Fractional Vegetation Cover Estimation of Different Vegetation Types in the Qaidam Basin

Siqi Zhang,Huihui Niu,Yi Yang,Boxiong Zhang,Yang Fu,Hui Chen

doi:10.3390/su11030864

Siqi Zhang, Huihui Niu + Show 4 more

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https://doi.org/10.3390/su11030864

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Journal: Sustainability	Publication Date: Feb 7, 2019
Citations: 41	License type: CC BY 4.0

Affiliation: Hebei Normal University

Abstract

The estimation of fractional vegetation cover (FVC) by using remote sensing images has become feasible. Based on Landsat8-OLI images and field data obtained from an unmanned aerial vehicle, we established an empirical model (EM) and a pixel decomposition model (PDM) of FVC in the desert vegetation region, steppe vegetation region, meadow vegetation region and mixed vegetation region (the three vegetation region types) of the Qaidam Basin, and the inversion accuracies of the models were compared. The results show the following: (1) Vegetation classification inversion (VCI) provides a promising approach for FVC estimation. The accuracy of FVC by VCI was obviously better than that achieved using vegetation mixed inversion (VMI); (2) Differences were observed in the FVC estimation between VCI and VMI by the EM in areas with relatively high-density vegetation cover (FVC > 60%). The FVC in some parts of steppe region in the basin was slightly overestimated by VMI of the EM; 3) VCI estimated by the PDM resulted in lower inversion values for extremely low-density vegetation cover (FVC ≤ 10%) and higher inversion values for high-density vegetation cover (FVC > 80%). The FVC inversion was underestimated by the PDM in steppe and meadow regions with FVC > 15% in the basin. The application of VCI in different models can provide new ideas for the sustainable study of vegetation in arid regions.

Highlights

Vegetation is a vital part of ecosystems and provides a link among the soil, atmosphere and moisture
The correlation between the normalized difference vegetation index (NDVI) and Fractional vegetation cover (FVC) was the most significant, and the linear regression was ideal (R2 > 0.7) for the desert, steppe and meadow regions in the Qaidam Basin, indicating that NDVI is more suitable for constructing an empirical model (EM) for FVC estimation
Differences were observed in the FVC estimation between VCI and VMI by the EM in the areas with relatively high-density vegetation cover, and differences in the FVC of pixel decomposition model (PDM) occurred in the areas with extremely low-density vegetation cover and high-density vegetation cover

Summary

Introduction

Vegetation is a vital part of ecosystems and provides a link among the soil, atmosphere and moisture. It plays an important role in the energy exchange of the land surface, the global biochemical cycle and the water cycle [1,2]. Fractional vegetation cover (FVC) is defined as the projected percentage of the total study area that is vegetated (roots, stems and leaves) [3]. The development of remote sensing technology has provided a promising tool for FVC estimation [10,11]. EM and PDM are used as basic approaches in most FVC studies based on remote sensing data [18,19]

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