Plant litter estimation and its correlation with sediment concentration in the Loess Plateau

Qian Li; Ligang Ma; Suhong Liu; Adilai Wufu; Yinbo Li; Shengtian Yang; Xiaodong Yang

doi:10.7287/peerj.preprints.27891v1

Plant litter estimation and its correlation with sediment concentration in the Loess Plateau

Qian Li¹, Ligang Ma ^1,2, Suhong Liu^3,4, Adilai Wufu¹, Yinbo Li¹, Shengtian Yang¹, Xiaodong Yang¹

1 College of Resource and Environmental Science, Xinjiang University, Urumqi, Xinjiang, China

2 General College Key Laboratory of Smart City and Environmental Modeling, Xinjiang University, Urumqi, Xinjiang, China

3 Faculty of Geographical Science, Beijing Normal University, Beijing, Beijing, China

4 Beijing Key Laboratory of Environmental Remote Sensing and Digital Cities, Beijing Normal University, Beijing, Beijing, China

DOI: 10.7287/peerj.preprints.27891v1

Published: 2019-08-10
Accepted: 2019-08-10

Subject Areas: Ecology, Ecosystem Science, Ecohydrology, Forestry, Spatial and Geographic Information Science
Keywords: multiscale, spatiotemporal, prediction, classification, upscaling

Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.

Cite this article: Li Q, Ma L, Liu S, Wufu A, Li Y, Yang S, Yang X. 2019. Plant litter estimation and its correlation with sediment concentration in the Loess Plateau. PeerJ Preprints 7:e27891v1 https://doi.org/10.7287/peerj.preprints.27891v1

Abstract

Background. Sediment concentration in the water of the loess Plateau region has dramatically decreased during the past two decades. Plant litter is considered to be one of the most important factors for this change. Existing remote sensing studies that focus on plant litter mainly use extraction methods based on vegetation indices or changes in the plant litter. Few studies have conducted time series analyses of plant litter or considered the correlation between plant litter and soil erosion. In addition, social factors are not given enough consideration in the remote sensing and soil community. Methods. This study performs time series estimation of plant litter by integrating three-scale remotely sensed data and a random forest (RF) modeling algorithm. Predictive models are used to estimate the spatially explicit plant litter cover for the entire Loess Plateau over the last two decades (2000–2018). Then, the sediment concentration in the water was classified into 9 grades based on environmental and social-economic factors. Results. Our results demonstrate the eﬀectiveness of the proposed predictive models at the regional scale. The areas with increased plant litter cover accounted for 67% of the total area, while the areas with decreased plant litter cover accounted for 33% of the total area. In addition, plant litter is demonstrated to be one of the top three factors contributing to the decrease in the river sediment concentration. Social-economic factors were also important for the decrease of the sediment concentration in the water, for example, the population of the rural area.

Author Comment

This is a submission to PeerJ for review.