The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusion...The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer（ASTER） data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared（VNIR） and short wave infrared（SWIR） data were transformed using band ratios and minimum noise fraction（MNF）, while the thermal infrared（TIR） data were processed using mafic index（MI） and principal components analysis（PCA）. ASTER band ratios（6/8, 5/4, 2/1） in RGB image and MNF（1, 2, 4） in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.展开更多
The Main Ethiopian Rift(MER)is an area of extreme topography underlain by post-Miocene volcanic rocks,Jurassic limestone and a Precambrian basement.A prime concern is the rapid expansion of wide gullies that are impin...The Main Ethiopian Rift(MER)is an area of extreme topography underlain by post-Miocene volcanic rocks,Jurassic limestone and a Precambrian basement.A prime concern is the rapid expansion of wide gullies that are impinging on agricultural land.We investigate the potential contribution of Advanced Space-borne Thermal Emission and Reflection Radiometer(ASTER)data and geomorphologic parameters to discern patterns and features of gully erosion in the MER.Maximum Likelihood Classifica-tion(MLC),Support Vector Machine(SVM),and Minimum Distance(MD)classifiers are used to extract different gully shapes and patterns.Several spatial textures based on Grey Level Co-occurrence Matrices(GLCMs)are then generated.Afterwards,the same classifiers are applied to the ASTER data combined with the spatial texture information.We used geomorphologic parameters ex-tracted from SRTM and ASTER DEMs to describe the geomorphologic setting and the gullies' shapes.The classifications show accuracies varying between 67% and 89%.Maps derived from this quantitative analysis allow the monitoring and mapping of land degradation as a direct result of gully-widening.This study reveals the utility of combining ASTER data and spatial textural infor-mation in discerning areas affected by gully erosion.展开更多
The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,bu...The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,but it is rarely used in areas with complex terrain and high vegetation coverage.Based on this purpose,this study used Aster remote sensing data,and took Gongchangling iron deposit as a case study.It combined the mineral spectrum theory and the basic geologic data of the study area,using the model of principal component analysis(PCA)and color synthesis to extract abnormal altered minerals.The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area,which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas.展开更多
Most methods for classification of remote sensing data are based on the statistical parameter evaluation with the assumption that the samples obey the normal distribution. How-ever, more accurate classification result...Most methods for classification of remote sensing data are based on the statistical parameter evaluation with the assumption that the samples obey the normal distribution. How-ever, more accurate classification results can be obtained with the neural network method through getting knowledge from environments and adjusting the parameter (or weight) step by step by a specific measurement. This paper focuses on the double-layer structured Kohonen self-organizing feature map (SOFM), for which all neurons within the two layers are linked one another and those of the competition layers are linked as well along the sides. Therefore, the self-adapting learning ability is improved due to the effective competition and suppression in this method. The SOFM has become a hot topic in the research area of remote sensing data classi-fication. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a new satellite-borne remote sensing instrument with three 15-m resolution bands and three 30-m resolution bands at the near infrared. The ASTER data of Dagang district, Tianjin Munici-pality is used as the test data in this study. At first, the wavelet fusion is carried out to make the spatial resolutions of the ASTER data identical; then, the SOFM method is applied to classifying the land cover types. The classification results are compared with those of the maximum likeli-hood method (MLH). As a consequence, the classification accuracy of SOFM increases about by 7% in general and, in particular, it is almost as twice as that of the MLH method in the town.展开更多
There are hundreds of villages in the western mountainous area of Beijing,of which quite a few have a profound history and form the settlement culture in the western part of Beijing.Taking dozens of ancient villages i...There are hundreds of villages in the western mountainous area of Beijing,of which quite a few have a profound history and form the settlement culture in the western part of Beijing.Taking dozens of ancient villages in Mentougou District as the research sample,the village space as the research object,based on ASTER GDEM database and quantitative analysis tools such as Global Mapper and ArcGIS,this study analyzed from the perspectives of altitude,topography,slope direction,and building density distribution,made a quantitative study on the spatial distribution and plane structure of ancient villages so that the law of village space with the characteristics of western Beijing was summarized to supplement and improve the relevant achievements in the research field of ancient villages in western Beijing.展开更多
基金supported by the Special Fund for Basic Scientific Research of Central Colleges (Nos. 2014G1271060, 2013G1271103)Chang’an University, China and the High Resolution Earth Observation Systems of National Science and Technology Major Projects
文摘The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer（ASTER） data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared（VNIR） and short wave infrared（SWIR） data were transformed using band ratios and minimum noise fraction（MNF）, while the thermal infrared（TIR） data were processed using mafic index（MI） and principal components analysis（PCA）. ASTER band ratios（6/8, 5/4, 2/1） in RGB image and MNF（1, 2, 4） in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.
基金Supported by the German Academic Exchange Service
文摘The Main Ethiopian Rift(MER)is an area of extreme topography underlain by post-Miocene volcanic rocks,Jurassic limestone and a Precambrian basement.A prime concern is the rapid expansion of wide gullies that are impinging on agricultural land.We investigate the potential contribution of Advanced Space-borne Thermal Emission and Reflection Radiometer(ASTER)data and geomorphologic parameters to discern patterns and features of gully erosion in the MER.Maximum Likelihood Classifica-tion(MLC),Support Vector Machine(SVM),and Minimum Distance(MD)classifiers are used to extract different gully shapes and patterns.Several spatial textures based on Grey Level Co-occurrence Matrices(GLCMs)are then generated.Afterwards,the same classifiers are applied to the ASTER data combined with the spatial texture information.We used geomorphologic parameters ex-tracted from SRTM and ASTER DEMs to describe the geomorphologic setting and the gullies' shapes.The classifications show accuracies varying between 67% and 89%.Maps derived from this quantitative analysis allow the monitoring and mapping of land degradation as a direct result of gully-widening.This study reveals the utility of combining ASTER data and spatial textural infor-mation in discerning areas affected by gully erosion.
基金Supported by projects of Institute of Geology,Chinese Academy of Geological Sciences(No.DD20160121)the National Key Research and Development Program of China(No.2020YFA0714103).
文摘The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data,which can more accurately reveal the distribution of altered minerals.It plays an important role in prospecting,but it is rarely used in areas with complex terrain and high vegetation coverage.Based on this purpose,this study used Aster remote sensing data,and took Gongchangling iron deposit as a case study.It combined the mineral spectrum theory and the basic geologic data of the study area,using the model of principal component analysis(PCA)and color synthesis to extract abnormal altered minerals.The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area,which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas.
文摘Most methods for classification of remote sensing data are based on the statistical parameter evaluation with the assumption that the samples obey the normal distribution. How-ever, more accurate classification results can be obtained with the neural network method through getting knowledge from environments and adjusting the parameter (or weight) step by step by a specific measurement. This paper focuses on the double-layer structured Kohonen self-organizing feature map (SOFM), for which all neurons within the two layers are linked one another and those of the competition layers are linked as well along the sides. Therefore, the self-adapting learning ability is improved due to the effective competition and suppression in this method. The SOFM has become a hot topic in the research area of remote sensing data classi-fication. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a new satellite-borne remote sensing instrument with three 15-m resolution bands and three 30-m resolution bands at the near infrared. The ASTER data of Dagang district, Tianjin Munici-pality is used as the test data in this study. At first, the wavelet fusion is carried out to make the spatial resolutions of the ASTER data identical; then, the SOFM method is applied to classifying the land cover types. The classification results are compared with those of the maximum likeli-hood method (MLH). As a consequence, the classification accuracy of SOFM increases about by 7% in general and, in particular, it is almost as twice as that of the MLH method in the town.
基金Sponsored by National Natural Science Fund of China(51608007)Young Top-notch Talent Cultivation Project of North China University of Technology(2018)
文摘There are hundreds of villages in the western mountainous area of Beijing,of which quite a few have a profound history and form the settlement culture in the western part of Beijing.Taking dozens of ancient villages in Mentougou District as the research sample,the village space as the research object,based on ASTER GDEM database and quantitative analysis tools such as Global Mapper and ArcGIS,this study analyzed from the perspectives of altitude,topography,slope direction,and building density distribution,made a quantitative study on the spatial distribution and plane structure of ancient villages so that the law of village space with the characteristics of western Beijing was summarized to supplement and improve the relevant achievements in the research field of ancient villages in western Beijing.
