• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.548-553
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• 2017

The aim of this study was to develop a low impact development design technique that can be applied in the land use planning stage and verify quantitatively the effects of non-point pollution reduction. For this purpose, the low impact development design elements that can be applied in the land use planning stage were derived and applied to an actual site, and the non-point pollution reduction effect was analyzed using the LIDMOD2 program. The analysis showed that the permeability rate of the land use plan using low impact development decreased by 19.8% compared to the existing land use plan. In addition, annual surface runoff decreased by 19.0% and annual infiltration increased by 164.1%. In the case of non-point pollution, the annual loading, T-N, T-P, and BOD decreased by 18.7 ~ 22.8%. Therefore, compared to the existing land use plan, the land use plan using low impact development has a considerably large effect of reducing the non-point pollution without changing the floor area according to each application. Therefore, to maximize the reduction effect of non-point pollution, it will be necessary to establish a related plan by applying the low impact development technique from the land use planning stage to the existing LID facility-oriented plan.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.3
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• pp.63-73
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• 1993

For a systematic approach to rural settlement planning, socio-economic and land use potentialities were analysed in 10 villages("Ri", the lowest-order administrative unit in Korea)of Izuk-myun, Anseong-gun, Kyeonggi province, the model area in this study. Socio-economic potentialities, sub-grouped into rural and urban related ones, were analysed by the principal component analysis technique, while land use potentialities by the land suitability system of which the physical analysis is based on geographical information system. The principal component of rurality is strongly related with 5 key variables such as annual increasing rate of farm households, ratio of over 1ha-households, ratio of full-time farmers, ratio of animal rearing households and the principal component of urbanity with 6 key ones such as population density, number of schools, number of shops and servicing facilities, number of daily bus routes, number of non-farm households, percentage of area of housing sites. The analysis procedure of land suitability using the geographical information system were generalized and the results of analysis on village sites and paddy and upland fields were presented. The whole land use planning was presented by the criteria of the land suitability rank and the priority order of land use. land use.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.33-40
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• 2015

Forests are to be recognized as an important carbon sink under the UNFCCC that consist of above- and below-biomass, dead organic matter (DOM) such as dead wood and litter, and soil organic matter (SOM). In order to asses for DOM and SOM, however, it is relevant to land-use change matrices over last 20 years for each land-use category. In this study, a land-use change matrix was produced and its uncertainty was assessed using a point sampling technique with permanent sample plots in national forest inventory at Chungbuk province. With point sampling estimated areas at 2012 year for each land-use category were significantly similar to the true areas by given six land-use categories. Relative standard error in terms of uncertainty of land-use change among land-use categories ranged in 4.3~44.4%, excluding the other land. Forest and cropland covered relatively large areas showed lower uncertainty compared to the other land-use categories. This result showed that selected permanent samples in the NFI are able to support for producing land-use change matrix at a national or province level. If the $6^{th}$ NFI data are fully collected, the uncertainty of estimated area should be improved.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.58-70
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• 2007

The purpose of this study is to predict future land use using Landsat images through assessing the effect of spatial scale and resolution in applying CA (Cellular Automata)-Markov technique. The scale for areas ranging from $31.26km^2$ to $84.48km^2$ showed about 11% difference of overall accuracies. Among the five spatial resolutions (10m, 30m, 50m, 100m, 150m), 30m resolution showed the best result in the prediction of area and spatial distribution of urban areas. Based on the results, the 2004 land use by CA-Markov was predicted using 1996 and 2001 land use data and compared with the 2004 land use by maximum likelihood classification. After that, future land uses of 2030, 2060 and 2090 were predicted and the results showed a tendency of gradual increase in urban area and high decrease in forest area.

• Journal of Environmental Impact Assessment
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• v.4 no.2
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• pp.23-28
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• 1995

Remote sensing begins to be applied in Environmental Impact Assessment(EIA), and it can systematically assess land use which is an important factor in EIA. This study is to predict land use change of Ulsan region and to assess impact on land use using the past and the present data of remote sensing. Also we analyzed an impact area influenced by EIA projects through the integration of remote sensing and GIS. This technique will be applied to the screening stage in EIA.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.147-150
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• 2008

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.361-369
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• 1987

The idea of multiple-use of forest land is tile one field of economics to improve the efficiency of forest land, and is the famous management technique widely used in the developed forestry country. This paper introduces the STEM and the constraint method, which is one kind of mathematical programming techniques used for multiple forest Land use, and discusses the differences between these two methods by using the hypothetical data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.249-260
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• 2017

UHI (Urban Heat Island) is an important environmental issue occurring in highly developed (or urbanized) area such as Seoul Metropolitan City of Korea due to modification of the land surface by man-made structures. With the advance of the remote sensing technique, land cover types and LST (Land Surface Temperature) influencing UHI were frequently investigated describing that they have a positive relationship. However, the concept of land cover considers material characteristics of the urban cover in a comprehensive way and does not provide information on how human activities influence on LST in detail. Instead, land use reflects ways of land use management and human life patterns and behaviors, and explains the relationship with human activities in more details. Using this concept, LST was segmented according to land use types from the Landsat imagery to identify the human-induced heat from the surface and interannual and seasonal variation of LST with GIS. The result showed that the LST intensity of Seoul was greatest in the industrial area and followed by the commercial and residential areas. In terms of size, the residential area could be defined as the major contributor among six urban land use types (i.e., residential, industrial, commercial, transportation, etc.) affecting UHI during daytime in Seoul. For temperature, the industrial area was highest and could be defined as a major contributor. It was found that land use type was more appropriate to understand the human-induced effect on LST rather than land cover. Also, there was no significant change in the interannual pattern of LST in Seoul but the seasonal difference provided a trigger that the human life pattern could be identified from the satellite-derived LST.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.315-327
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• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.