within 20cm above the surface,30-40% of soil flux concentrated within 30 cm above the surface, 43-54% of soil flux concentrated within 50 cm above the surface,85-90% of soil flux concentrated within 150 cm above the surface, respectively. No significant differences of soil flux structures in spring, autumn, winter and in the whole year were found. The research on wind erosion of grassland in the vertical direction more dispersed, in the height range of sediment accumulated percentage was lower than that of the previous research.

Delving Deeper: Derivatives of Generalized Power Functions

2009 ◽  
Vol 102 (7) ◽  
pp. 554-557
Author(s):  
John M. Johnson
Keyword(s):  
Power Function ◽  
Exponential Function ◽  
Power Functions ◽  
Exponential Functions ◽  
First Semester ◽  
Derivatives Of

After several years of teaching multiple sections of first-semester calculus, it was easy for me to think that I had nothing new to learn. But every year and every class bring a new group of students with their unique gifts and insights. In a recent class, after covering the derivative rules for power functions and exponential functions, I asked the class about the derivative of a function like y = xsinx, which is neither a power function (the power is not constant) nor an exponential function (the base is not constant).

scholarly journals Long-term variation in aerosol lidar ratio in Shanghai based on Raman lidar measurements

2021 ◽  
Vol 21 (7) ◽  
pp. 5377-5391
Author(s):  
Tongqiang Liu ◽  
Qianshan He ◽  
Yonghang Chen ◽  
Jie Liu ◽  
Qiong Liu ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Particle Shape ◽  
Strong Dependence ◽  
Influence Factors ◽  
Raman Lidar ◽  
Height Range ◽  
Average Value ◽  
Variation Characteristics ◽  
Lidar Ratio ◽  
The Vertical Distribution

Abstract. Accurate lidar ratio (LR) and better understanding of its variation characteristics can not only improve the retrieval accuracy of parameters from elastic lidar, but also play an important role in assessing the impacts of aerosols on climate. Using the observational data of a Raman lidar in Shanghai from 2017 to 2019, LRs at 355 nm were retrieved and their variations and influence factors were analyzed. Within the height range of 0.5–5 km, about 90 % of the LRs were distributed in 10–80 sr with an average value of 41.0 ± 22.5 sr, and the LR decreased with the increase in height. The volume depolarization ratio (δ) was positively correlated with LR, and it also decreased with the increase in height, indicating that the vertical distribution of particle shape was one of the influence factors of the variations in LR with height. LR had a strong dependence on the original source of air masses. Affected by the aerosols transported from the northwest, the average LR was the largest, 44.2 ± 24.7 sr, accompanied by the most irregular particle shape. The vertical distribution of LR was affected by atmospheric turbidity, with the greater gradient of LR under clean conditions. The LR above 1 km could be more than 80 sr, when Shanghai was affected by biomass burning aerosols.

The vertical distribution of thin features over the Arctic analysed from CALIPSO observations. Part I: Optically thin clouds

Tellus B ◽  
2011 ◽  
Vol 63 (1) ◽  
Author(s):  
Abhay Devasthale ◽  
Michael Tjernström ◽  
Karl-Göran Karlsson ◽  
Manu Anna Thomas ◽  
Colin Jones ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
The Arctic ◽  
The Vertical Distribution

scholarly journals UAV Based Estimation of Forest Leaf Area Index (LAI) through Oblique Photogrammetry

2021 ◽  
Vol 13 (4) ◽  
pp. 803
Author(s):  
Lingchen Lin ◽  
Kunyong Yu ◽  
Xiong Yao ◽  
Yangbo Deng ◽  
Zhenbang Hao ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Point Cloud ◽  
Forest Canopy ◽  
Estimation Method ◽  
Vertical Direction ◽  
Estimation Accuracy ◽  
3D Point Cloud ◽  
Area Index ◽  
Better Than

As a key canopy structure parameter, the estimation method of the Leaf Area Index (LAI) has always attracted attention. To explore a potential method to estimate forest LAI from 3D point cloud at low cost, we took photos from different angles of the drone and set five schemes (O (0°), T15 (15°), T30 (30°), OT15 (0° and 15°) and OT30 (0° and 30°)), which were used to reconstruct 3D point cloud of forest canopy based on photogrammetry. Subsequently, the LAI values and the leaf area distribution in the vertical direction derived from five schemes were calculated based on the voxelized model. Our results show that the serious lack of leaf area in the middle and lower layers determines that the LAI estimate of O is inaccurate. For oblique photogrammetry, schemes with 30° photos always provided better LAI estimates than schemes with 15° photos (T30 better than T15, OT30 better than OT15), mainly reflected in the lower part of the canopy, which is particularly obvious in low-LAI areas. The overall structure of the single-tilt angle scheme (T15, T30) was relatively complete, but the rough point cloud details could not reflect the actual situation of LAI well. Multi-angle schemes (OT15, OT30) provided excellent leaf area estimation (OT15: R2 = 0.8225, RMSE = 0.3334 m2/m2; OT30: R2 = 0.9119, RMSE = 0.1790 m2/m2). OT30 provided the best LAI estimation accuracy at a sub-voxel size of 0.09 m and the best checkpoint accuracy (OT30: RMSE [H] = 0.2917 m, RMSE [V] = 0.1797 m). The results highlight that coupling oblique photography and nadiral photography can be an effective solution to estimate forest LAI.

scholarly journals Continuous borehole optical televiewing reveals variable englacial debris concentrations at Khumbu Glacier, Nepal

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Katie E. Miles ◽  
Bryn Hubbard ◽  
Evan S. Miles ◽  
Duncan J. Quincey ◽  
Ann V. Rowan ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Water Supply ◽  
Depth Profile ◽  
Variable Thickness ◽  
Surface Melting ◽  
High Mountain ◽  
Ablation Area ◽  
The Mean ◽  
Surface Melt ◽  
The Vertical Distribution

AbstractSurface melting of High Mountain Asian debris-covered glaciers shapes the seasonal water supply to millions of people. This melt is strongly influenced by the spatially variable thickness of the supraglacial debris layer, which is itself partially controlled by englacial debris concentration and melt-out. Here, we present measurements of deep englacial debris concentrations from debris-covered Khumbu Glacier, Nepal, based on four borehole optical televiewer logs, each up to 150 m long. The mean borehole englacial debris content is ≤ 0.7% by volume in the glacier’s mid-to-upper ablation area, and increases to 6.4% by volume near the terminus. These concentrations are higher than those reported for other valley glaciers, although those measurements relate to discrete samples while our approach yields a continuous depth profile. The vertical distribution of englacial debris increases with depth, but is also highly variable, which will complicate predictions of future rates of surface melt and debris exhumation at such glaciers.

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