scholarly journals A Conversion Method to Determine the Regional Vegetation Cover Factor from Standard Plots Based on Large Sample Theory and TM Images: A Case Study in the Eastern Farming-Pasture Ecotone of Northern China

2017 ◽  
Vol 9 (10) ◽  
pp. 1035 ◽  
Author(s):  
Degen Lin ◽  
Yuan Gao ◽  
Yaoyao Wu ◽  
Peijun Shi ◽  
Huiming Yang ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Northern China ◽  
Cover Factor ◽  
Large Sample ◽  
Conversion Method ◽  
Large Sample Theory

scholarly journals A Conversion Method to Determine Regional Vegetation Cover Factor from Standard Plots based on Large Sample Theory and TM Images: A Case Study in the Eastern Farming-pasture Ecotone of Northern China

2017 ◽  
Author(s):  
Degen Lin ◽  
Yuan Gao ◽  
Yaoyao Wu ◽  
Peijun Shi ◽  
Huiming Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Vegetation Cover ◽  
Regional Scale ◽  
Strong Support ◽  
Vegetation Coverage ◽  
Large Sample ◽  
Coverage Ratio ◽  
Conversion Method ◽  
Large Sample Theory

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate C factor at regional scale cannot directly use the C factor formula. That is because the C factor formula is obtained by experiment, and needs the coverage ratio data of croplands, woodlands and grasslands at standard plot scale. In this paper, we present a C factor conversion method from a standard plot to a km-sized grid based on large sample theory and multi-scale remote sensing. Results show that: 1) Compared with the existing C factor formula, our method is based on the coverage ratio of croplands, woodlands and grasslands on a km-sized grid, takes the C factor formula obtained from the standard plot experiment and applies it to regional scale. This method improves the applicability of the C factor formula, and can satisfy the need to simulate soil erosion in large areas. 2) The vegetation coverage obtained by remote sensing interpretation is significantly consistent (paired samples t-test, t = −0.03, df = 0.12, 2-tail significance p < 0.05) and significantly correlated with the measured vegetation coverage. 3) The C factor of the study area is smaller in the middle, southern and northern regions, and larger in the eastern and western regions. The main reason for that is the distribution of woodlands, the Hunshandake and Horqin sandy lands and the valleys affected by human activities. 4) The method presented in this paper is more meticulous than the C factor method based on the vegetation index, improves the applicability of the C factor formula, and can be used to simulate soil erosion on large scale and provide strong support for regional soil and water conservation planning.

scholarly journals A Conversion Method to Determine Regional Vegetation Cover Factor from Standard Plots based on Large Sample Theory and TM Images: A Case Study in the Eastern Farming-pasture Ecotone of Northern China

2017 ◽  
Author(s):  
Degen Lin ◽  
Yuan Gao ◽  
Yaoyao Wu ◽  
Peijun Shi ◽  
Huiming Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Vegetation Cover ◽  
Regional Scale ◽  
Strong Support ◽  
Vegetation Coverage ◽  
Large Sample ◽  
Coverage Ratio ◽  
Conversion Method ◽  
Large Sample Theory

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate C factor at regional scale cannot be directly using the C factor formula. That is because the C factor formula obtain by experiment, and need the coverage ratio data of croplands, woodlands and grasslands at standard plot scale. In this paper, we present a C factor conversion method from a standard plot to a km-sized grid based on large sample theory and multi-scale remote sensing. Results show that: 1) Compared with the existing C factor formula, our method is based on the coverage ratio of croplands, woodlands and grasslands on a km-sized grid, takes the C factor formula obtained from the standard plot experiment and applies it to regional scale. This method improves the applicability of the C factor formula, and can satisfy the need to simulate soil erosion in large areas. 2) The vegetation coverage obtained by remote sensing interpretation is significantly consistent (paired samples t-test, t = −0.03, df = 0.12, 2-tail significance p < 0.05) and significantly correlated with the measured vegetation coverage. 3) The C factor of the study area is smaller in the middle, southern and northern regions, and larger in the eastern and western regions. The main reason for that is the distribution of woodlands, the Hunshandake and Horqin sandy lands and the valleys affected by human activities. 4) The method presented in this paper is more meticulous than the C factor method based on the vegetation index, improved the applicability of the C factor formula, and can be used to simulate soil erosion on large scale and provide strong support for regional soil and water conservation planning.

Changes in the vegetation cover of transgressive dune fields: A case study in Cape Woolamai, Victoria

2021 ◽  
Author(s):  
Jinjuan Gao ◽  
David M. Kennedy ◽  
Teresa M. Konlechner ◽  
Sarah McSweeney ◽  
Andre Chiaradia ◽  
...  
Keyword(s):  
Vegetation Cover
Sign in / Sign up

Export Citation Format

Share Document