Fully automatic generation of geoinformation products with chinese zy‐3 satellite imagery

The advantages of continuously and soundly obtaining large multidimensional, multiscale and multitemporal observation datasets from satellite remote sensing make it indispensable in building a national spatial data infrastructure. This paper introduces the ZY‐3 satellite developed in China and discusses a fully automatic data‐processing system to generate geoinformation products, such as digital elevation models (DEMs) and digital orthophotomaps (DOMs), based on ZY‐3 imagery. The key technologies of automatic geoinformation product generation, including strip image‐based bundle adjustment together with creating DEMs and DOMs, are illustrated. The accuracies of the georeferencing and automatically generated geoinformation products are also discussed. This automatic data‐processing system is shown to provide a good foundation for near real‐time derivation of such geoinformation products and for the promotion and application of Chinese domestic satellites.

[1]  F. Mantovani,et al.  Remote sensing techniques for landslide studies and hazard zonation in Europe , 1996 .

[2]  Alexander Ignatov,et al.  Development, validation, and potential enhancements to the second‐generation operational aerosol product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration , 1997 .

[3]  E. Schetselaar Fusion by the IHS transform: Should we use cylindrical or spherical coordinates? , 1998 .

[4]  J. Cihlar Land cover mapping of large areas from satellites: Status and research priorities , 2000 .

[5]  Jing Li,et al.  DEVELOPMENT OF GEOGRAPHIC INFORMATION SYSTEMS (GIS) IN CHINA: AN OVERVIEW , 2002 .

[6]  Clive S. Fraser,et al.  Three‐Dimensional Geopositioning Accuracy of Ikonos Imagery , 2002 .

[7]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Susan L. Ustin,et al.  Using satellite remote sensing for DEM extraction in complex mountainous terrain: Landscape analysis of the Makalu Barun National Park of eastern Nepal , 2002 .

[9]  Zhang Li,et al.  AUTOMATIC DSM GENERATION FROM LINEAR ARRAY IMAGERY DATA , 2004 .

[10]  Clive S. Fraser,et al.  Insights into the affine model for high-resolution satellite sensor orientation , 2004 .

[11]  Clive S. Fraser,et al.  Accuracy assessment of QuickBird stereo imagery , 2004 .

[12]  EVALUATION OF 3 D CITY MODEL PRODUCTION FROM PLEIADES-HR SATELLITE IMAGES AND 2 D GROUND MAPS , 2005 .

[13]  C. Tao,et al.  Automatic Segmentation of High-resolution Satellite Imagery by Integrating Texture, Intensity, and Color Features , 2005 .

[14]  A. Gruen,et al.  Least squares 3D surface and curve matching , 2005 .

[15]  J. Nichol,et al.  Application of high-resolution stereo satellite images to detailed landslide hazard assessment , 2006 .

[16]  Li Zhang,et al.  Multi-image matching for DSM generation from IKONOS imagery , 2006 .

[17]  C. Fraser,et al.  Sensor orientation via RPCs , 2006 .

[18]  E. Rodríguez,et al.  A Global Assessment of the SRTM Performance , 2006 .

[19]  George Vosselman,et al.  An integrated approach for modelling and global registration of point clouds , 2007 .

[20]  Sébastien Leprince,et al.  Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[21]  D. Donoghue,et al.  High Resolution Elevation Data Derived from Stereoscopic CORONA Imagery with Minimal Ground Control: An Approach Using Ikonos and SRTM Data , 2007 .

[22]  Domenico Tegolo,et al.  A non-parametric scale-based corner detector , 2008, 2008 19th International Conference on Pattern Recognition.

[23]  Olaf Bubenzer,et al.  Combining digital elevation data (SRTM/ASTER), high resolution satellite imagery (Quickbird) and GIS for geomorphological mapping: A multi-component case study on Mediterranean karst in Central Crete , 2009 .

[24]  A. Davranche,et al.  Radiometric Normalization of SPOT-5 Scenes: 6S atmospheric Model versus Pseudo-invariant Features , 2009 .

[25]  V. Bhanumurthy,et al.  Application of satellite — based rainfall products and SRTM DEM in hydrological modelling of Brahmaputra basin , 2009 .

[26]  J. Nichol,et al.  Application of high-resolution satellite images to detailed landslide hazard assessment , 2009, 2009 Joint Urban Remote Sensing Event.

[27]  F. Rottensteiner,et al.  AUTOMATIC VERIFIACTION OF AGRICULTURAL AREAS USING IKONOS SATELLITE IMAGES , 2009 .

[28]  S. Bhaskaran,et al.  Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data , 2010 .

[29]  Baboo S.Santhosh,et al.  Geometric Correction in Recent High Resolution Satellite Imagery: A Case Study in Coimbatore, Tamil Nadu , 2011 .

[30]  Yongjun Zhang,et al.  Precise Orthoimage Generation of Dunhuang Wall Painting , 2011 .

[31]  Mi Wang,et al.  Isprs Journal of Photogrammetry and Remote Sensing Epipolar Resampling of Linear Pushbroom Satellite Imagery by a New Epipolarity Model , 2022 .

[32]  Pat Norris Developments in high resolution imaging satellites for the military , 2011 .

[33]  Thierry Toutin,et al.  Review of developments in geometric modelling for high resolution satellite pushbroom sensors , 2012 .

[34]  Yongjun Zhang,et al.  A New Approach on Optimization of the Rational Function Model of High-Resolution Satellite Imagery , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[35]  A. Gruen Development and Status of Image Matching in Photogrammetry , 2012 .

[36]  Guo Zhang,et al.  In‐Orbit Geometric Calibration And Validation Of Zy‐3 Linear Array Sensors , 2014 .

[37]  Maoteng Zheng,et al.  On-Orbit Geometric Calibration of ZY-3 Three-Line Array Imagery With Multistrip Data Sets , 2014, IEEE Transactions on Geoscience and Remote Sensing.