• Ocean Science Journal
• /
• v.41 no.2
• /
• pp.97-104
• /
• 2006

A useful radiance-converting method was developed to convert the Landsat-7 ETM+thermal-infrared (TIR) band's radiance ($L_{{\lambda},L7/ETM+}$) to that of Landsat-5 TM TIR ($L_{{\lambda},L5/TM+})$ as: $L_{{\lambda},L5/TM}=0.9699{\times}L_{{\lambda},L7/ETM+}+0.1074\;(R^2=1)$. In addition, based on the radiance-converting equation and the linear relation between digital number (DN) and at-satellite radiance, a DN-converting equation can be established to convert DN value of the TIR band between Landsat-5 and Landsat-7. Via this method, it is easy to integrate Landsat-5 and Landsat-7 TIR data to retrieve the sea surface temperature (SST) in coastal waters on the basis of local empirical algorithms in which the radiance or DN of Lansat-5 and 7 TIR band is usually the only input independent variable. The method was employed in a local empirical algorithm in Daya Bay, China, to detect the thermal pollution of cooling water discharge from the Daya Bay nuclear power station (DNPS). This work demonstrates that radiance conversion is an effective approach to integration of Landsat-5 and Landsat-7 data in the process of a SST retrieval which is based on local empirical algorithms.

• Journal of the Korean earth science society
• /
• v.35 no.1
• /
• pp.54-68
• /
• 2014

In order to analyze the land surface properties in Seoul and its surrounding metropolitan area, several indices and land surface temperature were calculated by the Landsat satellites (e.g., Landsat 5, Landsat 7, and Landsat 8). The Landsat data came from only in the fall season with Landsat 5 on October 21, 1985, Landsat 7 on September 29, 2003, and Landsat 8 on September 16, 2013. The land surface properties used are the indices that represented Soil Adjusted Vegetation Index (SAVI), Modified Normalized Difference Wetness Index (MNDWI), Normalized Difference Wetness Index (NDWI), Tasseled cap Brightness, Tasseled cap Greenness, Tasseled cap Wetness Index, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) and the land surface temperature of the area in and around Seoul. Most indices distinguish very well between urban, rural, mountain, building, river and road. In particular, most of the urbanization is represented in the new city (e.g., Ilsan) around Seoul. According to NDVI, NDBI and land surface temperature, urban expansion is displayed in the surrounding area of Seoul. The land surface temperature and surface elevation have a strong relationship with the distribution and structure of the vegetation/built-up indices such as NDVI and NDBI. While the NDVI is positively correlated with the land surface temperature and is also negatively correlated with the surface elevation, the NDBI have just the opposite correlations, respectively. The NDVI and NDBI index is closely associated with the characteristics of the metropolitan area. Landsat 8 and Landsat 5 have very strong correlations (more than -0.6) but Landsat 7 has a weak one (lower than -0.5).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.8
• /
• pp.3692-3697
• /
• 2012

Landsat 7 ETM+ sensor is getting imageries in the SLC-off state since May 31, 2003 due to mechanical defect of SLC(Scan Line Corrector). Therefore additional correction works are required to use these imageries. In this study, Landsat 7 SLC-off imageries were corrected using Gapfill function and compared with Landsat 5 around the same time. Most of pixels in omitted areas due to SLC-off by producing SLC-off imageries and imageries without visual incompatibility could be achieved as there were not unnatural noises. Also, the corrected imageries were performed land cover classification which was compared with the classification result using reference image. To do this, it could be suggested the possibility of SLC-off imagery. Landsat 7 SLC-off corrected imageries will improve the difficult conditions to detect changes of large areas and be used to detect changes of large areas and classify imageries as well as to recover imagery loss arising regionally such as small scale cloud, etc.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.2
• /
• pp.31-43
• /
• 2005

Four time points of the fractional area data during the 15 years of the highest group of land surface temperature and the lowest group of NDVl of the Kunsan city Chollabuk_do, Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the intention to detect the changes of urban land cover. As long as the effective contributions of satellite images in the continuous monitoring of the wide area for wide range of time period, Landsat-5 TM and Landsat-7 ETM+ artificial satellite images, acquisited over the Kunsan city area, are surveyed by the compared calibration after quantization and classification of the deviations between TM and ETM+ images substituted approved error correction thresholds such as gains and biases or offsets. This experiment and research applied Landsat-5 TM and Landsat-7 ETM+ artificial satellite images in change detection of urban land cover in urbanized Kunsan city, then detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of NDVI which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of NDVI will be able to give proof an effective suitability to the land city change detection monitoring.

• 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.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2006.04a
• /
• pp.229-234
• /
• 2006

On May 31, 2003. Landsat 7 experienced an anomaly causing the Scan Line Corrector(SLC) to stop functioning normally. The SLC-off causes individual scan lines to alternately overlap and then leave large gaps at the edge of the Image. A many scientists with ongoing experience using ETM+ data evaluated the scientific usability and validity of Landsat 7 products containing the SLC anomaly The best reference scene for gap-filling is the other SLC-on Landsat scene that provide same resolution, few changes, and similar data acquisition. But receiving of Landsat imagery is not stable in Korea. So SPOT image can be another alternative solution because it is a steady-state multispectral satellite image as Landsat image. In this study, we filled the SLC-off gap s of 2, 3, 4 bands using SPOT image by a local regression technique, and assigned the optimum spectral value to gaps of 1, 5, 7 bands based on a spectral adjacency. Through this process, we could restore Landsat SLC-off image and evaluated the accuracy of the results.

• Korean Journal of Remote Sensing
• /
• v.7 no.1
• /
• pp.29-43
• /
• 1991

The study was performed to extraction the ground water potential area using LANDSAT TM data. The image processing techniques developed for the study are contrast transformation, differential filtering and pseudo stereoscopic image methods. These were examined for lineament extraction, lineament interpretation and the integration of vertor data with LANDSAT data. The differential filtering method is much usefull for lineament extraction, and all direction lineaments are clearly shown on the band 5 image of LANDSAT TM. The pseudo stereoscopic image are made in which color differential method is adopted, the pair images are usefull for the lineament interpretation. The results of the analysis are as follows. 1) there is a close correlation between lineament and cased well in the study area, because 33 wells of the developed 45 cased wells coincide with the lineaments. 2) 21 sites in the study area were selected for pumping test, and as a result 11 sites of them produces over than 200 ton/day.

• Journal of Cadastre & Land InformatiX
• /
• v.47 no.1
• /
• pp.27-35
• /
• 2017

Human activity such as agriculture, industrial development and urban sprawl has been the major threat to wetlands ecosystem, which have caused the greatest losses of coastal wetlands. The Garorim bay provides one of the most important wetland habitate and Ministry of Oceans and Fisheries designated Garorim bay to marine ecosystem protected area in July 2016. The purpose of this research is to analysis the spatial pattern of Garorim bay using Landsat 5 (TM), Landsat 7 (ETM+), Landsat 8 (OLI & TIRS). The surface temperature and NDVI of Garorim bay were processed with spatial analysis method and time series analysis were applied to 25 years Landsat satellite 19 images. The results of time series distribution map compared with the several wetland habitate on remotely sensed images. Landsat images showed the change area of wetland vegetation distribution from 1988 to 2014. The southern part habitate of Garorim bay have been changed with vegetation patterns on coastal wetland which were covered with tidal flat.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.29 no.2
• /
• pp.123-131
• /
• 2011

Characteristics of sea surface temperature(SST) difference around Gwang-Yang steel Mill where can affect marine ecosystem in Gwang-Yang bay using 25 collected Landsat-7 ETM+ thermal infrared band data from 2000 to 2010. To analyze accuracy of SST from the Landsat-7 ETM+ thermal infrared image， satellite-induced SST was verfied by compared Yeo-Su tide station and Landsat thermal image. As a result, SST from Landsat-7 ETM+ is $1.22^{\circ}C$ lower than sea temperature from Yeo-Su tide station and correlation coefficient resulted in above 0.991 which means that correlation coefficient between Landsat image temperature and field sea temperature is relatively high. Five regions were selected to analyze sea surface temperature between near Gwang-Yang steel mill and the open sea and analyzed timeseries of sea surface temperature seasonally and regionally. Moreover, the additional analysis has been carried out by comparing the averaged temperatures of Gwang-Yang and Soon-Cheon bays using the dataset over a year.

• Korean Journal of Remote Sensing
• /
• v.29 no.5
• /
• pp.443-459
• /
• 2013

Located on Java subduction zone, Merapi volcano is an active stratovolcano with a volcanic activity cycle of 1-5 years. Merapi's eruptions were relatively small with VEI 1-3. However, the most recent eruption occurred in 2010 was quite violent with VEI 4 and 386 people were killed. In this study, we have attempted to study the characteristics of Merapi's eruptions during 18 years using optical Landsat images. We have collected a total of 55 Landsat images acquired from July 6, 1994 to September 1, 2012 to identify pyroclastic flows and their temporal changes from false color images. To extract areal extents of pyroclastic flows, we have performed supervised classification after atmospheric correction by using COST model. As a result, the extracted dimensions of pyroclastic flows are nearly identical to the CVP monthly reports. We have converted the thermal band of Landsat TM and ETM+ to the surface temperature using NASA empirical formula and calculated time-series of the mean surface temperature in the area of peak temperature surrounding the crater. The mean surface temperature around the crater repeatedly showed the tendency to rapidly rise before eruptions and cool down after eruptions. Although Landsat satellite images had some limitations due to weather conditions, these images were useful tool to observe the precursor changes in surface temperature before eruptions and map the pyroclastic flow deposits after eruptions at Merapi volcano.