• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.609-616
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• 2019

Land surface temperature ($T_s$) is a critical variable for understanding the surface energy exchange between land and atmosphere. Using the data measured from micrometeorological flux towers, three types of $T_s$, obtained using a thermal-infrared radiometer (IRT), a net radiometer, and an equation for sensible heat flux, were compared. The $T_s$ estimated using the net radiometer was highly correlated with the $T_s$ obtained from the IRT. Both values acceptably fit the $T_s$ from the Terra/MODIS (Moderate Resolution Imaging Spectroradiometer)satellite. These results will enhance the measurement of land surface temperatures at various scales. Further, they are useful for understanding land surface energy partitioning to evaluate and develop land surface models and algorithms for satellite remote sensing products associated with surface thermal conditions.

• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.44-51
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• 2021

Rapid urbanization and population growth have caused substantial land use land cover (LULC) change in the Kathmandu valley. The lack of temporal and geographical data regarding LULC in the middle mountain region like Kathmandu has been challenging to assess the changes that have occurred. The purpose of this study is to investigate the changes in LULC in Chandragiri Municipality between 1996 and 2017 using geographical information system (GIS) and remote sensing. Using Landsat imageries of 1996 and 2017, this study analyzed the LULC change over 21 years. The images were classified using the Maximum Likelihood classification method and post classified using the change detection technique in GIS. The result shows that severe land cover changes have occurred in the Forest (11.63%), Built-up areas (3.68%), Agriculture (-11.26%), Shrubland (-0.15%), and Bareland (-3.91%) in the region from 1996 to 2017. This paper highlights the use of GIS and remote sensing in understanding the changes in LULC in the south-west part of Kathmandu valley.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.399-415
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• 2014

The intensity of stormwater runoff is particularly acute across cities located in arid climates. During flash floods loose sediment and pollutants are typically transported across sun-hardened surfaces contributing to widespread degradation of water quality. Rapid, dense urbanization exacerbates the problem by creating continuous areas of impervious surfaces, perforated only by a few green patches. Our work demonstrates how the latest techniques in remote sensing can be used to routinely measure urban land cover types, impervious cover, and vegetated areas. In addition, multiple regression models can then infer relationships between urban land use and land cover types with stormwater quality data, initially sampled at discrete monitoring sites, and then extrapolated annually across an arid city; in our case, the city of Phoenix in Arizona, USA. Results reveal that from 30 storm event samples, solids and heavy metal pollutants were found to be highly related with general impervious surfaces; in particular, with industrial and commercial land use types. Repercussions stemming from this work include support for public policies that advocate environmental sustainability and the more recent focus on urban livability. Also, advocacy for new urban construction and re-development that both steer away from vast unbroken impervious surfaces, in place of more fragmented landscapes that harmonize built and green spaces.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.508-510
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• 2003

Land cover change has been recognized as one of the most important factors influencing the occurrence of rainfall-triggered landslides. Satellite remote sensing provides detailed information regarding the spatial distribution and extent of land cover/use changes. This study describes the land cover changes in Nagasaki City, Japan and Kangnung City, South Korea. The former has been suffered from rainfall-triggered disasters for long term and latter was damaged by Typhoon Rusa in 2002. The results obtained from both study areas clearly show that land cover changes have occurred in the last decade as a result of both natural forces and human activities.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.426-428
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• 2003

Optical and microwave remote sensing data have been widely used in land cover and land use classification. Thanks to the spectral absorption characteristics of ground object in visible and near infrared region, optical data enables to extract different land cover types according to their material composition like water body, vegetation cover or bare land. On the other hand, microwave sensor receives backscatter radiance which contains information on surface roughness, object density and their 3-D structure that are very important complementary information to interpret land use and land cover. Separate use of these data have brought many successful results in practice. However, the accuracy of the land use / land cover established by this methodology still has some problems. One of the way to improve accuracy of the land use / land cover classification is just combination of both optical and microwave data in analysis. In this paper for the research, the author used LANDSAT TM scene 127/45 acquired on October 21, 1992, JERS-1 SAR scene 119/265 acquired on October 27, 1992 and aerial photographs taken on October 21, 1992. The study area has been selected in Hanoi City and surrounding area, Vietnam. This is a flat agricultural area with various land use types as water rice, secondary crops like maize, cassava, vegetables cultivation as cucumber, tomato etc. mixed with human settlement and some manufacture facilities as brick and ceramic factories. The use of only optical or microwave data could result in misclassification among some land use features as settlement and vegetables cultivation using frame stages. By combination of multitemporal JERS-1 SAR and TM data these errors have been eliminated so that accuracy of the final land use / land cover map has been improved. The paper describes a methodology for data combination and presents results achieved by the proposed approach.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.445-449
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• 2006

Diffuse pollution has been considering as a major source of the quality deterioration of water resources. The establishment of riparian vegetation strips or buffers along those areas of water bodies is used to reduce the threat of diffuse pollution. Remote sensing offers a means by which critical areas could be identified, so that subsequent action toward the establishment of riparian zones can be taken. On the behalf of KOMPSAT-2 satellite imagery as a high resolution spatial data, Landsat TM satellite data are used to aquire the land cover for the riparian buffers studied. This investigation aims to assess the riparian buffers established on the upper Geum river as a pollution mitigation. Through comparing the delineation of riparian buffer zones developed with the existing zones established by the government, we can find the critical distortion points of the existing riparian buffer zone.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.702-707
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• 2002

Three periods of land-use maps of the Suomo Basin were drawn from topographic maps (1970a) and Landsat TM/ETM images (1986a and 1999a). The area of each kind of land use was calculated from the three maps. From 1970 to 1999, the area of forestland decreased 17%, the area of sparse forestland increased 8%, and the area of grassland increased 10%. The transferring trend of the land-use is that forestland turned into sparse forestland and brush land, and the brush land degenerated into grassland based on the transferring matrixes from 1970 to 1986, and from 1986 to 1999. According to the local government record and statistical data, forest cover rate had been increasing from 1970 to 1998, but the amount of growing stock had been declining. From 1957 to 1998, the amount of growing stock declined from 423m$^3$/ha to 177m$^3$/ha.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.310-313
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• 2007

In this study, a new technique for atmospheric transmittance estimated from ALOS PRISM data is developed. It is based on satellite's observing radiances of different view angles and assumes that the cause of difference in radiances is the different view angles. The ALOS PRISM has three independent optical systems for viewing forward and backward and producing a stereoscopic image along the satellite's track. This stereo pair data can be used to estimate the transmittance according to the radiative transfer theory. This derived transmittance will be validated by the AERONET data and compared with the MODTRAN4 simulation results. Results show that the higher the land cover albedo, the better the derived transmittance compared to the AERONET data. Besides, this technique also shows the transmittance retrieval will be underestimated for the low land cover albedo.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.233-242
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• 2009

This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1386-1388
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• 2003

This paper analyzes the advantage of the XML, and studies the simple feature object model and Geography Markup Language that proposed by the Open GIS Consortium (OGC). We discussed the means of encoding the geographical data based on XML.