This paper introduces some of the image processing techniques developed in the Canada Research Chair in Advanced Geomatics Image Processing Laboratory (CRC-AGIP Lab) and in the Department of Geodesy and Geomatics Engi...This paper introduces some of the image processing techniques developed in the Canada Research Chair in Advanced Geomatics Image Processing Laboratory (CRC-AGIP Lab) and in the Department of Geodesy and Geomatics Engineering (GGE) at the University of New Brunswick (UNB), Canada. The techniques were developed by innovatively/“smartly” utilizing the characteristics of the available very high resolution optical remote sensing images to solve important problems or create new applications in photogrammetry and remote sensing. The techniques to be introduced are: automated image fusion (UNB-PanSharp), satellite image online mapping, street view technology, moving vehicle detection using single set satellite imagery, supervised image segmentation, image matching in smooth areas, and change detection using images from different viewing angles. Because of their broad application potential, some of the techniques have made a global impact, and some have demonstrated the potential for a global impact.展开更多
Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas ...Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas synthetic aperture radar(SAR)imagery is sensitive to changes in growth states and morphological structures.Crop-type mapping with a single type of imagery sometimes has unsatisfactory precision,so providing precise spatiotemporal information on crop type at a local scale for agricultural applications is difficult.To explore the abilities of combining optical and SAR images and to solve the problem of inaccurate spatial information for land parcels,a new method is proposed in this paper to improve crop-type identification accuracy.Multifeatures were derived from the full polarimetric SAR data(GaoFen-3)and a high-resolution optical image(GaoFen-2),and the farmland parcels used as the basic for object-oriented classification were obtained from the GaoFen-2 image using optimal scale segmentation.A novel feature subset selection method based on within-class aggregation and between-class scatter(WA-BS)is proposed to extract the optimal feature subset.Finally,crop-type mapping was produced by a support vector machine(SVM)classifier.The results showed that the proposed method achieved good classification results with an overall accuracy of 89.50%,which is better than the crop classification results derived from SAR-based segmentation.Compared with the ReliefF,mRMR and LeastC feature selection algorithms,the WA-BS algorithm can effectively remove redundant features that are strongly correlated and obtain a high classification accuracy via the obtained optimal feature subset.This study shows that the accuracy of crop-type mapping in an area with multiple cropping patterns can be improved by the combination of optical and SAR remote sensing images.展开更多
Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system ...Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1:50,000 topographic data of China’s land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing mapping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of collaboration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic surveying and mapping.展开更多
文摘This paper introduces some of the image processing techniques developed in the Canada Research Chair in Advanced Geomatics Image Processing Laboratory (CRC-AGIP Lab) and in the Department of Geodesy and Geomatics Engineering (GGE) at the University of New Brunswick (UNB), Canada. The techniques were developed by innovatively/“smartly” utilizing the characteristics of the available very high resolution optical remote sensing images to solve important problems or create new applications in photogrammetry and remote sensing. The techniques to be introduced are: automated image fusion (UNB-PanSharp), satellite image online mapping, street view technology, moving vehicle detection using single set satellite imagery, supervised image segmentation, image matching in smooth areas, and change detection using images from different viewing angles. Because of their broad application potential, some of the techniques have made a global impact, and some have demonstrated the potential for a global impact.
基金The authors acknowledge that this study was financially supported by the National Key R&D Programs of China(No.2017YFB0504201)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA20020101)+1 种基金and the Natural Science Foundation of China(No.61473286 and No.61375002)Our sincere thanks go to the students at the State Key Laboratory of Remote Sensing Science for their assistance during the field survey campaigns.
文摘Remote sensing is an important technical means to investigate land resources.Optical imagery has been widely used in crop classification and can show changes in moisture and chlorophyll content in crop leaves,whereas synthetic aperture radar(SAR)imagery is sensitive to changes in growth states and morphological structures.Crop-type mapping with a single type of imagery sometimes has unsatisfactory precision,so providing precise spatiotemporal information on crop type at a local scale for agricultural applications is difficult.To explore the abilities of combining optical and SAR images and to solve the problem of inaccurate spatial information for land parcels,a new method is proposed in this paper to improve crop-type identification accuracy.Multifeatures were derived from the full polarimetric SAR data(GaoFen-3)and a high-resolution optical image(GaoFen-2),and the farmland parcels used as the basic for object-oriented classification were obtained from the GaoFen-2 image using optimal scale segmentation.A novel feature subset selection method based on within-class aggregation and between-class scatter(WA-BS)is proposed to extract the optimal feature subset.Finally,crop-type mapping was produced by a support vector machine(SVM)classifier.The results showed that the proposed method achieved good classification results with an overall accuracy of 89.50%,which is better than the crop classification results derived from SAR-based segmentation.Compared with the ReliefF,mRMR and LeastC feature selection algorithms,the WA-BS algorithm can effectively remove redundant features that are strongly correlated and obtain a high classification accuracy via the obtained optimal feature subset.This study shows that the accuracy of crop-type mapping in an area with multiple cropping patterns can be improved by the combination of optical and SAR remote sensing images.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 41701506 and 41671440].
文摘Remote sensing mapping is an important research direction in the development of geographic surveying and mapping.In order to successfully implement the project of Mapping Western China(MWC),a technical mapping system has been established.In this project,many problems have been solved through technological innovation,such as block adjustment with scarce control points,large-scale aerial/satellite image mapping,and intelligent interpretation of multi-source images.Several softwares were developed,e.g.PixelGrid for aerial/satellite image mapping in a large area,FeatureStation for the integration of multi-source data in the complex terrain areas,and an airborne multi-band and multi-polarization interferometric data acquisition system for SAR mapping.For the first time,full coverage of 1:50,000 topographic data of China’s land territory has been produced,which means the geospatial framework of digital China is basically completed.With the implementation of other key national plans and projects(i.e.national geographic conditions monitoring and national remote sensing mapping),the focus has changed from MWC to national dynamic mapping.Accordingly,a dynamic mapping system is established.The data acquisition capability has developed from a single source to multiple sources and multiple modalities.The mapping capability has developed into dynamic mapping,and the capability for database update shows the characteristics of collaboration.The national geographic condition monitoring creates a multi-scale index system for statistical analysis for various needs.A multi-level and multi-dimensional technical system for statistical computing and decision-making service is developed for the transformation from dynamic monitoring to information service.In this paper,we give a brief introduction about the recent development of remote sensing mapping in China with respect to data acquisition,map production,and information service.The purpose of this paper is to motivate the establishment of theory and method for remote sensing mapping,technical and equipment in the smart mapping era,to improve the capability of perceiving,analyzing,mining,and applying geographic data,and to promote the intelligent development of geographic surveying and mapping.
