• Journal of the Korean Association of Geographic Information Studies
• /
• v.12 no.2
• /
• pp.52-68
• /
• 2009

The purpose of this study is to establish the management area using assessment of the conservation value on forest wetland, Sandeul wetland in Mt. Jaeyak, Miryang-si, Gyeongsangnam-do, Korea. The six assessment factors were selected through the review of previous researches and written evidences such as wetland vegetation, hydrological factor, soil factor, topographical factor, naturalness and risk. The assessment data were built on the basis of digital topographic maps, digital detailed soil maps, high resolution satellite images and field surveys of three times. According to the result of assessment of the conservation value and establishment the management area, the core area which has the highest conservation value was occupied by 1.9ha and the conservation area which conservation value is 2 grades was occupied by 33.7ha. The buffer area surrounded core area and conservation area was analyzed by 33.7ha. The transition area which conservation value is 4 grades showed by the widest area(151.2ha) and restoration area that is the ecological hazard area was occupied by 1.7ha. In conclusion, these results can provide methods and basic informations for conserving and managing wetlands because the management area was classified scientifically considering rational processes.

• Journal of Korea Multimedia Society
• /
• v.6 no.1
• /
• pp.28-39
• /
• 2003

This paper is an overview of research contributions by the authors to the use of compression techniques to handle high resolution, multi-spectral images. Originally developed in the remote sensing context, the same techniques are here applied to food and medical images. The objective is to point out the potential of this kind of processing in different contexts such as remote sensing, food monitoring, and medical imaging and to stimulate new research exploitations. Compression is based on the simple assumption that it is possible to find out a relationship between pixels close one each other in multi-spectral images it translates to the possibility to say that there is a certain degree of correlation within pixels belonging to the same band in a close neighbourhood. Once found a correlation based on certain coefficient on one band, the coefficients of this relationship are, in turn, quite probably, similar to the ones calculated in one of the other bands. Based upon this second observation, an algorithm was developed, able to reduce the number of bit/pixel from 16 to 4 in satellite remote sensed multi-spectral images. A comparison is carried out between different methods about their speed and compression ratio. As reference it was taken the behaviour of three common algorithms, LZW (Lempel-Ziv-Welch), Huffman and RLE (Run Length Encoding), as they are used in common graphic format such as GIF, JPEG and PCX. The Presented methods have similar results in both speed and compression ratio to the commonly used programs and are to be preferred when the decompression must be carried out on line, inside a main program or when there is the need of a custom made compression algorithm.

• Atmosphere
• /
• v.15 no.2
• /
• pp.75-90
• /
• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.141-153
• /
• 2016

Reliable assessment of Land Use and Land Cover (LULC) changes greatly improves many practical issues in hydrography, socio-geographical research such as the observation of erosion and accretion, coastal monitoring, ecological effects evaluation. Remote sensing imageries can offer the outstanding capability to monitor nature and extent of land and associated changes over time. Nowadays accurate analysis using remote sensing imageries with high spatio-temporal resolution is required for environmental monitoring. This study develops a methodology of mapping and change detection in LULC by using classified Korea Multi-Purpose Satellite-2 (KOMPSAT-2) multispectral imageries at Jeonbuk and Jeonnam provinces including protected tidal flats located in the west coasts of Korean peninsula from 2008 to 2015. The LULC maps generated from unsupervised classification were analyzed and evaluated by post-classification change detection methods. The LULC assessment in Jeonbuk and Jeonnam areas had not showed significant changes over time although developed area was gradually increased only by 1.97% and 4.34% at both areas respectively. Overall, the results of this study quantify the land cover change patterns through pixel based analysis which demonstrate the potential of multispectral KOMPSAT-2 images to provide effective and economical LULC maps in the coastal zone over time. This LULC information would be of great interest to the environmental and policy mangers for the better coastal management and political decisions.

• Korean Journal of Remote Sensing
• /
• v.29 no.2
• /
• pp.219-233
• /
• 2013

In this study, spatio-temporal variations of Land Surface Emissivity (LSE) of the three LSE data sets in the Asian-Oceanian regions were addressed. The MODerate Resolution Imaging Spectroradiometer (MODIS) LSE, Cooperative Institute for Meteorological Satellite Studies (CIMSS) LSE, and Kongju National Univ. (KNU) LSE data sets were used. The three data sets showed very similar emissivity in the Tibetan Plateau, desert in the Middle East and Australia, and low latitude regions irrespective of season. The emissivity of $12{\mu}m$ was systematically greater than that of $11{\mu}m$, in particular, in the Tibetan Plateau, desert over Middle East and Australia. In general, they showed a weak seasonal variation in the low latitude regions although the emissivity was different among them. However, the three data sets showed quite different spatial and temporal variations in the other regions of Asian-Oceanian regions. The KNU LSE showed a systematic seasonal variation with a high emissivity during summer and low emissivity during winter but the other two LSE data sets showed irregular seasonal variations without regard to the regions. And the annual mean correlations of $11{\mu}m$ and $12{\mu}m$ between KNU LSE and MODIS LSE (KNU LSE and CIMSS LSE; MODIS LSE and CIMSS LSE) were 0.423 and 0.399 (0.330, 0.101; 0.541, 0.154), respectively. The relatively low correlations and strong inter-month variations, in particular, in $12{\mu}m$, indicated that consistency in spatial variation was very low. The comparison results showed that caution should be given before operational use of the LSE data sets in these regions.

• Korean Journal of Remote Sensing
• /
• v.36 no.3
• /
• pp.487-501
• /
• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.10 no.4
• /
• pp.77-85
• /
• 1990

The application of remote sensing in small scale mapping has recently been widened to various fields such as information analysis of landuse, environmental conservation and natural resources. SPOT imagery, in particular, offers data which can be processed for 3-dimensional point determination. This is made possible by its high resolution, appropriate swatch width/altitude ratio and stereo imaging capabilities. This study aims to develop a suitable polymonial and an algorithm in the determination of exterior orientation which is essential in the 3-dimensional point determination of SPOT imgery. An algorithm is presented in this study to determine the exterior orientation of a preprocessed level lB film of the satellite image. It was found that a polynominal of 15 parameters is the best fit polynominal for exterior orientation determination, where 1st order line function is used for positon ($X_o$, $Y_o$, $Z_o$) and 2nd order line function is used for orientation (${\kappa}_o$, ${\phi}_o$, ${\omega}_o$).

• Journal of the Korean association of regional geographers
• /
• v.9 no.4
• /
• pp.425-436
• /
• 2003

Integrated approach is presented by developing the technology and the ways of the practical use of the integrated digital map of and Electronical Navigational Chart (ENC) and Digital Terrain Map (DTM) for the effective and scientific based conservation, development and management of coastal area in this study. At first as preliminary studies to make eventual integrated maps, the necessity of the integrated map is described with the concept of coastal areas. Then, the characteristics of digital maps developed by Korean Geography Institute and National Marine Investigation Institute are carefully analyzed and integrated to a digital map as a test for edge matching in coastal line. Developed test coastal map was overlayed with a high-resolution satellite image (KVR-1000). The ground survey using Global Positioning System was conducted for the analysis of edge matching along the coastal line. Results from the edge matching analysis of coastal lines showed about 14 meters mean difference in artificial terrain and 4 meters mean difference in natural terrain. The problems, causes and solutions for the edge-matched differences are described. Furthermore, the value of utilization, the future use and various fields of application produced by the integrated digital map database are suggested as a basis for ICZM implementation in South Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.14 no.2
• /
• pp.127-139
• /
• 1996

This paper presents a procedure to recover sea surface heights (SSH) and free-air (FA) gravity anomalies from dense satellite altimeter SSH data with enhanced accuracies over the full spectrum of the gravity field. A wavenumber correlation filtering (WCF) of co-linear SSH tracks is developed for the coherent signals of sub-surface geological masses. Orbital cross-over adjustments with bias parameters are applied to the filtered SSH data, which are then separated into two groups of ascending and descending tracks and gridded with tensioned splines. A directional sensitive filter (DSF) is developed to reduce residual errors in the orbital adjustments that appear as track patterned SSH. Finally, FA gravity anomalies can be obtained by the application of a gradient filter on a high resolution estimate of geoid undulations after subtracting dynamic sea surface topography (DSST) from the SSH. These procedures are applied to the Geosat Geodetic Mission (GM) data of the southern oceans in a test area of ca. $900km\;\times{1,200}\;km$ to resolve geoid undulations and FA gravity anomalies to wavelengths of-10 km and larger. Comparisons with gravity data from ship surveys, predictions by least squares collocation (LSC), and 2 versions of NOAA's predictions using vertical deflections illustrate the performance of this procedure for recovering all elements of the gravity spectrum. Statistics on differences between precise ship data and predicted FA gravity anomalies show a mean of 0.1 mgal, an RMS of 3.5 mgal, maximum differences of 10. 2 mgal and -18.6 mgal, and a correlation coefficient of 0.993 over four straight ship tracks of ca. 1,600 km where gravity changes over 150 mgals.

• Korean Journal of Remote Sensing
• /
• v.30 no.2
• /
• pp.315-329
• /
• 2014

In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.