## 3 Results and Discussion
### Analysis for Application in the Lubbusha Chromite Deposit  
The fractal surface variance statistical method was applied to the gravity anomaly of the Robusha chromite deposit, and its edge detection was carried out. The obtained fractal dimension maps of the four directions of the Robussa chromite gravity anomaly are  
Figure 7: The gravity and magnetic anomaly map of the study area. (**a**) Contour map of magnetic anomaly in the study area; (**b**) contour map of the gravity anomaly; (**c**) contour map of the residual gravity anomaly.  
shown in Figure 8a-d. It can be seen that they have an obvious directional distribution. Through directional calculations, some faults and geological interfaces in the northern part of the study area can be identified. The 2 mGal gravity anomaly contours used as the reference range for chromite deposits do not correspond well to the fractal dimension values. Furthermore, it is worth stating that deposits I, II, VI and V are distributed at different high values and cannot be confirmed by just one directional calculation. The high value of the maximum fractal dimension (Figure 8e) obtained by the fractal surface variance statistics method shows the complexity of the development of faults and geological structures in this area, and the range is larger than the high value of the average fractal dimension (Figure 8f). Deposits I, II, IV and V, as well as deposits exposed by boreholes and workings, are surrounded by high-depth contours. Because the fractal change law of damaged rocks can be inferred through fractal analysis, high-value fault development zones can be determined according to the self-similar law. Therefore, the macroscopic properties of the fault distribution can be determined by the fractal dimension. Figure 8f shows high values of dimensionality greater than 2.6, indicating the boundaries of geological bodies and fault development zones, with smoother contours than those shown in Figure 8e, showing more detail.  
Figure 8: Fractal dimension results of the research area. (**a**) S-N direction; (**b**) W-E direction; (**c**) WN-SE direction; (**d**) NE-SW direction; (**e**) the maximum fractal dimension; (**f**) the average fractal dimension.  
The above analysis shows that the fractal dimension of the fractal surface variance statistics method is more sensitive to the abnormal gradient area, and is suitable for edge detection. Due to the self-similarity and self-affinity of fractals, the maximum fractal dimension is the best dimension to explain the complexity of the geological structure and reduce the influence of the direction of grid calculation. High values of fractal dimension correspond to deposit boundaries or interfaces with significant density differences. To summarise, the fractal dimension indicator \"lightsup\" is located at the maximum gradient in the graph. Similarly, continuous stratigraphic regions with few faults correspond to low-value regions. The analysis yields more detailed information about the deposit, structure, and interface. Therefore, the fractal surface variance statistical method is an effective method to determine the geological structure and locate the ore area by using the gravity anomaly data in geological surveying and exploration.