Quantifying the Sensitivity of NDVI-Based C Factor Estimation and Potential Soil Erosion Prediction using Spaceborne Earth Observation Data

• Main Authors: Dawit A. Ayalew, Detlef Deumlich, Bořivoj Šarapatka, Daniel Doktor
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Remote Sensing
• Subjects: C factor; Landsat 7; Landsat 8; Sentinel 2; soil erodibility; slope shape
• Online Access: https://www.mdpi.com/2072-4292/12/7/1136

The Normalized Difference Vegetation Index (NDVI), has been increasingly used to capture spatiotemporal variations in cover factor (C) determination for erosion prediction on a larger landscape scale. However, NDVI-based C factor (C_ndvi) estimation per se is sensitive to various biophysical variables, such as soil condition, topographic features, and vegetation phenology. As a result, C_ndvi often results in incorrect values that affect the quality of soil erosion prediction. The aim of this study is to multi-temporally estimate C_ndvi values and compare the values with those of literature values (C_lit) in order to quantify discrepancies between C values obtained via NDVI and empirical-based methods. A further aim is to quantify the effect of biophysical variables such as slope shape, erodibility, and crop growth stage variation on C_ndvi and soil erosion prediction on an agricultural landscape scale. Multi-temporal Landsat 7, Landsat 8, and Sentinel 2 data, from 2013 to 2016, were used in combination with high resolution agricultural land use data of the Integrated Administrative and Control System, from the Uckermark district of north-eastern Germany. Correlations between C_ndvi and C_lit improved in data from spring and summer seasons (up to <i>r</i> = 0.93); nonetheless, the C_ndvi values were generally higher compared with C_lit values. Consequently, modelling erosion using C_ndvi resulted in two times higher rates than modelling with C_lit. The C_ndvi values were found to be sensitive to soil erodibility condition and slope shape of the landscape. Higher erodibility condition was associated with higher C_ndvi values. Spring and summer taken images showed significant sensitivity to heterogeneous soil condition. The C_ndvi estimation also showed varying sensitivity to slope shape variation; values on convex-shaped slopes were higher compared with flat slopes. Quantifying the sensitivity of C_ndvi values to biophysical variables may help improve capturing spatiotemporal variability of C factor values in similar landscapes and conditions.