• Title/Summary/Keyword: Forestland Classification Map

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A Study on the Improvement of Evaluation Indicators for Adjusting Forestland Classification (산지구분 조정을 위한 산지특성평가 지표 개선에 관한 연구)

  • KWAK, Doo-Ahn;RYU, Keun-Won;KWON, Soon-Duk;KIM, Won-Kyung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.1
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    • pp.12-29
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    • 2016
  • The purpose of this study was to improve forestland characteristic evaluation system's indicators for rational development and ecosystem conservation. There has been no consideration for statistical duplication between variables, and it caused inefficient data collection. Furthermore, the same evaluation criteria were applied for all forestlands without considering regionally different characteristics, and it made variation for designation cancel rates of preservation semi-preservation forestlands between cities. To solve these problems, we first removed 'DBH' variable which has a multicollinearity. Second, we applied standard normal distribution for each forest watershed type. As a result of eliminating 'DBH', the numbers of parcels for all grades except A were changed but their numbers and areas were not large enough to consider the change of total score. For the output of analyses with the existing same regional criteria, the total scores of urban type and urban-fringe type forestlands were higher than those of other types. The numbers of parcels for A and B were increased and those for C and E were decreased by applying standard normal distribution. This caused the increase of preservation-oriented parcels. Finally, we suggested a new evaluation method based on standard normal distribution to consider regional forest characteristics and to solve regional imbalance.

Type Classification of Forestland Value by Using GIS Analysis (GIS를 이용한 산지가치 구분)

  • Ha, Do;Kim, Young-Seup
    • Korean Journal of Remote Sensing
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    • v.26 no.4
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    • pp.411-419
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    • 2010
  • The type of forestland value was evaluated using various thematic maps, satellite images, and aerial photograph of Namyangju, Based on GIS analysis, forestland value was classified into 4 kind types; conservation, production, recreation, and development values. Finally, the comprehensive analysis map of forestland value was made according to the priority order of value assessment. Among the whole forestland of Namyangju, conservation value area is $195km^2$, high production value area $96km^2$ except the conservation value area, high recreation value area $59km^2$, and the high development value area is $11km^2$. Henceforward, The value evaluation system of forestland by using GIS is to be very applicable for the scientific management of forestland, according to the periodic data update.

A Study on the Development of Topographical Variables and Algorithm for Mountain Classification (산지 경계 추출을 위한 지형학적 변수 선정과 알고리즘 개발)

  • Choi, Jungsun;Jang, Hyo Jin;Shim, Woo Jin;An, Yoosoon;Shin, Hyeshop;Lee, Seung-Jin;Park, Soo Jin
    • Journal of The Geomorphological Association of Korea
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    • v.25 no.3
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    • pp.1-18
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    • 2018
  • In Korea, 64% of the land is known as mountain area, but the definition and classification standard of mountain are not clear. Demand for utilization and development of mountain area is increasing. In this situation, the unclear definition and scope of the mountain area can lead to the destruction of the mountain and the increase of disasters due to indiscreet permission of forestland use conversion. Therefore, this study analyzed the variables and criteria that can extract the mountain boundaries through the questionnaire survey and the terrain analysis. We developed a mountain boundary extraction algorithm that can classify topographic mountain by using selected variables. As a result, 72.1% of the total land was analyzed as mountain area. For the three catchment areas with different mountain area ratio, we compared the results with the existing data such as forestland map and cadastral map. We confirmed the differences in boundary and distribution of mountain. In a catchment area with predominantly mountainous area, the algorithmbased mountain classification results were judged to be wider than the mountain or forest of the two maps. On the other hand, in the basin where the non-mountainous region predominated, algorithm-based results yielded a lower mountain area ratio than the other two maps. In the two maps, we was able to confirm the distribution of fragmented mountains. However, these areas were classified as non-mountain areas in algorithm-based results. We concluded that this result occurred because of the algorithm, so it is necessary to refine and elaborate the algorithm afterward. Nevertheless, this algorithm can analyze the topographic variables and the optimal value by watershed that can distinguish the mountain area. The results of this study are significant in that the mountain boundaries were extracted considering the characteristics of different mountain topography by region. This study will help establish policies for stable mountain management.

Analysis of land use change for advancing national greenhouse gas inventory using land cover map: focus on Sejong City

  • Park, Seong-Jin;Lee, Chul-Woo;Kim, Seong-Heon;Oh, Taek-Keun
    • Korean Journal of Agricultural Science
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    • v.47 no.4
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    • pp.933-940
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    • 2020
  • Land-use change matrix data is important for calculating the LULUCF (land use, land use change and forestry) sector of the national greenhouse gas inventory. In this study, land cover changes in 2004 and 2019 were compared using the Wall-to-Wall technique with a land cover map of Sejong City from the Ministry of Environment. Sejong City was classified into six land use classes according to the Intergovernmental Panel on Climate Change (IPCC) guidelines: Forest land, crop land, grassland, wetland, settlement and other land. The coordinate system of the land cover maps of 2004 and 2019 were harmonized and the land use was reclassified. The results indicate that during the 15 years from 2004 to 2019 forestlands and croplands decreased from 50.4% (234.2 ㎢) and 34.6% (161.0 ㎢) to 43.4% (201.7 ㎢) and 20.7% (96.2 ㎢), respectively, while Settlement and Other land area increased significantly from 8.9% (41.1 ㎢) and 1.4% (6.9 ㎢) to 35.6% (119.0 ㎢) and 6.5% (30.3 ㎢). 79.㎢ of cropland area (96.2 ㎢) in 2019 was maintained as cropland, and 8.8 ㎢, 1.7 ㎢, 0.5 ㎢, 5.4 ㎢, and 0.4 ㎢ were converted from forestland, grassland, wetland, and settlement, respectively. This research, however, is subject to several limitations. The uncertainty of the land use change matrix when using the wall-to-wall technique depends on the accuracy of the utilized land cover map. Also, the land cover maps have different resolutions and different classification criteria for each production period. Despite these limitations, creating a land use change matrix using the Wall-to-Wall technique with a Land cover map has great advantages of saving time and money.