• Journal of the Korean Association of Geographic Information Studies
• /
• v.3 no.1
• /
• pp.1-11
• /
• 2000

The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.343-348
• /
• 1998

In this study, we extracted several terrain information using satellite and aerial images. We detected change of terrain using Landsat Thematic Mapper(TM) and aerial images which are multitemporal data. In change detection processing, we first classified satellite images by ISODATA algorithm which is an unsupervised learning algorithm, then performed change detection. By this method, we could obtain good result. Also we introduce sub-pixel concept to classify road and agriculture area in inaccessible area. In summary, in chang detection processing, we can find that the used method is efficient.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.148-151
• /
• 2004

In this study the micro landform of tide flat in west Seohan bay. North Korea was classified and the change of this environment was detected by using Landsat TM. FTM+, KOMPAST. For this. ISODATA method of the unsupervised methods was used to classify the micro landform while tasseled cap method was used to detect the change of environment in west Seohan bay, North Korea by passing years. This study shows the possibility that the topography analysis and change especially in unapproachable area could be detected and monitored by using satellite images.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.355-355
• /
• 2011

토지피복의 분류는 토지표면의 물리적인 지표면의 상태를 나타내는 자료로 환경, 행정, 수자원, 재해 등 다방면으로 이용되고 있다. 특히 수자원과 관련하여 식생의 증산과 토양의 증발을 통칭하는 증발산과 유출, 토양수분 등과 연관되어 있다. 광범위한 토지피복의 산정에는 경제성 및 주기성 등의 장점으로 인하여 인공위성 영상을 이용하는 기법이 적합하다. 위성영상분류법은 훈련지역의 선정 여부에 따라 감독분류와 무감독 분류로 나누어지며 각각의 알고리즘의 특성에 따라 더욱 세분화된다. 본 연구에서는 Landsat-TM (Thematic Mapper) 영상을 이용하여 감독 분류와 무감독 분류를 각각 적용하여 한강유역의 토지피복을 수역, 시가, 나지 습지, 초지, 산림, 농지의 7가지 부분으로 대분류로 산정하고 비교하였다. 두 경우의 정확도는 각각 91.6%, 90.9%의 비슷한 정확도를 나타내었으며, 세부적으로 우리나라의 대부분의 면적에 분포하는 산림, 농지, 시가, 수역의 정확도가 높게 나타났다. 또한 각 항목별로 정확도를 비교하였을 때 감독분류가 무감독분류에 비해 다소 정확한 것을 확인할 수 있었다. 추후 외부자료를 도입하면 비교적 낮은 정확도를 나타낸 초지, 습지, 나지의 정확도를 보완할 수 있을 것이다.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.103-109
• /
• 1998

A technique on atmospheric correction algorithm for a single band (0.76-0.90 $\mu$m) reflective of Landsat TM imagery has been developed using a radiation transfer model simulation. It proceeds in two steps: First, calculation of the surface reflectance of each pixel based on precomputed planetary albedo functions for actual atmospheres(e. g. radiosonde) and two kinds of atmospheric visibility states. Second, approximate correction of the adjacency pixel effect by taking into account the average reflectance in an 7 $\times$ 7 pixel neighbourhood and using appropriate land cover classification in reflectance. The correction functions are provided by MODTRAN model.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.159-162
• /
• 1998

Land cover and land use classification on a huge scale, e.g. national or continental scale, has become more and more important because environmental researches need land cover: And land use data on such scales. We developed a crop field extraction method, which is one of the steps in our land cover classification system for a huge area. Firstly, a crop field model is defined to characterize "crop field" in terms of NDVI value and textual information Textual information is represented by the density of straight lines which are extracted by wavelet transform. Secondly, candidates of NDVI threshold value are determined by "scale-space filtering" method. The most appropriate threshold value among the candidates is determined by evaluating the line density of the area extracted by the threshold value. Finally, the crop field is extracted by applying level slicing to Landsat TM image with the threshold value determined above. The experiment demonstrates that the extracted area by this method coincides very well with the one extracted by visual interpretation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.7 no.1
• /
• pp.49-57
• /
• 1989

On this study, we performed the landuse classification using the Landsat data acquired before and after reclamation, and extracted the ground temperature from infrared band(TM band6) data. Using the satellite data, it was possible to extract changes of landuses effectively according to the reclamation, and could obtain the thermal characteristics of the reclaimed area and the surroundings by converting infrared data value into temperatures of surfaces of ground and water. The result of this analysis will be used for the land management of large-scale reclaimed area applying the satellite data and related information.

• Journal of the Korean GEO-environmental Society
• /
• v.6 no.4
• /
• pp.73-80
• /
• 2005

The domestic Remote Sensing field uses mainly Landsat TM image that is used to the monitoring of the wide area. In this study, it is analyzed the land cover change of rural and urban area by time series using satellite images and is proposed the vision for a urban balanced development. It execute an analysis for urban change which is a fundamental data of city planning through the integration of the spatial analysis technique of GIS and Remote Sensing using satellite data.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.44-46
• /
• 2003

In 1996, Thailand's participation in the Pacific Rim as a part of NASA's Mission to Planet Earth (MTPE) Program, was titled 'AIRSAR Thailand Project'. In this project the Department of Land Development utilized Topographic SAR (TOPSAR) which had multi-frequencies: C band, L band, and P band with multi-polarization: HH, VV, and HV as well as C band VV DEM. Satellite data such as LANDSAT TM was also utilized for optimal use. Results of AIRSAR image processing including data fusion among difference wavelength bands and polarization revealed the quality of AIRSAR that best suit for detection of agricultural land uses. The HH-L band AIRSAR was proven to be useful to distinguish among crop types when combined with appropriate data. The HH, VV, and HV-P band enhanced surface characteristics of swamp forest and wetland. In addition, TOPSAR has its great advantage for identification of salt farms and shrimp ponds.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.262-266
• /
• 1999

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.