Preprint Article Version 2 This version not peer reviewed

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

Version 1 : Received: 20 September 2017 / Approved: 21 September 2017 / Online: 21 September 2017 (04:27:48 CEST)
Version 2 : Received: 21 September 2017 / Approved: 21 September 2017 / Online: 21 September 2017 (16:33:49 CEST)

A peer-reviewed article of this Preprint also exists.

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. 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.

Journal reference: Remote Sens. 2017, 9, 1035
DOI: 10.3390/rs9101035

Abstract

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.

Subject Areas

farming-pasture ecotone; TM image; remote sensing; vegetation cover factor; scale conversion; land use; high resolution image

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.