• 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.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.386-389
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• 1999

In this study, visible and near infrared channels of NOAA/AVHRR data were used to classify land use and vegetation types over Korean peninsula. Analyzing forest stand structures and prediction of forest productivity using satellite data were also reviewed. Land use and land cover classification was made by unsupervised clustering methods. After monthly Normalized Difference Vegetation Index (NDVI) composite images were derived from April to November 1998, the derived composite images were used as temporal feature vector's in this clustering analysis. Visually interpreted, the classification result was satisfactory in overall for it matched well with the general land cover patterns. But subclassification of forests into coniferous, deciduous, and mixed forests were much confused due to the effects of low ground resolution of AVHRR data and without defined classification scheme. To investigate into the forest stand structures, digital forest type maps were used as an ancillary data. Forest type maps, which were compiled and digitalized by Forestry Research Institute, were registered to AVHRR image coordinates. Two data sets were compared and percent forest cover over whole region was estimated by multiple regression analysis. Using this method, other forest stand structure characteristics within the primary data pixels are expected to be extracted and estimated.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.131-139
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• 1994

Geo-spatial information system technology and cartographic modeling techniques were used as a way to Improve the land use planning process. Off-road vehicle(ORV) trails, timber harvest sites, timber haul mads and wildlife ruffed grouse habitats areas should be allocated together in the Wayne National Forest in the United States. Automated spatial cartographic models were developed to resolve the conflicts of the multiple land use allocation. The techniques of descriptive and prescriptive modeling made the multiple land use allocation efficient and effective.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.176-184
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• 2020

Due to constant development and decline on Seoul areas the Seoul government is pushing various policies to regenerate declined Seoul areas. Theses various policies lead to land-use changes around numerous Seoul districts. This study aims to create prediction model which can foresee future land-use changes and while doing so, tried to derive various influential factors which leads to land-use changes. To do so, various open-data from national departments and Seoul government have been collected and implemented into random forest algorithm. The results showed promising accuracy and derived multiple influential factors which causes land-use changes around Seoul districts. The result of this study could further be implemented in policy makings for the public sectors, or could also be used as basis for studying gentrification problems happening in Seoul Area.

• Journal of Environmental Science International
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• v.18 no.2
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• pp.169-176
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• 2009

The present study observed temperature in order to identify factors affecting temperature by zoning and to measure the intensity of their impact on temperature. The empirical results of analyzing observed data are as follows. In order to make up for multicollinearity, a problem in multiple regression analysis, and to give more specific explanations, this study conducted factor analysis and obtained desirable data with adequacy and statistical significance. In the correlation matrix, factors decreasing temperature were planted areas, water surfaces and grasslands, and those increasing temperature were bare grounds, paved areas, and building area. According to land cover patterns, commercial areas had the highest temperature lowering effect. Through the rotated component matrix, we found that factors are grouped into those decreasing temperature, those increasing temperature, and those with low significance in increasing or decreasing temperature. In order to solve the problem of multicollinearity in multiple regression analysis, we performed factor analysis between the land use patterns and temperature and confirmed the usability of factor analysis as a new analysis method in urban heat island.

• Journal of Korean Society of Forest Science
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• v.76 no.3
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• pp.275-294
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• 1987

In the United States, forest administration is a constantly changing complex of policies, programs, and management regulations. Forest administration is the product of a brief but tumultuous history during which much of the forests which once covered half the land were coutover for farms, industry, and cities. In the last 15 years, forest administration has been increasingly dominated by concerns for maintaining an ecological balance. Current forest administration is deeply rooted in the American traditions of decentralized federalism and free enterprise, yet combines state socialism and private capitalism. The major elements of U.S. forest administration consist of : 1) programs and policies on taxation, professional education and research, and "cooperative forestry", 2) state controls on forest practices for privately owned lands, and of federal policies and regulations for the management of federal lands. The federal Forest Service has played a lead role in developing and implementing national forest policies and programs. Since the end of World War II, the national forests managed by the Forest Service for multiple use have provided and ever growing fraction of domestic timber needs. In the coming decades, cultural and social trends may force a change in management policy on federal land, reducing the importance of timber harvesting in relation to amenity values.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.33-49
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• 2015

The objective of this study was to predict land use change based on the land use change scenarios for the Hwangguji river watershed, South Korea. The land use change scenario was derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The CLUE (conversion of land use and its effects) model was used to simulate the land use change. The CLUE is the modeling framework to simulate land use change considering empirically quantified relations between land use types and socioeconomic and biophysical driving factors through dynamical modeling. The Hwangguji river watershed, South Korea was selected as study area. Future land use changes in 2040, 2070, and 2100 were analyzed relative to baseline (2010) under the RCP4.5 and 8.5 scenarios. Binary logistic regressions were carried out to identify the relation between land uses and its driving factors. CN (Curve number) and impervious area based on the RCP4.5 and 8.5 scenarios were calculated and analyzed using the results of future land use changes. The land use change simulation of the RCP4.5 scenario resulted that the area of urban was forecast to increase by 12% and the area of forest was estimated to decrease by 16% between 2010 and 2100. The land use change simulation of the RCP8.5 scenario resulted that the area of urban was forecast to increase by 16% and the area of forest was estimated to decrease by 18% between 2010 and 2100. The values of Kappa and multiple resolution procedure were calculated as 0.61 and 74.03%. CN (III) and impervious area were increased by 0-1 and 0-8% from 2010 to 2100, respectively. The study findings may provide a useful tool for estimating the future land use change, which is an important factor for the future extreme flood.

• KIEAE Journal
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• v.14 no.5
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• pp.123-130
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• 2014

In order for effective heat island reduction policies to be proposed, this research made use of the land usage and land coverage and Temperature of cities, Coordinate axis data within 500 meters of nationwide automatic weather stations (478 points) in order to analyze the correlation of summertime temperatures through multiple regression analysis. This research also developed a model and empirically analyzed the urban heat island reduction effect of factors that affect regional temperatures. Heat islands cause environment deterioration and therefore can harm citizens' health, and also affects the city's metabolism process. Thus in order to restrain regional temperature rises the conclusion was drawn that consideration to increase forest areas on part of land usage planning is needed. Appropriate policy measures to regulate traffic related factors are also needed to restrain regional temperature rises. In order for future heat island reduction this research proposes a way to set up more effective policies and urban sustainability improvement strategies, and is significant in that it makes use of detailed data such as land usage and land coverage, Temperature of cities, Coordinate axis in analyses.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.19-37
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• 2023

This study empirically analyzed the determinants of the assessment ratio (hereinafter 'AR') based on a total of 2,129 sales cases of forests in Gwangju, Gyeonggi-do. The main findings of this study through multiple regression analysis are summarized as follows. First, this study shows that regional characteristics have significantly different effects on the AR of forest land prices. Specifically, there was a significant difference in the AR depending on the location of the parcel by sub-region and the ratio of residential area, and the higher the number of development plans in progress, the more likely the officially assessed land price will be formed close to the sale price. Second, this study analyzed that location characteristics such as the proximity of the inner and outer center of the jurisdiction and traffic accessibility had a significant influence on the determination of the AR. Third, this study identified significant differences in AR depending on detailed factors such as planning management areas, production management areas, conservation areas for mountain, conservation areas for nature, and restricted development areas as land use and regulatory characteristics of forest lands. Fourth, this study found that land characteristics are a significant factor influencing the AR as an individual factor in forest land.