<div style="text-align:justify;"> This research is based on Landsat5 TM, Landsat8 OLI/TIRS remote sensing data using RSEI model to analyze and monitor the ecological environment and its temporal and sp...<div style="text-align:justify;"> This research is based on Landsat5 TM, Landsat8 OLI/TIRS remote sensing data using RSEI model to analyze and monitor the ecological environment and its temporal and spatial changes in the forest-grass transition zone in Northeast China from 2004 to 2019. The change characteristics of the ecological environment of different types of land cover types are monitored by RSEI method, and the response of different land cover types to natural factors such as precipitation and temperature is analyzed at the same time. The distribution of RSEI in the study area presents the characteristics of high in the east and low in the west. The eastern mountainous area is densely covered with woodland, which is the area with the best ecological environment quality in the study area. The grassland in the western plain and the saline-alkali land around the river are the areas with poor ecological environment in the study area. Climate, precipitation, topography and other natural elements work together to form the quality of the ecological environment in the study area roughly bounded by 120?E. In years with poor natural conditions, this dividing line will have a clear eastward shifting trend, especially in the northern part of the study area. The spatial distribution of RSEI in the study area has a high degree of spatial autocorrelation, and Global Moran’s I has been above 0.8 over the years. In terms of temporal changes in ecological conditions, the ecological environment in the study area was basically stable from 2004 to 2008, with a slight deterioration;it improved significantly from 2008 to 2011;however, it deteriorated significantly from 2011 to 2019. According to the results of partial correlation analysis, the ecological environment of the former is highly correlated with natural elements such as climate and precipitation, while the latter is mainly affected by human factors. </div>展开更多
<div style="text-align:justify;"> The automatic classification of Macro landforms was processed with the program developed by Hammond’s Manual procedures, which based on properties of slope, local rel...<div style="text-align:justify;"> The automatic classification of Macro landforms was processed with the program developed by Hammond’s Manual procedures, which based on properties of slope, local relief, and profile type, which consists of 5 landform types, 24 landform class and 96 landform subclasses. This program identified landform types by moving a square window with size of 9.8 km × 9.8 km. The data includes 816 sheets of topological map with a scale of 1:250,000. The DEM were buildup with the contours and mark points based on this data with a cell size of 200 m, and merge into one sheet. The automated classification was processed on this DEM data with a AML program of ArcGIS 10.X Workstation. The result indicates it produced a classification that has good resemblance to the landforms in China. The maps were produced respectively with 5 types, 16 classes and, 90 subclasses The 5 Landform types of landforms were Plains (PLA), 20.25% of whole areas;Tablelands (TAB) of 3.56%;Plains with Hills or Mountains (PHM) of 32.84%;Open Hills and Mountains (OHM) of 18.72%;Hills and Mountains (HM) of 24.63%. In the result of 24 landform classes, there are not some classes, such as irregular plains with low relief;open very low hills, open low hills;very low hills, low hills, moderate hills. The result of 96 landform subclass is similar to the 24 class. </div>展开更多
Collapse is a geological disaster second only to landslides and occurs in large numbers every year in the northern foothills of the Tianshan Mountains in Xinjiang, China. We collected a variety of data such as topogra...Collapse is a geological disaster second only to landslides and occurs in large numbers every year in the northern foothills of the Tianshan Mountains in Xinjiang, China. We collected a variety of data such as topography, geological vegetation coverage, and human activities, and used spatial correlation analysis to eliminate factors with strong correlations. The frequency of collapse was calculated by the frequency ratio method and a hierarchical map was made. The result shows, in low susceptibility zone (LSI = 0 - 4), only 3 collapses happened, and 0.39% of total collapses. In middle susceptibility zone (LSI = 4 - 7.5), 35 collapses happened, and 5.66% of total collapses. In high susceptibility zone (LSI = 7.5 - 10), 64 collapses happened, and 10.36% of total collapses. In extremely high susceptibility zone (LSI = 10 - 14), 516 collapses happened, and 83.5% of total collapses. Using the GIS-based frequency method, the susceptibility to collapse was calculated and mapped, which was in good agreement with the actual landslide data. Collapse susceptibility results provide guidance for engineering construction.展开更多
China is a country prone to geological disasters, especially in the northern mountainous areas of the Tianshan Mountains in Xinjiang, where the surface vegetation is sparse and the rainfall is concentrated, which is p...China is a country prone to geological disasters, especially in the northern mountainous areas of the Tianshan Mountains in Xinjiang, where the surface vegetation is sparse and the rainfall is concentrated, which is prone to landslides and brings a lot of losses to the local people. Based on the field investigation, this paper evaluates the landslide susceptibility in the northern mountainous area of Tianshan Mountains. The frequency ratio method is used to calculate the landslide probability, and the landslide index (LSI) is formed to represent the landslide susceptibility. The slope unit method is used to determine the landslide units, which values were calculated by the average of the landslide index. According to the calculated LSI range of 4.53 - 20.60. It is divided into 4 grades, LSI = 4.53 - 9, which is an area that is not prone to landslides, with an area of 891.69 km<sup>2</sup>. LSI = 9 - 11 indicates an area where landslides are more likely to occur, with an area of 1252.31 km<sup>2</sup>. LSI = 11 - 13 indicates the area is more prone to landslides, with an area of 714.86 km<sup>2</sup>. LSI > 13 indicates the most prone area for landslides, with an area of 924.60 km<sup>2</sup>.展开更多
文摘<div style="text-align:justify;"> This research is based on Landsat5 TM, Landsat8 OLI/TIRS remote sensing data using RSEI model to analyze and monitor the ecological environment and its temporal and spatial changes in the forest-grass transition zone in Northeast China from 2004 to 2019. The change characteristics of the ecological environment of different types of land cover types are monitored by RSEI method, and the response of different land cover types to natural factors such as precipitation and temperature is analyzed at the same time. The distribution of RSEI in the study area presents the characteristics of high in the east and low in the west. The eastern mountainous area is densely covered with woodland, which is the area with the best ecological environment quality in the study area. The grassland in the western plain and the saline-alkali land around the river are the areas with poor ecological environment in the study area. Climate, precipitation, topography and other natural elements work together to form the quality of the ecological environment in the study area roughly bounded by 120?E. In years with poor natural conditions, this dividing line will have a clear eastward shifting trend, especially in the northern part of the study area. The spatial distribution of RSEI in the study area has a high degree of spatial autocorrelation, and Global Moran’s I has been above 0.8 over the years. In terms of temporal changes in ecological conditions, the ecological environment in the study area was basically stable from 2004 to 2008, with a slight deterioration;it improved significantly from 2008 to 2011;however, it deteriorated significantly from 2011 to 2019. According to the results of partial correlation analysis, the ecological environment of the former is highly correlated with natural elements such as climate and precipitation, while the latter is mainly affected by human factors. </div>
文摘<div style="text-align:justify;"> The automatic classification of Macro landforms was processed with the program developed by Hammond’s Manual procedures, which based on properties of slope, local relief, and profile type, which consists of 5 landform types, 24 landform class and 96 landform subclasses. This program identified landform types by moving a square window with size of 9.8 km × 9.8 km. The data includes 816 sheets of topological map with a scale of 1:250,000. The DEM were buildup with the contours and mark points based on this data with a cell size of 200 m, and merge into one sheet. The automated classification was processed on this DEM data with a AML program of ArcGIS 10.X Workstation. The result indicates it produced a classification that has good resemblance to the landforms in China. The maps were produced respectively with 5 types, 16 classes and, 90 subclasses The 5 Landform types of landforms were Plains (PLA), 20.25% of whole areas;Tablelands (TAB) of 3.56%;Plains with Hills or Mountains (PHM) of 32.84%;Open Hills and Mountains (OHM) of 18.72%;Hills and Mountains (HM) of 24.63%. In the result of 24 landform classes, there are not some classes, such as irregular plains with low relief;open very low hills, open low hills;very low hills, low hills, moderate hills. The result of 96 landform subclass is similar to the 24 class. </div>
文摘Collapse is a geological disaster second only to landslides and occurs in large numbers every year in the northern foothills of the Tianshan Mountains in Xinjiang, China. We collected a variety of data such as topography, geological vegetation coverage, and human activities, and used spatial correlation analysis to eliminate factors with strong correlations. The frequency of collapse was calculated by the frequency ratio method and a hierarchical map was made. The result shows, in low susceptibility zone (LSI = 0 - 4), only 3 collapses happened, and 0.39% of total collapses. In middle susceptibility zone (LSI = 4 - 7.5), 35 collapses happened, and 5.66% of total collapses. In high susceptibility zone (LSI = 7.5 - 10), 64 collapses happened, and 10.36% of total collapses. In extremely high susceptibility zone (LSI = 10 - 14), 516 collapses happened, and 83.5% of total collapses. Using the GIS-based frequency method, the susceptibility to collapse was calculated and mapped, which was in good agreement with the actual landslide data. Collapse susceptibility results provide guidance for engineering construction.
文摘China is a country prone to geological disasters, especially in the northern mountainous areas of the Tianshan Mountains in Xinjiang, where the surface vegetation is sparse and the rainfall is concentrated, which is prone to landslides and brings a lot of losses to the local people. Based on the field investigation, this paper evaluates the landslide susceptibility in the northern mountainous area of Tianshan Mountains. The frequency ratio method is used to calculate the landslide probability, and the landslide index (LSI) is formed to represent the landslide susceptibility. The slope unit method is used to determine the landslide units, which values were calculated by the average of the landslide index. According to the calculated LSI range of 4.53 - 20.60. It is divided into 4 grades, LSI = 4.53 - 9, which is an area that is not prone to landslides, with an area of 891.69 km<sup>2</sup>. LSI = 9 - 11 indicates an area where landslides are more likely to occur, with an area of 1252.31 km<sup>2</sup>. LSI = 11 - 13 indicates the area is more prone to landslides, with an area of 714.86 km<sup>2</sup>. LSI > 13 indicates the most prone area for landslides, with an area of 924.60 km<sup>2</sup>.
