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To study the applicability of full polarimetric synthetic aperture radar (SAR) data to identify alpine glaciers in the central Himalayas, six polarimetric decomposition methods were used to obtain 20 polarimetric characteristic parameters based on the Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band SAR (PALSAR) data. Object-oriented multiscale segmentation was performed on a Landsat 8 Operational Land Imager (OLI) image prior to classification, and the vector boundaries of different types of training samples were selected from the segmented results. We performed a support vector machine (SVM)-based classification on the characteristic parameters from each polarimetric decomposition. All 20 parameters were then screened and combined according to different requirements: the degree of separability of different types of training samples and the type of scattering mechanisms. The results show that the classification accuracy of the incoherent decomposition characteristics based on the covariance matrix is the best, reaching 87%, and it can exceed 91% after adding the local incidence angle to the suite of classifiers. Eventually, more than 93% accuracy was achieved using a combination of multiple polarimetric parameters, which reduced the misclassification between bare ice and rock. We also analyzed the use of controlling factors on the accuracy of alpine glacier identification and found that the polarimetric information and aspect of the glacier surface are the most important factors. The former is the main basis for identification but the latter will confuse the feature distributions of different categories and cause misclassification.

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.

Lake ice under phase transition shows large variation on radar backscattering due to the changes of dielectric constant and roughness of ice surface and thus the transmissivity of microwave into ice body. To study the effects of freezing/thawing of ice on radar backscattering in a short time, we spread water over lake ice and continuously measured radar backscattering by using a ground-based microwave scatterometer system operated in C-band HH polarization. By establishing scattering models and applying inversion from genetic algorithm, radar returns were separated into ice-surface, volume, and ice-bottom scatterings, and the changes in dielectric constant and roughness parameters of ice surface were estimated as well. Immediately after spreading water on ice surface, ice-surface scattering was strongest due to high dielectric constant of surface water while volume and ice-bottom scatterings were very weak due to low microwave transmissivity into ice body. As surface water was being frozen, ice-surface scattering became weak with decreasing dielectric constant while volume and ice-bottom scattering increased due to higher transmissivity into ice body. In a transition stage, when surface water was almost frozen, all three scatterings increased simultaneously. Crystallization of ice produced rougher surface overcoming the decrease in dielectric constant, resulting in the increase of ice-surface scattering, while volume and ice-bottom scattering was continuously increased due to increasing transmissivity. At the end of the experiment, air temperature rose above freezing point, and ice surface thawed again so that ice-surface scattering increased while volume and ice-bottom scattering were decreased.

This paper presents the variation of the radar backscattering of intertidal mudflats in the west coast of Korea observed by Radarsat-1 synthetic aperture radar (SAR) images and investigates the related factors by an indoor experiment and a field experiment using a ground-based C-band scatterometer. The 15 Radarsat-1 SAR images of the intertidal mudflat near Jebu Island used in this study were all taken at around 6:30 p.m., which is an ideal local time for evaluating the daytime evaporation effects during the 12.4-h tidal cycle. An exposure time map and an evaporation time map of mudflats at the time of each SAR acquisition are calculated based on the tidal records, a digital elevation map generated by the waterline extraction method, and the normalized daily evaporation index. The radar backscattering of the upper intertidal mudflat did not show a monotonic change with evaporation time but a complex pattern. An indoor experiment using a C-band scatterometer on drying mud revealed an M-shaped change (increase-decrease-increase-decrease) of radar backscattering due to various factors that affect dielectric constant and roughness such as the drainage of surface water (increase), evaporation (decrease), mud cracking (increase), and further evaporation (decrease). The variation of backscattering observed from SAR images agreed well with the initial three stages of the indoor experiment (increase-decrease-increase) but did not show the final stage of decrease from continuous evaporation. A field experiment on natural intertidal mudflats showed not only the pattern related to the initial drainage and evaporation but also speckles from biological activity.

This paper proposes a binary coding method, a novel post classification 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.

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.

Topographic decorrelation due to the local surface slope has been an obstacle to interferometric synthetic aperture radar (InSAR) applications. A modified spatial decorrelation function is derived as a function of the baseline and topography. This function explains the origin of the total topographic decorrelation phenomenon on the slopes directly facing radar illumination and layover, which may mislead InSAR coherence image interpretation. The authors define critical terrain slope (or critical incidence angle) as the angle for which two SAR signals completely decorrelate regardless of surface stability. It is found that the width of the critical terrain slope increases with the increase of the component of the baseline perpendicular to the radar look direction. A new analytical method, the ratio coherence imagery, is then introduced to highlight total topographic decorrelation against the temporal decorrelation features. The applications of this methodology are demonstrated in selected locations in the Sahara Desert, Algeria, and Almer/spl inodot//spl acute/a, Spain, using ERS-1 and ERS-2 SAR data.