• The Korean Journal of Quaternary Research
• /
• v.23 no.1
• /
• pp.42-53
• /
• 2009

In response to the abrupt climate change in recent years, atmosphere, ocean and cryosphere are reported to be altered. In addition to these changes, the land surface is also gradually changing and its impact on the global climate may not be negligible. The land surface change impacts the global climate via two ways, the biogeochemical and biophysical feedbacks. The biogeochemcial change in the land surface modifies the atmospheric trace-gas concentrations through a change in photo synthesis, while biophycal changes of the land surface alters the surface albedo, which influences the amount of the short wave radiative heat fluxes. There are many examples in the past that the change in land surface greatly influences the global climate change. The recent IPCC report has suggested that the climate change will occur rather abrubtly in the near future. In order to predict the future climate accurately, the impact of the land surface change is fully considered.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.22-24
• /
• 2004

The land use has changed rapidly since 1960s in accordance with urbanization in Seoul Metropolitan Region. As a result, the urban microclimate has undergone changes as well. This study aims to recognize trend of the urban heat island change which is caused by land use change during urbanization in large city. Thermal data of Landsat TM images in 1987 and 1999 were for land surface temperature change detection in the study.

• Journal of the Korean Geographical Society
• /
• v.40 no.3 s.108
• /
• pp.296-309
• /
• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Journal of Korean Society for Geospatial Information Science
• /
• v.13 no.4 s.34
• /
• pp.59-65
• /
• 2005

It is very important to detect land cover/land use change from the past and to use it for future urban plan. This paper investigated the application of Landsat satellite imagery for detecting urban growth and assessing its impact on surface temperature in the region. Land cover/land use change detection was carried out by using 30m resolution Landsat satellite images and hierarchial approach was introduced to detect more detail change on the changing area through high resolution aerial photos. Also, surface temperature according to land cover/land use was calculated from Landsat TM thermal infrared data and compared with real temperature to analyze the relationship between urban expansion and surface temperature. As a result, the urban expansion has raised surface radiant temperature in the urbanized area. The method using remote sensing data based on GIS was found to be effective in monitoring and analysing urban growth and in evaluating urbanization impact on surface temperature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.21 no.3
• /
• pp.261-267
• /
• 2003

We are able to simultaneously extract the land surface change information, as we input each information extracted from images classified during the two periods, as the attribute information of geographic information, and then use it a parameter of GIS. Hence, this research sought to present basic data far efficient management and development of land surface, together with land use trends, by using the remote-sensing technique enabling the acquisition of the land surface covering information, as well as the benefits of GIS. The research conducted a study on the extraction of land surface change information, and made it possible to treat image information easily compared to the existing image classification methods, thereby making it easy to know the land surface change process for each pixel.

• Korean Journal of Remote Sensing
• /
• v.39 no.1
• /
• pp.99-110
• /
• 2023

Land surface temperature (LST) is a critical environmental indicator affected by land cover (LC) changes. Currently, the most convenient and fastest way to retrieve LST is to use remote sensing images due to their continuous monitoring of the Earth's surface. The work intended to investigate land cover change and temperature response inAn-Najaf province. Landsat multispectral imageries acquired inAugust 1989, 2004, and 2021 were employed to estimate land cover change and LST responses. The findings exhibited an increase in water bodies, built-up areas, plantations, and croplands by 7.78%, 7.27%, 6.98%, 3.24%, and 7.78%, respectively, while bare soil decreased by 25.27% for the period (1989-2021). This indicates a transition from barren lands to different land cover types. The contribution index (CI) was employed to depict how changes in land cover categories altered mean region surface temperatures. The highest LSTs recorded were in bare lands (42.2℃, 44.25℃, and 46.9℃), followed by built-up zones (41.6℃, 43.96℃, and 44.89℃), cropland (30.9℃, 32.96℃, and 34.76℃), plantations (35.4℃, 36.97℃, and 38.92℃), and water bodies (27.3℃, 29.35℃, and 29.68℃) respectively, in 1989, 2004, and 2021. Consequently, these changes resulted in significant variances in LST between different LC types.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.2
• /
• pp.113-122
• /
• 2021

Urban expansion, particularly converting sub-urban areas to residential and commercial land use in metropolitan areas, has been considered as a significant signal of regional economic development. However, this results in urban climate change. One of the key impacts of rapid urbanization on the environment is the effect of UHI (Urban Heat Island). Understanding the effects of urban land cover change on UHI is crucial for improving the ecology and sustainability of cities. This research reports an application of remote sensing data, GIS (Geographic Information Systems) for assessing effects of urban land cover change on the LST (Land Surface Temperature) and heat budget components in Ho Chi Minh City, where is one of the fastest urbanizing region of Vietnam. The change of urban land cover component and LST in the city was derived by using multi-temporal Landsat data for the period of 1998 - 2020. The analysis showed that, from 1998 to 2020 the city had been drastically urbanized into multiple directions, with the urban areas increasing from approximately 125.281 km² in 1998 to 162.6 km² in 2007, and 267.2 km² in 2020, respectively. The results of retrieved LST revealed the radiant temperature for 1998 ranging from 20.2℃ to 31.2℃, while that for 2020 remarkably higher ranging from 22.1℃ to 42.3℃. The results also revealed that given the same percentage of urban land cover components, vegetation area is more effective to reduce the value of LST, meanwhile the impervious surface is the most effective factor to increase the value of the LST.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.927-929
• /
• 2003

Using received northeast region in China of Terra/MODIS data at Tokyo University of information Sciences. Make monthly division Land Surface Temperature maximum composite image. Using monthly division Land Surface Temperature maximum composite image, considered characteristic of monthly variation of Land surface temperature and relation with land covering and NDVI at the northeast region in China.

• Atmosphere
• /
• v.28 no.4
• /
• pp.427-441
• /
• 2018

This study examines the impact of the urban parameterization scheme and the land cover change on simulated near surface temperature using Unified Model (UM) over the Seoul metropolitan area. We perform four simulations by varying the land cover and the urban parameterization scheme, and then compare the model results with 46 AWS observation data from 2 to 9 August 2016. Four simulations were performed with different combination of two urban parameterization schemes and two land cover data. Two schemes are Best scheme and MORUSES (Met Office Reading Urban Surface Exchange Scheme) and two land cover data are IGBP (International Geosphere and Biosphere Programme) and EGIS (Environmental Geographic information service) land cover data. When land use data change from IGBP to EGIS, urban ratio over the study area increased by 15.9%. The results of the study showed that the higher change in urban fraction between IGBP and EGIS, the higher the improvement in temperature performance, and the higher the urban fraction, the higher the effect of improving temperature performance of the urban parameterization scheme. 1.5-m temperature increased rapidly during the early morning due to increase of sensible heat flux in EXP2 compared to CTL. The MORUSES with EGIS (EXP3) provided best agreement with observations and represents a reasonable option for simulating the near surface temperature of urban area.

• Korean Journal of Remote Sensing
• /
• v.32 no.1
• /
• pp.39-48
• /
• 2016

Yangon Mega City is densely populated and most urbanization area of Myanmar. Rapid urbanization is the main causes of Land Use and Land Cover (LULC) change and they impact on Land Surface Temperature (LST). The objectives of this study were to investigate on the LST with respect to LULC of Yangon Mega City. For this research, Landsat satellite images of 1996, 2006 and 2014 of Yangon Area were used. Supervised classification with the region of interest and calculated change detection. Ground check points used 348 points for accuracy assessment. The overall accuracy indicated 89.94 percent. The result of this paper, the vegetation area decreased from $1061.08sq\;km^2$ (24.5%) in 1996 to $483.53sq\;km^2$ (11.2%) in 2014 and built up area clearly increased from $485.33sq\;km^2$ (11.2%) in 1996 to $1435.72sq\;km^2$ (33.1%) in 2014. Although the land surface temperature was higher in built up area and bare land, lower value in cultivated land, vegetation and water area. The results of the image processing pointed out that land surface temperature increased from $23^{\circ}C$, $26^{\circ}C$ and $27^{\circ}C$ to $36^{\circ}C$, $42^{\circ}C$ and $43.3^{\circ}C$ for three periods. The findings of this paper revealed a notable changes of land use and land cover and land surface temperature for the future heat management of sustainable urban planning for Yangon Mega city. The relationship of regression experienced between LULC and LST can be found gradually stronger from 0.8323 in 1996, 0.8929 in 2006 and 0.9424 in 2014 respectively.