## 5 Results and Discussion
### Field Geological Verification  
Benefiting from the synergy of optical remote sensing and high spatial resolution imagery, the resulting lithological boundaries were acquired in a much shorter time compared to traditional geological surveys. Nevertheless, field-based geological mapping was still the backbone of the whole exploration procedure described in this study for verifying remote-sensing data. The integrated OLI-WV2 results were utilized for the first time in the Lubbusa area and proved their efficiency in lithological discrimination, as well as accurate detection of chrome-bearing peridotite and its spatially associated alteration. Fieldwork (field geology, field sampling, and field photos) as well as previous geological maps were used to validate remote sensing and machine learning results. Figure 13 shows the locations where the photos were taken for field verification. The sedimentary rocks exposed in the study area are mainly located in the north of the ophiolite belt, composed of a set of rocks including polymitic conglomerate, sandstone, and greywacke. The conglomerate had strong weathering resistance, large terrain fluctuations, and rough textures (Figure 14a). The sandstone mostly formed a one-sided mountain; it appeared as inclined rock layers. They had a lower density of water systems and underdeveloped vegetation (Figure 14b,j). The field inspection results are consistent with the visual interpretation results of the WV-2 remote-sensing images (Figure 4a,b). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Eigenvectors** & **Band 2** & **Band 4** & **Band 5** & **Band 6** & **Information** \\ \hline PC1 & \(-0.169\) & \(-0.348\) & \(-0.536\) & \(-0.750\) & 88.96\% \\ PC2 & \(-0.611\) & \(-0.618\) & \(-0.087\) & 0.487 & 9.71\% \\ PC3 & \(-0.390\) & \(-0.080\) & 0.801 & \(-0.447\) & 0.94\% \\ PC4 & \(-0.668\) & 0.700 & \(-0.252\) & 0.006 & 0.39\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Principal component analysis eigenvector matrix. Figure 12: Abnormal extraction using de-interfered anomalous principal component thresholding technique based on Landsat@ OLI. Figure 14: Field photographs showing the rock units of (**a**) contacts between peridotite and Tertiary Luobusa Formation; (**b**) contacts between harzburgite, conglomerate, and sandstone; (**c**) outcrop of slate; (**d**) outcrop of harzburgite, Tertiary Luobusa Formation, and slate in Kangjinla; (**e**) a block of harzburgite; (**f**) contacts between harzburgite and dunite; (**g**) the view of chromite by open pit; (**h**) underground chromite mining; (**i**) quartz veins inside listwanite. (**j**) sandstone. Figure 13: The OLI b5 image shows the field samples and figure locations in the study area. Currently, mining operations are still being carried out in the Luobusa mining area (Figure 14g,h). The chromite ore is mainly distributed in the harzburgite (Figure 15a,c-e). A clear contact boundary between dunite and harzburgite can be seen in the field (Figures 14f and 15g). The main rock-forming minerals of the two rocks are forsterite, and they have roughly similar spectral absorption characteristics. Therefore, they are uniformly identified as peridotite. The harzburgite has a blocky structure (Figure 14e), with severe surface weathering, and is mostly dark yellow-brown. The serpentinite peridotite is dark green in color, with obvious interpretation marks on the WV-2 true color image (Figure 6a,b). The gabbro was interlaced in veins (Figure 14f). Due to the later tectonic movement modification, the exposed range is not large and is difficult to identify on remote-sensing images. The linear features in the study area were enhanced by directional filtering (Figure 16b, scale 1:50,000) to interpret the tectonic structures. Meanwhile, according to mineralogical research, the cataclastic structure is widely developed in the southeastern part of the study area, which indicates that the rocks may have undergone relatively strong tectonic stress [34; 105].