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This paper presents the development of a ground-based arc-scanning synthetic aperture radar (ArcSAR) system mounted on a truck. ArcSAR formulates synthetic aperture by a horizontal circular motion of antennas attached at the end of an extendable boom. The ArcSAR system is designed to operate in two different imaging modes: the spot mode and the scan mode . The spot mode obtains a high-resolution image by fixing the view angle of antennas toward a target. The scan mode obtains wider image coverage with a reduced resolution by fixing the antennas relative to the boom. Different SAR focusing algorithms were implemented for the accuracy and efficiency of image processing: the time domain algorithm for the spot mode and the range Doppler algorithm for the scan mode. An exemplary X-band ArcSAR spot mode image, obtained with a 180 ° scanning of 4-m boom, has an azimuth resolution of 0.07 ° , which is equivalent to the 12.6-m linear scanning of a conventional ground-based SAR system. An ArcSAR scan mode image was successfully obtained as well, covering a 350 ° image area at an azimuth resolution of 1.07 °, which is 11 times better than that of arc-scanning real aperture radar that would have 11.84 ° azimuth resolution. [ABSTRACT FROM AUTHOR]

This paper proposes a binary coding method, a novel postclassification change detection method that indexes multitemporal satellite images into a single information layer. As a case study, this method is applied to the production of a deforestation map and a tree age map of evergreen trees. Seven images of Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus of Kangwon province in Korea, all obtained in November from 1984 to 2005, were used. Seven forest/nonforest bitmaps were produced by the normalized difference vegetation index thresholding. After the maximum value composite, the binary coding method was applied to convert the five bitmaps into a single-layered binary index map. This simple but intuitive method produced a deforestation map and a tree age map. The deforestation map contains the history of forest fires and massive replantation while the tree age map shows the age of evergreen trees with 30 years of range, both in approximately five-year temporal resolution. Comparison of the results with a digital forest inventory, forest fire records, and field investigations showed good agreement on the south-facing sunny slopes. Errors from geometric and radiometric data processing and inaccuracies of the digital forest inventory were also identified. [ABSTRACT FROM AUTHOR]

To evaluate sea ice concentrations (SICs) from the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E), we observed sea ice with the 6-m-resolution panchromatic electronic optical camera (EOC) sensor onboard the Korea Multi-Purpose Satellite-1 (KOMPSAT-1). A total of 68 cloud-free EOC images were obtained across the Antarctic continental edges from September to November 2005. Sea ice types in the EOC images were classified into white ice (W), gray ice (G), and dark-gray ice (D) and then compared with SSM/I and AMSR-E SICs. Spatiotemporal standard deviation of passive microwave SIC proved useful in selecting temporally stable and spatially homogeneous SICs to overcome the diurnal variation of sea ice in the analysis of data from multiple satellites. In the Antarctic spring, the EOC SIC of W + G showed the best fit to SSM/I SIC calculated by the NASA Team (NT) algorithm (mean difference of -2.3% and rmse of 3.2%), whereas that of W + G + D showed the best fit to AMSR-E SIC calculated by the NT2 algorithm (mean difference of 0.3% and rmse of 1.4%). It is concluded that the SSM/I NT algorithm responds to young ice in addition to the ice types A and B, whereas the AMSR-E NT2 algorithm detects ice type C and thin ice as well. The 4.7% difference of SICs between AMSR-E and SSM/I was attributed to the enhanced detection of ice type C (2.1%) and thin ice (2.6%) of the AMSR-E NT2 algorithm. [ABSTRACT FROM AUTHOR]

Presents a study which analyzed topographic decorrelation (TD) to provide a refined technique for change detection and environmental monitoring using interferometric-synthetic aperture radar (SAR) applications. Critical conditions for TD to occur; How to benefit from intrinsic limitation of the SAR system; Applications.