4.3. Analysis of Landslide Detection Results and Their Distribution in Gansu Province
We also validated the accuracy of the trained AttU-Net model on the validation set constructed from tracks 55 to 102. Ultimately, we used the trained model for landslide detection across the entirety of Gansu Province. Due to the large area of Gansu Province, the data from 26 tracks are required to cover the region completely. However, a substantial amount of descending orbit data was found to be missing upon retrieving the Sentinel-1A data. Therefore, only the ascending orbit data were collected for the automatic landslide detection task in Gansu Province. The final detection results are shown in
Figure 11, indicating that a significant number of landslides were distributed in the southern region of Gansu Province.
Landslides are primarily categorized by volume into small, medium, large, and gigantic. As we could not obtain the depth information of the landslides and could only classify them based on their areas, in this study, landslides with an area of less than 0.1 km2 were classified as small, those between 0.1 and 1 km2 were medium, those between 1 and 5 km2 were large, and those greater than 5 km2 were gigantic. According to this classification, we identified eight-hundred-and-ninety-five small landslides, eight-hundred-and-twenty-four medium landslides, one-hundred-and-fifty-five large landslides, and eight gigantic landslides. We also compiled statistics on the number of landslides in each city in Gansu Province. Gansu Province comprises 14 cities, but no significant landslides were detected in Jiayuguan City due to its flat terrain and relatively small area.
Among the 13 cities where landslides were detected, the Gannan Tibetan Autonomous Prefecture and Longnan City had the highest numbers of landslides. These two cities are located in the southern part of Gansu Province, where the tectonic activity is more pronounced, and the terrain is more variable, resulting in numerous landslides.
Figure 11a presents the distribution of all landslides throughout Gansu Province.
Figure 11b illustrates the distribution of micro-landslides within the same region.
Figure 11c displays the spatial distribution of medium-sized landslides.
Figure 11d shows the locations of large and very large landslides. Lastly,
Figure 11e categorizes the landslides of different scales across the 13 cities. It shows that most landslides in the Gannan Tibetan Autonomous Prefecture and Longnan City range from small- to medium-sized landslides, with the latter being more prevalent. Conversely, small landslides predominate in the cities of Qingyang, Wuwei, and Zhangye.
The elevation in Gansu Province ranges from 500 to 6000 m, with higher elevations in the east and lower elevations in the west.
Figure 12a illustrates the correlation between the landslide distribution identified by the model and the elevation data. In
Figure 12b, we show the corresponding distribution of micro-landslides in Gansu Province.
Figure 12c presents the corresponding distribution of medium-sized landslides. Finally,
Figure 12d displays the elevation locations for large and very large landslides. A significant number of landslides are in the southern and eastern regions of Gansu Province, where the terrain is more variable. The elevation distribution of the identified landslides was statistically analyzed and is shown in
Figure 12e.
The majority of the landslides were found at elevations between 1000 and 2000 m. There were relatively fewer landslides at elevations between 2000 and 3000 m, but a substantial number were also present at elevations between 3000 and 4000 m. However, there were not many landslides at elevations above 4500 m.
A significant concentration of landslides was found in the southern part of Gansu Province. Although this area features more pronounced terrain variations, its elevation primarily ranges between 1000 and 3000 m. Notably, the western part of the Gannan Tibetan Autonomous Prefecture and the southern part of Longnan City contained the highest density of landslides, with elevations predominantly between 1000 and 3000 m.
In contrast, the numerous landslides at elevations between 3000 and 4000 m were primarily located in the southern part of Jiuquan City and the western part of the Gannan Tibetan Autonomous Prefecture. The landslides at elevations greater than 4500 m were mainly found in the southernmost part of Jiuquan City, although they were uncommon.
Slopes are a significant factor in the development of landslide hazards. When a slope is not steep, the probability of failure is minimal. Conversely, rocks and soil become unstable when a slope is very steep. This paper analyzed the slope information of the 1882 identified landslides as shown in
Figure 13.
Figure 13a presents the slope information for Gansu Province, highlighting that the southern part of the province has relatively steep slopes. In
Figure 13b, we display the distribution of micro-landslides in Gansu Province.
Figure 13c illustrates the distribution of medium-sized landslides. Finally,
Figure 13d shows the spatial distribution of large and very large landslides. Additionally, the region along the eastern border with Qinghai Province also features steep slopes. The landslides identified by the model were primarily distributed in these steep-sloped areas. The statistical results in
Figure 13e further illustrate that the majority of the landslides were found on slopes ranging from 20° to 40°, with the highest concentration at around 40°.
This study used only ascending orbit data to detect the landslides in Gansu Province. Since the ascending orbit data captured images from southeast to northwest, and InSAR is highly sensitive to line-of-sight deformation, we investigated whether using a single orbit might have impacted the identification results and analyzed the directional information of these landslides as shown in
Figure 14.
Figure 14a presents the aspect information for Gansu Province while
Figure 14e shows the number of landslides across eight different aspects. In
Figure 14b, we display the distribution of micro-landslides in Gansu Province.
Figure 14c illustrates the distribution of medium-sized landslides. Finally,
Figure 14d shows the spatial distribution of large and very large landslides. The results indicate that the numbers of landslides identified by the model were significantly higher in the northeastern and eastern directions compared to the other six directions. This was primarily due to the ascending orbit data having an azimuth angle of approximately −15°, making them more sensitive to deformations in the northeastern and eastern directions. In contrast, detecting deformations in the flight direction was more challenging.
Figure 14a shows that the slopes facing the north are mainly distributed in the northern part of Gansu Province, where a large number of landslides were not detected.
