Microwave and optical remote sensing study of Boone County, Missouri

Integration of synthetic-aperture radar data with spaceborne optical data offers potential for improving land-use classification for local and state government applications. Remote sensing techniques using optical sensor data are well established for local and state government applications. As commercial SAR products become available at lower costs, local government applications using optical based classification can incorporate SAR sensor data into their processing. For this study, we orthorectified and analyzed Radarsat SAR data and Landsat TM data that covers Boone County, Missouri. Optical and SAR sensor data are co-registered for data fusion and classification process. Training data from sites throughout the study area are used to verify and validate the classification of five classes: crops, water, built-up, forest and grass. We present preliminary results of our study.

[1]  Philip H. Swain,et al.  Remote Sensing: The Quantitative Approach , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  S. Goetz,et al.  Applications of multi-temporal land cover information in the mid-Atlantic region: a RESAC initiative , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[3]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[4]  A. Fung,et al.  Microwave Remote Sensing Active and Passive-Volume III: From Theory to Applications , 1986 .

[5]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[6]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[7]  Barry Haack,et al.  Radar and Optical Data Integration for Land-Use/Land-Cover Mapping , 2000 .

[8]  Robert N. Colwell,et al.  Manual of remote sensing , 1983 .

[9]  N. Classeau,et al.  Time-space filtering of multitemporal SAR images , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[10]  V. Manian,et al.  A computational framework for analyzing textured image classification , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[11]  Richard K. Moore,et al.  Microwave Remote Sensing , 1999 .

[12]  Anil K. Jain,et al.  Texture Analysis in the Presence of Speckle Noise , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.

[13]  J. R. Jensen SPECTRAL AND TEXTURAL FEATURES TO CLASSIFY ELUSIVE LAND COVER AT THE URBAN FRINGE , 1979 .

[14]  Anil K. Jain,et al.  Multisource classification of remotely sensed data: fusion of Landsat TM and SAR images , 1994, IEEE Trans. Geosci. Remote. Sens..

[15]  J. Rais,et al.  A framework for multi-date multi-sensor image interpretation , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.