Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total ...Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total reflective brightness Rij received in different bands with a remote sensor. Nine models delineating the ground-space correlation between the ground spectra and the optimal bands of images of the typical gold deposits have been established based on the ground-space correlativity and field measurements of the ground spectra of the typical gold deposits in the Ailaoshan area. According to the 9 correlation models, TM images were inverted into ground-space correlation images that are related to the typical gold deposits within the area and then recognized by a computer. Research on the ground spectra and TM data in the Ailaoshan area shows that the correlation analysis of the ground spectra and TM data of gold deposits can be effectively applied to the prediction of gold deposits, location of prospecting targets, and extraction of imagery information of gold mineralization.展开更多
Characterized by lithological diversity and rich mineral resources, Benshangul-Gumuz National Regional State located in Asosa Zones, Western Ethiopia has been investigated for geological mapping and morpho-structural ...Characterized by lithological diversity and rich mineral resources, Benshangul-Gumuz National Regional State located in Asosa Zones, Western Ethiopia has been investigated for geological mapping and morpho-structural lineaments extraction using PALSAR (Phased Array type L-band Synthetic Aperture Radar ) Fine Beam Single (FBS) L-HH polarization and Landsat-5 TM (Thematic Mapper ) datasets. These data were preprocessed to retrieve ground surface reflectance and backscatter coefficients. To overcome the geometry acquisition between the two sensors, they were geometrically and topographically rectified using ASTER-V2 DEM. Intensity-Hue-Saturation, directional filters and automatic lineaments extraction were applied on the datasets for lithological units’ discrimination and structural delimitation for potential mineral exploration. The obtained results showed good relationship among the topographic morphology, rock-substrate, structural variations properties, and drainage network. The spectral variations were easily associated with lithological units. Likewise, the morpho-structural information highlighted in the PALSAR image was visible without altering the radiometric integrity of the details in TM bands through the fusion process. Moreover, predominant lineaments directions trending NE-SW, NS, and NW-SE were identified. Results of this study highlighted the importance of the PALSAR FBS L-HH mode and TM data fusion to enhance geological features and lithological units for mineral exploration particularly in tropical zones.展开更多
The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjia...The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM im- age texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS in- formation (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to im- plement and should be applicable in other settings and over larger extents.展开更多
Based on the research on the diffusion of suspended sediments discharged outside of Yangtze River estuary and the landuse of Shanghai using Landsat MSS images in several years, the authors analysed the characteristics...Based on the research on the diffusion of suspended sediments discharged outside of Yangtze River estuary and the landuse of Shanghai using Landsat MSS images in several years, the authors analysed the characteristics of TM CCT data of Shanghai scene, pointed out concrete range of maximum turbidity and growth of urban boundary of Shanghai through the information extraction.The feature vector combination method is used in the research process. The result is getting nice.展开更多
The investigation of the tendency of climate change and its effects on ecology, economy and sociology is essential for long term policy making. The long-term measurement of the physical and chemical properties of the ...The investigation of the tendency of climate change and its effects on ecology, economy and sociology is essential for long term policy making. The long-term measurement of the physical and chemical properties of the atmosphere with state-of-the-arts instruments provides high-quality data for these studies. The evaluated data are stored in really special file structures and formats that cannot be inserted in one common database. Moreover, the observed data usually available in ASCII format and the users sometimes need to convert them in other format. The file conversion is usually time consuming procedure and can contribute to the uncertainties. MeteoRead is a client database software that imports the observed atmospheric data e.g. wind direction, wind speed, aerosol particle concentration etc. and makes them available in different file formats, which are most commonly used in climate research. This Java<sup>TM</sup> based program applies the Structured Query Language (SQL) functions such as table creation on a database server, data or figures insertion into the table and data selection via Graphical User Interface. The selected data can be stored in NetCDF, HDF5, DataBase or TXT file formats and the figures can be available in PNG, JPG, JPNG, PDF or GIF file formats. The program was tested on Linux and Windows platforms with different Java<sup>TM</sup> Development Kit. The MeteoRead is planned to be developed to visualizing the annual, seasonal, monthly, daily or hourly average value of the selected data and to use the functionality of the SQL database to calculate various mathematical and statistical correlations.展开更多
文摘Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total reflective brightness Rij received in different bands with a remote sensor. Nine models delineating the ground-space correlation between the ground spectra and the optimal bands of images of the typical gold deposits have been established based on the ground-space correlativity and field measurements of the ground spectra of the typical gold deposits in the Ailaoshan area. According to the 9 correlation models, TM images were inverted into ground-space correlation images that are related to the typical gold deposits within the area and then recognized by a computer. Research on the ground spectra and TM data in the Ailaoshan area shows that the correlation analysis of the ground spectra and TM data of gold deposits can be effectively applied to the prediction of gold deposits, location of prospecting targets, and extraction of imagery information of gold mineralization.
文摘Characterized by lithological diversity and rich mineral resources, Benshangul-Gumuz National Regional State located in Asosa Zones, Western Ethiopia has been investigated for geological mapping and morpho-structural lineaments extraction using PALSAR (Phased Array type L-band Synthetic Aperture Radar ) Fine Beam Single (FBS) L-HH polarization and Landsat-5 TM (Thematic Mapper ) datasets. These data were preprocessed to retrieve ground surface reflectance and backscatter coefficients. To overcome the geometry acquisition between the two sensors, they were geometrically and topographically rectified using ASTER-V2 DEM. Intensity-Hue-Saturation, directional filters and automatic lineaments extraction were applied on the datasets for lithological units’ discrimination and structural delimitation for potential mineral exploration. The obtained results showed good relationship among the topographic morphology, rock-substrate, structural variations properties, and drainage network. The spectral variations were easily associated with lithological units. Likewise, the morpho-structural information highlighted in the PALSAR image was visible without altering the radiometric integrity of the details in TM bands through the fusion process. Moreover, predominant lineaments directions trending NE-SW, NS, and NW-SE were identified. Results of this study highlighted the importance of the PALSAR FBS L-HH mode and TM data fusion to enhance geological features and lithological units for mineral exploration particularly in tropical zones.
基金Under the auspices of National Natural Science Foundation of China (No. 40871188) National Key Technologies R&D Program of China (No. 2006BAD23B03)
文摘The main objective of this research is to determine the capacity of land cover classification combining spec- tral and textural features of Landsat TM imagery with ancillary geographical data in wetlands of the Sanjiang Plain, Heilongjiang Province, China. Semi-variograms and Z-test value were calculated to assess the separability of grey-level co-occurrence texture measures to maximize the difference between land cover types. The degree of spatial autocorrelation showed that window sizes of 3×3 pixels and 11×11 pixels were most appropriate for Landsat TM im- age texture calculations. The texture analysis showed that co-occurrence entropy, dissimilarity, and variance texture measures, derived from the Landsat TM spectrum bands and vegetation indices provided the most significant statistical differentiation between land cover types. Subsequently, a Classification and Regression Tree (CART) algorithm was applied to three different combinations of predictors: 1) TM imagery alone (TM-only); 2) TM imagery plus image texture (TM+TXT model); and 3) all predictors including TM imagery, image texture and additional ancillary GIS in- formation (TM+TXT+GIS model). Compared with traditional Maximum Likelihood Classification (MLC) supervised classification, three classification trees predictive models reduced the overall error rate significantly. Image texture measures and ancillary geographical variables depressed the speckle noise effectively and reduced classification error rate of marsh obviously. For classification trees model making use of all available predictors, omission error rate was 12.90% and commission error rate was 10.99% for marsh. The developed method is portable, relatively easy to im- plement and should be applicable in other settings and over larger extents.
文摘Based on the research on the diffusion of suspended sediments discharged outside of Yangtze River estuary and the landuse of Shanghai using Landsat MSS images in several years, the authors analysed the characteristics of TM CCT data of Shanghai scene, pointed out concrete range of maximum turbidity and growth of urban boundary of Shanghai through the information extraction.The feature vector combination method is used in the research process. The result is getting nice.
文摘The investigation of the tendency of climate change and its effects on ecology, economy and sociology is essential for long term policy making. The long-term measurement of the physical and chemical properties of the atmosphere with state-of-the-arts instruments provides high-quality data for these studies. The evaluated data are stored in really special file structures and formats that cannot be inserted in one common database. Moreover, the observed data usually available in ASCII format and the users sometimes need to convert them in other format. The file conversion is usually time consuming procedure and can contribute to the uncertainties. MeteoRead is a client database software that imports the observed atmospheric data e.g. wind direction, wind speed, aerosol particle concentration etc. and makes them available in different file formats, which are most commonly used in climate research. This Java<sup>TM</sup> based program applies the Structured Query Language (SQL) functions such as table creation on a database server, data or figures insertion into the table and data selection via Graphical User Interface. The selected data can be stored in NetCDF, HDF5, DataBase or TXT file formats and the figures can be available in PNG, JPG, JPNG, PDF or GIF file formats. The program was tested on Linux and Windows platforms with different Java<sup>TM</sup> Development Kit. The MeteoRead is planned to be developed to visualizing the annual, seasonal, monthly, daily or hourly average value of the selected data and to use the functionality of the SQL database to calculate various mathematical and statistical correlations.
