SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error, time-space decorrelation, atmospheric error, thereby improving the reliability of surface-deformation monitoring. This paper studies the early landslide identification method based on SBAS-InSAR technology. Selecting the Jiangdingya landslide area in Zhouqu County, Gansu Province as the research area, 84 ascending-orbit Sentinel-1A SAR images from 2015 to 2019 are collected. In addition, using SBAS-InSAR technology, the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted, and potential landslides are identified. The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas. 相似文献
ENSO is an interannual mode which may be affected by external forcing, such as volcanic eruptions. Based on the reconstructed volcanic eruptions chronology and ENSO sequences, both 195 large volcanic eruptions(VEI≥4) and 398 ENSO(El Ni?o and La Ni?a) events were extracted from 1525 to 2000. An analysis of the correspondence between the large volcanic eruptions and ENSO events was performed by matching the large volcanic eruptions with the types and magnitudes of ENSO events present in the 0–2 years after the eruptions. The results show the following:(1) The percentages of ENSO events within the 3 years after the large eruptions had increased to 68.3% from 31.7% compared with those with no-eruptions in the previous 0–2 years. In addition, the ratio of El Ni?o to La Ni?a events turned from 2:3 to 1:1, and more El Ni?o events occurred in the 0 year after eruptions in the low-latitudes of the Northern Hemisphere and in the tropics but more La Ni?a events occurred in the 0 year after in the high-latitudes of the Northern Hemisphere and the Southern Hemisphere.(2) After the eruptions, the weak(W) El Ni?o events had increased by 8 percentage points and the very strong(VS) El Ni?o events had decreased by 10 percentage points; conversely, there was a decrease by 15 percentage points of the weak La Ni?a events and an increase by 11.4 percentage points of the very strong La Ni?a events. Specifically, the percentages of strong La Ni?a events increased to a peak at 1(+1) year after the eruptions.(3) The percentage of eruptions followed by single-year ENSO was the greatest. The percentage of ENSO events that occurred in the consecutive 2 years following an eruption was approximately equal to the percentage of events that occurred consecutively 3 years following an eruption, and both sets of ENSO magnitudes showed a decreasing trend. 相似文献
A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.