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Addendum: Bian, Z. et al. A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index. Remote Sens. 2017, 9, 780
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Remote Sens. 2017, 9(10), 1035; https://doi.org/10.3390/rs9101035

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

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State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
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College of Geography and Environmental Sciences, Zhejiang Normal University, Zhejiang 321004, China
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Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China
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Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
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College of Life Science & Technology, Hebei Normal University of Science & Technology, Qinhuangdao 066000, China
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Key Laboratory of Environmental Change and Natural Disaster, MOE, Beijing Normal University, Beijing 100875, China
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Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China
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Remote Sensing Application & Environmental Disaster Research Center, Zhejiang Normal University, Zhejiang 321004, China
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Author to whom correspondence should be addressed.
Received: 18 August 2017 / Revised: 26 September 2017 / Accepted: 8 October 2017 / Published: 11 October 2017
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Abstract

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate the C factor at a regional scale cannot directly use the C factor formula. That is because the C factor formula is obtained by experiments, and needs the coverage ratio data of croplands, woodlands, and grasslands at a 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. The 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, and takes the C factor formula obtained from the standard plot experiment and applies it to a 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 a large scale and provide strong support for regional soil and water conservation planning. View Full-Text
Keywords: farming-pasture ecotone; TM image; remote sensing; vegetation cover factor; scale conversion; land use; high resolution image farming-pasture ecotone; TM image; remote sensing; vegetation cover factor; scale conversion; land use; high resolution image
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Lin, D.; Gao, Y.; Wu, Y.; Shi, P.; Yang, H.; Wang, J. 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. Remote Sens. 2017, 9, 1035.

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