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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Remote Sensing
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Journal DOI :
The Korean Society of Remote Sensing
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Volume & Issues
Volume 1, Issue 1 - May 1985
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A Hill-Sliding Strategy for Initialization of Gaussian Clusters in the Multidimensional Space
Park, J.Kyoungyoon ; Chen, Yung-H. ; Simons, Daryl-B. ; Miller, Lee-D. ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 5~27
A hill-sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimates of sample data for the first step of iterative unsupervised classification. The underlying assumption in this approach was that each cluster possessed a unimodal normal distribution. The key idea was that a clustering function proposed could distinguish elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill-sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with Landsat multispectral scanner (MSS) data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill-sliding clustering technique developed herein has the potential applicability to decomposition of any multivariate mixture distribution into a number of unimodal distributions when an appropriate diatribution function to the data set is employed.
A Microcomputer Based Image Processing System for Remotely Sensed Data
Lim, Young-S. ; Lee, Kyung-K. ; Pak, Kyu-H. ; Kim, Myung-Hwan ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 29~37
A low cost image processing system based on a CROMEMCO microcomputer called KAIS-MIPS, is developed for processing remotely sensed Landsat data. It hardware system can be easily interfacd with other peripheral devices. The software system provides flexibility, expansibility, portability, and maintainability as well as extensive processing capacity. As an example, processing and land use classification of Landsat 2 data for the Inchun city and its 6vicinity in Korea are provided.
A Geological Study on the Seoul-Dongducheun Lineament Using Digital Image Processing Teachniques of Landsat Data
姜必鍾 ; 智光薰 ; 曺民肇 ; 崔映燮 ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 39~51
The study was emphasized on application of the digital image processing techniques for lineament analysis. The major lineament of the study area belongs to Choogaryong faults which many geologists have studied since 1903. Also the lineament is so significant in geological views, because the lineament runs through Seoul area. The several image processing methods such as gradient, Laplacian and spatial filter have been applied, and the spatial filtering is most suitable method for lineament analysis among them. The lineaments distribute predominently in the N20.deg.-30.deg.E trend and N80.deg.-90.deg.W trend which have the conjugated relationship each other, and it coincides with the Gyeongsang conjugate system. The circular structure of study area was developed by cooling circular joint.
A Study on Modeling of Spatial Land-use Prediction
Kim, Eui-Hong ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 53~61
The purpose of the study is to establish models of land use prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-disciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-use projection strategy emerged as a synthesis of the probability transition model and the discriminant-annlysis model. A discriminant model is applied to all pixels in CheJoo landscape plane to predict the most likely change in land use. The probability transition model provides the number of these pixels that will convert to different land use in a gives future time increment. The synthetic model predicts the future change in land use and its volume of pixels in the landscape plane.
Correlations of Rice Grain Yields to Radiometric Estimates of Canopy Biomass as a Function of Growth Stage, : Hand-Held Radiometric Measurements of Two of the Thematic Mapper's Spectral Bands Indicate that the Forecasting of Rice Grain Yields is Feasible at Early to Mid Canopy Development Stages
Yang, Young-Kyu ; Miller, Lee-D. ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 63~87
Considerable experience has been reported on the use of spectral data to measure the canopy biomass of dryland grain crops and the use of these estimates to forecast subsequent grain yield. These basic procedures were retested to assess the use of the general process to forecasting grain yield for paddy rice. The use of the ratio of a multiband radiometer simulation of Thematic Mapper band 4(.76 to .90 .mu.m) divided by band 3 (.63 to .69 .mu.m) was tested to estimate the canopy biomass of paddy rice as a function of the stage of development of the rice. The correlation was found to be greatest (R = .94) at panicle differentiation about midway through the development cycle of the rice canopy. The use of this ratio of two spectral bands as a surrogate for canopy biomass was then tested for its correlation against final grain yield. These spectral estimates of canopy biomass produced the highest correlations with final grain yield (R = .87) when measured at the canopy development stages of panicle differentiation and heading. The impact of varying the amounts of supplemental nitrogen on the use of spectral measuremants of canopy biomass to estimate grain yield was also determined. The effect of the development of a significant amount of weed biomass in the rice canopy was also clearly detected.
Development of the Hill-Sliding Clustering Algorithm Using BASIC Language
鄭夢炫 ; 崔圭弘 ; 朴景允 ; Park, J.Kyoungyoon ;
Korean Journal of Remote Sensing, volume 1, issue 1, 1985, Pages 89~97
An algorithm for the Hill-Sliding Clustering (HSC) method was developed using the BASIC language for Apple II personal computer. It was designed for initialization of clusters from multivariate multimodal Gaussian data. Landsat multispectral imagery data of a Korean coastal area were used for its performance test. The test showed encouraging results.