Extraction of rocky desertification information in karst area by using different multispectral sensor data and multiple endmember spectral mixture analysis method

Abstract

As a typical form of land degradation, karst rocky desertification seriously restricts the development of the regional social economy and seriously threatens the living environment of residents. Fractional vegetation cover (fVC) and bare rock fraction (fBR) are important indicators to identify and evaluate rocky desertification. However, it is a great challenge to obtain fVC and fBR due to the complex terrain and fragmentation of karst rocky desertification areas. In this study, comparisons between Sentinel-2A Multispectral Instrument (Sentinel-2), Landsat-8 Operational Land Imager (Landsat-8), and GF-6 Wide Field View (GF-6) sensors for retrieving fVC and fBR are presented. The multiple endmember spectral mixture analysis (MESMA) and measured spectral dates were used to overcome the limitations of Spectral mixture analysis (SMA). Subsequently, fVC and fBR were validated using root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The results showed that: 1) Sentinel-2 performed best in estimating fVC and obtained the highest accuracy (R2 = 0.6259, root mean square error = 0.1568, mean absolute error = 0.1215), followed by GF-6 and Landsat 8; in the extraction of the fBR, the performance was relatively the same, and the implementation of Sentinel-2 was also the best (R2 = 0.4911, root mean square error = 0.0714, mean absolute error = 0.0539), followed by GF-6 and Landsat 8. 2) Sentinel-2 images have higher resolution, the narrowest band range, and the most significant number of bands, which can better extract information about fVC and fBR in rocky desertification areas. 3) For the three optical sensors, the spatial resolution of the images is more important to extract the information of fVC and fBR in the rocky desertification areas. 4) In general, the extraction accuracy of fBR is not as good as that of fVC. The complicated ecological and geological environment of decertified areas has more influence on the effect of extraction of the fBR. 5) The Sentinel-2 achieves high accuracy for both fVC and fBR under different-level application scenarios. It thus has great potential for application in rocky desertification information extraction.