Publication Details

Category Text Publication
Reference Category Journals
DOI 10.3390/rs12071136
Licence creative commons licence
Title (Primary) Quantifying the sensitivity of NDVI-based C factor estimation and potential soil erosion prediction using spaceborne Earth observation data
Author Ayalew, D.A.; Deumlich, D.; Ĺ arapatka, B.; Doktor, D.
Source Titel Remote Sensing
Year 2020
Department CLE
Volume 12
Issue 7
Page From art. 1136
Language englisch
Keywords C factor; Landsat 7; Landsat 8; Sentinel 2; soil erodibility; slope shape; soil erosion; IACS; Germany
Abstract 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 (Cndvi) estimation per se is sensitive to various biophysical variables, such as soil condition, topographic features, and vegetation phenology. As a result, Cndvi often results in incorrect values that affect the quality of soil erosion prediction. The aim of this study is to multi-temporally estimate Cndvi values and compare the values with those of literature values (Clit) 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 Cndvi 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 Cndvi and Clit improved in data from spring and summer seasons (up to r = 0.93); nonetheless, the Cndvi values were generally higher compared with Clit values. Consequently, modelling erosion using Cndvi resulted in two times higher rates than modelling with Clit. The Cndvi values were found to be sensitive to soil erodibility condition and slope shape of the landscape. Higher erodibility condition was associated with higher Cndvi values. Spring and summer taken images showed significant sensitivity to heterogeneous soil condition. The Cndvi estimation also showed varying sensitivity to slope shape variation; values on convex-shaped slopes were higher compared with flat slopes. Quantifying the sensitivity of Cndvi values to biophysical variables may help improve capturing spatiotemporal variability of C factor values in similar landscapes and conditions
Persistent UFZ Identifier
Ayalew, D.A., Deumlich, D., Ĺ arapatka, B., Doktor, D. (2020):
Quantifying the sensitivity of NDVI-based C factor estimation and potential soil erosion prediction using spaceborne Earth observation data
Remote Sens. 12 (7), art. 1136 10.3390/rs12071136