Remote sensing estimation of the soil erosion cover‐management factor for China's Loess Plateau

Bibliographic Data

ID21649043
AuthorsXihua Yang (0000-0002-5990-2186, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation Northwest A & F University Yangling Shaanxi PR China), Xiaoping Zhang (0000-0003-0995-4989, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation Northwest A & F University Yangling Shaanxi PR China, corresponding author), Du Lv (State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation Northwest A & F University Yangling Shaanxi PR China), Shuiqing Yin (0000-0001-6914-6006, School of Geography Beijing Normal University Beijing PR China), Mingxi Zhang (0000-0003-2840-0885, School of Life Sciences, Faculty of Science University of Technology Sydney Australia), Qinggaozi Zhu (0000-0002-2371-4626, New South Wales Department of Primary Industry Parramatta New South Wales Australia), Qiang Yu (0000-0002-0695-1603, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation Northwest A & F University Yangling Shaanxi PR China), Baoyuan Liu (0000-0002-2479-260X, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation Northwest A & F University Yangling Shaanxi PR China)
Year2020
Volume31
Issue15
Pages1942-1955
Publication date2020-09-01
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.3577
OpenAlexW3005769156
LanguageEN
Citations received4
References cited38

The cover‐management factor (C‐factor) is used in the revised universal soil loss equation to represent the effect of vegetation cover and its management practices on hillslope erosion. Remote sensing has been widely used to estimate vegetation cover and the C‐factor, but most previous studies only used the photosynthetic vegetation (PV) or green vegetation indices (VI, e.g., normalized difference VI) for estimating the C‐factor and the important non‐PV (NPV) component was often ignored. In this study, we developed a new technique to estimate monthly time‐series C‐factor using the fractional vegetation cover (FVC) including both PV and NPV, and weighted by monthly rainfall erosivity ratio. The monthly FVC was derived from the moderate resolution imaging spectroradiometer and LANDSAT data with field validation. We conducted the case‐study over China's Loess Plateau and analysed the spatiotemporal variations of FVC and the C‐factor and their impacts on erosion over the Plateau. Our study reveals a significant increase in total vegetation cover (TC) from 56 to 76.8%, with a mean of 71.2%, resulting in about 20% decrease in the C‐factor and erosion risk during the 17‐year period. Our method has an advantage in estimating the C‐factor from TC at a monthly scale providing a basis for continuously and consistently monitoring of vegetation cover, erosion risk and climate impacts

Climate change · Enhanced vegetation index · Erosion · Geography · Geomorphology · Loess · Loess plateau · Moderate-resolution imaging spectroradiometer · Normalized Difference Vegetation Index · Physical geography · Remote sensing · Soil loss · Universal Soil Loss Equation · Vegetation Index · Environmental Science · Mathematics · Plant Water Relations and Carbon Dynamics · Remote Sensing in Agriculture · Soil erosion and sediment transport · Geology · Soil Science

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