<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
Quickly extraction of building information technology is an important application in urban development planning, electronic information, national defense and others. This paper takes Landsat-8 multispectral and panchr...Quickly extraction of building information technology is an important application in urban development planning, electronic information, national defense and others. This paper takes Landsat-8 multispectral and panchromatic data as data source, using the local variance method to select the optimal segmentation scale, normalized difference vegetation index (NDVI) and the normalized building index (NDBI) and panchromatic brightness value of an object oriented classification rule extraction. The high vegetation coverage area of buildings, and through the spatial relationships and distinguishing feature of collections of buildings independent buildings and villages. The results showed that Google earth high resolution image analysis and accuracy evaluation. the results of the extraction based on the overall accuracy of village extraction was 83%, the accuracy of extraction of independent buildings was 70%, according to the L8 remote sensing data, object oriented classification method can quickly and accurately extract the high vegetation coverage area of the building.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
One of the ophiolites that record the Proto-Tethys Ocean’s episodic closure is the Munabulake ophiolitic mélange,which is situated in the middle of the Kunlun-Qaidam and Altun-Qilian blocks.Detailed field mappin...One of the ophiolites that record the Proto-Tethys Ocean’s episodic closure is the Munabulake ophiolitic mélange,which is situated in the middle of the Kunlun-Qaidam and Altun-Qilian blocks.Detailed field mapping revealed that the Munabulake ophiolitic mélange comprises local(ultramafic rocks,basalts,andesites,gabbros,diorites,and plagiogranites)and exotic(marble,gneiss,schist,and amphibolite)blocks,many of which are in the schist matrix(Qimantage Group).Based on geochronological,geochemical,and petrological observations,the mafic rocks in the Munabulake ophiolitic mélange can be categorized into three categories:498-Ma OIB-like gabbros,468-Ma Hawaiian alkaline basalt-like dolerite and pillow basaltic slices,and 428 Ma massive SSZ-like ultramafic rocks.The 501-452 Ma I-type granites exhibit arc affinities due to the oceanic crust subduction.These findings,along with spatial relationships,suggest that the Early Paleozoic ophiolite complex,island arc rocks,and accretionary complex generated as an intra-oceanic arc system as a result of obduction of the south Altun Ocean’s onto the Central Altun block within a north-directed subduction event.A dextral strike-slip was evident throughout the Early Paleozoic oceanic crust subduction based on the whole set of planar and linear structural data,and the subduction polarity was likely to the north.According to the ophiolitic mélange’s youngest rocks and the existence of 413 Ma granite dykes that are widely exposed in the Munabulake ophiolitic mélange,the Munabulake ophiolitic mélange was most likely emplaced during the Middle Silurian.This Munabulake ophiolitic mélange is similar in age and petrochemical characteristics to the other ophiolites in the South Altun subduction-collision belt,indicating that the Manabulak ophiolite mélange is a westward extension of the Apa-Mangya subduction-collision belt,which formed during the northward subduction of the South Altun Ocean slab during the Early Paleozoic.Thus,the final closing time of the South Altun Ocean is between 413 and 428 Ma.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Quickly extraction of building information technology is an important application in urban development planning, electronic information, national defense and others. This paper takes Landsat-8 multispectral and panchromatic data as data source, using the local variance method to select the optimal segmentation scale, normalized difference vegetation index (NDVI) and the normalized building index (NDBI) and panchromatic brightness value of an object oriented classification rule extraction. The high vegetation coverage area of buildings, and through the spatial relationships and distinguishing feature of collections of buildings independent buildings and villages. The results showed that Google earth high resolution image analysis and accuracy evaluation. the results of the extraction based on the overall accuracy of village extraction was 83%, the accuracy of extraction of independent buildings was 70%, according to the L8 remote sensing data, object oriented classification method can quickly and accurately extract the high vegetation coverage area of the building.
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>.
基金Funding for this research was provided by the National Natural Science Foundations of China (Grant No.41702054)the China Geological Survey Program (DD2016007907)awarded to Changfeng Liu and administered by the Institute of Geological Survey,China University of Geosciences (Beijing).
文摘One of the ophiolites that record the Proto-Tethys Ocean’s episodic closure is the Munabulake ophiolitic mélange,which is situated in the middle of the Kunlun-Qaidam and Altun-Qilian blocks.Detailed field mapping revealed that the Munabulake ophiolitic mélange comprises local(ultramafic rocks,basalts,andesites,gabbros,diorites,and plagiogranites)and exotic(marble,gneiss,schist,and amphibolite)blocks,many of which are in the schist matrix(Qimantage Group).Based on geochronological,geochemical,and petrological observations,the mafic rocks in the Munabulake ophiolitic mélange can be categorized into three categories:498-Ma OIB-like gabbros,468-Ma Hawaiian alkaline basalt-like dolerite and pillow basaltic slices,and 428 Ma massive SSZ-like ultramafic rocks.The 501-452 Ma I-type granites exhibit arc affinities due to the oceanic crust subduction.These findings,along with spatial relationships,suggest that the Early Paleozoic ophiolite complex,island arc rocks,and accretionary complex generated as an intra-oceanic arc system as a result of obduction of the south Altun Ocean’s onto the Central Altun block within a north-directed subduction event.A dextral strike-slip was evident throughout the Early Paleozoic oceanic crust subduction based on the whole set of planar and linear structural data,and the subduction polarity was likely to the north.According to the ophiolitic mélange’s youngest rocks and the existence of 413 Ma granite dykes that are widely exposed in the Munabulake ophiolitic mélange,the Munabulake ophiolitic mélange was most likely emplaced during the Middle Silurian.This Munabulake ophiolitic mélange is similar in age and petrochemical characteristics to the other ophiolites in the South Altun subduction-collision belt,indicating that the Manabulak ophiolite mélange is a westward extension of the Apa-Mangya subduction-collision belt,which formed during the northward subduction of the South Altun Ocean slab during the Early Paleozoic.Thus,the final closing time of the South Altun Ocean is between 413 and 428 Ma.
