• Journal of Korea Water Resources Association
• /
• v.45 no.8
• /
• pp.755-765
• /
• 2012

The Land Surface Temperature (LST) is one of the significant factors to understand the water and energy cycles between the land surface and atmosphere. However, few previous studies for spatio-temporal variations of LST has been investigated. In this study, we conducted comparative analyses between the Communication, Ocean and Meteorological Satellite (COMS) and MOderate-Resolution Imaging Spectroradiometer (MODIS) LST data. We compared COMS data with observations to identify the accuracy and found relative underestimated patterns of the COMS data as compared to observations. We also found that COMS LST were underestimated in compare to MODIS LST. The Terra LST was verified to have more similar trends with the COMS LST rather than Aqua LST. While we identified the applicability of COMS based on the results of similar tendencies of two comparisons, more intensive validation research at a variety of field conditions should be conducted to gurantee current COMS LST.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.3
• /
• pp.149-163
• /
• 2004

Evapotranspiration (ET) is a critical component of the hydrologic cycle which influences economic activities as well as the natural ecosystem. While there have been numerous studies on ET estimation for homogeneous areas using point measurements of meteorological variables, monitoring of spatial ET has not been possible at landscape - or watershed - scales. We propose a site-specific application of the land surface model, which is enabled by spatially interpolated input data at the desired resolution. Gyunggi Province of South Korea was divided into a regular grid of 10 million cells with 30m spacing and hourly temperature, humidity, wind, precipitation and solar irradiance were estimated for each grid cell by spatial interpolation of synoptic weather data. Topoclimatology models were used to accommodate effects of topography in a spatial interpolation procedure, including cold air drainage on nocturnal temperature and solar irradiance on daytime temperature. Satellite remote sensing data were used to classify the vegetation type of each grid cell, and corresponding spatial attributes including soil texture, canopy structure, and phenological features were identified. All data were fed into a standalone version of SiB2(Simple Biosphere Model 2) to simulate latent heat flux at each grid cell. A computer program was written for data management in the cell - based SiB2 operation such as extracting input data for SiB2 from grid matrices and recombining the output data back to the grid format. ET estimates at selected grid cells were validated against the actual measurement of latent heat fluxes by eddy covariance measurement. We applied this system to obtain the spatial ET of the study area on a continuous basis for the 2001-2003 period. The results showed a strong feasibility of using spatial - data driven land surface models for operational monitoring of regional ET.

• Journal of Environmental Science International
• /
• v.18 no.4
• /
• pp.375-388
• /
• 2009

Numerical simulation is essential to indicate the flow of the atmosphere in the region with a complicated topography which consists of many mountains in the inland while it is neighboring the seashore. Such complicated topography produces land and sea breeze as the mesoscale phenomenon of meteorology which results from the effect of the sea and inland. In the mesoscale simulation examines, the change of the temperature in relation to the one of the sea surface for the boundary condition and, in the inland, the interaction between the atmosphere and land surface reflecting the characteristic of the land surface. This research developed and simulated PNULSM to reflect both the SST and vegetation effect as a bottom boundary for detailed meteorological numerical simulation in coastal urban area. The result from four experiments performed according to this protocol revealed the change of temperature field and wind field depending on each effect. Therefore, the lower level of establishment of bottom boundary suitable for the characteristic of the region is necessary to figure out the atmospheric flow more precisely, and if the characteristic of the surface is improved to more realistic conditions, it will facilitate the simulation of regional environment.

• Korean Journal of Remote Sensing
• /
• v.30 no.3
• /
• pp.375-381
• /
• 2014

Soil moisture is an essential satellite-driven variable for understanding hydrologic, pedologic and geomorphic processes. The European Space Agency (ESA) has endorsed soil moisture as one of Climate Change Initiates (CCI) and had merged multi-satellites over 30 years. The $0.25^{\circ}$ coarse resolution soil moisture satellite data showed correlations with variables of a water stress index, Temperature-Vegetation Dryness Index (TVDI), from a stepwise regression analysis. The ancillary data from TVDI, Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS were inputted to a multi-regression analysis for estimating the surface soil moisture. The estimated soil moisture was validated with in-situ soil moisture data from April, 2012 to March, 2013 at Andong observation sites in South Korea. The soil moisture estimated using satellite-based LST and NDVI showed a good agreement with the observed ground data that this approach is plausible to define spatial distribution of surface soil moisture.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.3
• /
• pp.90-103
• /
• 2017

This study analyzed the surface temperature characteristics of urban green spaces under high summer temperatures to clarify the functions of green spaces in reducing urban temperatures. We obtained accurate surface temperature data using highresolution unmanned aerial vehicle images of the survey site, which was an isolated green space in the city. We analyzed differences in the surface temperature by land cover type, vegetation type, species type, and the relationship between surface temperature and vegetation volume. Based on the results, among the land cover types, wetlands and forests had low temperatures and paving areas had very high temperatures. Regarding vegetation type, broad-leaved trees had lower temperatures than coniferous trees in forests. However, in planted areas, coniferous trees had lower temperatures than broad-leaved trees. The temperature of long grass was higher than that of short grass, which suggested that the volume of grass affected the temperature. Regarding forest species type, the temperature of broad-leaved Robinia pseudoacacia forest and mixed broad-leaved forest was lower than coniferous Pinus densiflora forest. There was a slight difference in temperature between R. pseudoacacia forest and mixed broad-leaved forest. The analysis of the relationship between vegetation volume and temperature by forest species type indicated a negative correlation, where the temperature decreased with increasing vegetation volume, similar to the results of previous studies. However, we found a weak positive correlation in R. pseudoacacia forest; therefore, an increase in volume may not reduce the surface temperature depending on the dominant species.

• Journal of Environmental Science International
• /
• v.11 no.10
• /
• pp.1133-1140
• /
• 2002

The growth and extent of the local pressure field at any point is of primary importance as it supplies the driving force for the local wind circulation which causes a medium-range transport of air pollutants. The local pressure field is produced by the variation of temperature in the lower layers of the atmosphere, and is called the thermal wave. The thermal wave is influenced by the difference in the diurnal variations between two regions with different surface condition, for example land and sea. This difference produces the land- and sea-breeze phenomenon, and brings corresponding variations in the form of the thermal wave. Daytime temperature over the inland area (Daegu) was higher than that of the coastal area (Busan). The temperature difference reached about 5~6$^{\circ}C$ in the late afternoon(30-31 May 1999). The low pressure system of Daegu was most fully developed at the time. In this study, we investigated the possibility of thermal low onset around Daegu in summer with an analytical model. The topography effect was neglected in the model. We could predict a thermal low-pressure of about 3.4hPa at Daegu with wide flat land surface, when the inland area is about 6K warmer than the coastal area temperature. The pressure decrease is somewhat less than the observed value(4~5 hPa).

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.171-183
• /
• 2016

Land Surface Temperature (LST) retrieved from Landsat 8 measured from 2013 to 2014 and it is corrected by surface temperature observed from ground. LST maps are retrieved from Landsat 8 calculate using the linear regression function between raw Landsat 8 LST and ground surface temperature. Seasonal and annual LST maps developed an average LST from season to annual, respectively. While the higher LSTs distribute on the industrial and commercial area in urban, lower LSTs locate in surrounding rural, sea, river and high altitude mountain area over Seoul and surrounding area. In order to correct the LST, linear regression function calculate between Landsat 8 LST and ground surface temperature observed 3 Korea Meteorological Administration (KMA) synoptic stations (Seoul(ID: 108), Incheon(ID: 112) and Suwon(ID: 119)) on the Seoul and surrounding area. The slopes of regression function are 0.78 with all data and 0.88 with clear sky except 5 cloudy pixel data. And the original Landsat 8 LST have a correlation coefficient with 0.88 and Root Mean Square Error (RMSE) with $5.33^{\circ}C$. After LST correction, the LST have correlation coefficient with 0.98 and RMSE with $2.34^{\circ}C$ and the slope of regression equation improve the 0.95. Seasonal and annual LST maps represent from urban to rural area and from commercial to industrial region clearly. As a result, the Landsat 8 LST is more similar to the real state when corrected by surface temperature observed ground.

• Korean Journal of Remote Sensing
• /
• v.32 no.5
• /
• pp.423-434
• /
• 2016

Surface emissivity and its background values according to each sensor are mandatorily necessary for Mid-Wavelength Infrared (MWIR) remote sensing to retrieve surface temperature and temporal variation. This study presents the methods and results of Land Surface Emissivity (LSE) of the MWIR according to land cover over the Korean Peninsula. The MWIR emissivity was estimated by applying the Temperature Independent Spectral Indices (TISI) method to the Visible Infrared Imaging Radiometer Suite (VIIRS) band 4 Day/Night images ($3.74{\mu}m$ in center wavelength). The obtained values were classified according to land-cover types, and the obtained emissivity was then compared with those calculated from a standard Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) spectral library. The annual means of MWIR emissivity of Deciduous Broadleaf Forest (0.958) and Mixed Forest (0.935) are higher than those of Croplands (0.925) and Natural Vegetation Mosaics (0.935) by about 2-3%. The annual mean of Urban area is the lowest (0.914) with an annual variation of about 2% which is by larger than those (1%) of other land-covers. The TISI and VIIRS based emissivity is slightly lower than the ASTER spectral library by about 2-3% supposedly due to various reasons such as lack of land cover homogeneity. The results will be used to understand the MWIR emissivity properties of the Korean Peninsula and to examine the seasonal and other environmental changes using MWIR images.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.39 no.3
• /
• pp.107-116
• /
• 2011

One of the major factors which increase urban temperature is roads. This paper is aimed to investigate the effect of urban roadside vegetation on the road surface temperature. For this, surface temperature was measured at 18 spots using the thermal imaging camera in terms of road components including use of roadside land use, roadway, sidewalk, roadside vegetation and vegetation median barrier. The size of the roadside vegetation and related urban road characteristics were also measured. In terms of the effect of roadside vegetation on a decrease in road surface temperature, the roadside land use as a green area or open space was the highest, followed by the size of vegetation median barrier and the size of roadside vegetation. Besides road surroundings, an increase in the green zone such as roadside vegetation and median strip vegetation has a significant impact on lowering road surface temperature. Therefore, a good solution for reducing urban heat island effects would be to increase the area of roadside vegetation and green areas along roads.

• Korean Journal of Remote Sensing
• /
• v.20 no.1
• /
• pp.1-11
• /
• 2004

Based on surface energy balance climatology, surface temperatures should respond to drying conditions well before plant response. To test this hypothesis, land surface temperatures (LST) derived from MODIS data were analyzed to determine how the data were correlated with climatic water balance variables and NDVI anomalies during a growing season in Western and Central Kansas. Daily MODIS data were integrated into weekly composites so that each composite data set included the maximum temperature recorded at each pixel during each composite period. Time-integrated, or cumulative values of the LST deviation standardized with mean air temperatures had significantly high correlation coefficients with SM, AE/PE, and MD/PE, ranging from 0.65 to 0.89. The Standardized Thermal Index (STI) is proposed in this study to accomplish the objective. The STI, based on surface temperatures standardized with observed mean air temperatures, had significant temporal relationships with the hydroclimatological factors. STI classes in all the composite periods also had a strong correlation with NDVI declines during a drought episode. Results showed that, based on LST, air temperature observations, and water budget analysis, NDVI declines below normal could be predicted as early as 8 weeks in advance in this study area.