TITLE:
Research on the Optimal Vegetation Cover for Remote Sensing Assessment of Soil Erosion Risk Using the Temporal Matching Relationship between Rainfall and Vegetation
AUTHORS:
Jianfeng Liu, Xiwang Zhang
KEYWORDS:
Optimal Vegetation Cover, Remote Sensing, Soil Erosion Risk, Temporal Matching Relationship
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.7 No.2,
February
13,
2019
ABSTRACT: Vegetation cover derived from remote sensing image is widely used for soil
erosion risk assessment, but there is no clear guideline to select the most appropriate
temporal satellite data. It is common practice that satellite data
during growing season are randomly selected and used in soil erosion risk
assessment. However, the effectiveness of vegetation in protecting the soil is
quite different even if it is the same growing season since vegetation covers
change as they grow. This article aims to provide a method of choosing optimal
vegetation cover for studying soil erosion risk using remote sensing,
that is, the vegetation cover in the most appropriate temporal period. Based
on the temporal relationship of the two most active impact factors, rainfall
and vegetation, an index of RV is developed and used to indicate the relative
erosion risk during the year. The results show that annual variation of rainfall
is significant, and vegetation is relatively stable, resulting in their matching
relationship is different in each year. The correlation coefficient reaches 0.89
between RV and real sediment transport during the period when rainfall can
cause soil erosion. In other words, RV is a good indicator of soil erosion.
Therefore, there is a good correlation between RV maximum and the optimal
vegetation cover, which can help facilitate erosion research in the future,
showing good potential for successful application in other places.