• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.168-182
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• 2019

The objectives of this study were to examine the production processes and methods of "Forest Type Map Actualization Production (Database (DB) Construction Work Manual)" (Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The "Forest Classification" defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of "Areas Changed Artificially and Areas Changed Naturally", and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, "Species Change" item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the "Forest Classification" item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

• Journal of the Korean association of regional geographers
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• v.20 no.2
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• pp.206-216
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• 2014

In this study, forest types in Chungheongnam-do were analyzed using Landsat satellite images and digital forest type map as a means to estimate forest carbon stocks. NDVI and Tasseled Cap, ISODATA, and supervised classification among others were used to analyze the forest types. The forest carbon stocks of Chungcheongnam-do were estimated utilizing forest statistical data derived from the classified results. The results indicate that the analysis of forest types through supervised classification yielded the highest overall accuracy in analyzing forest types using satellite images. Coniferous forests(49.3%) accounted for the highest proportion in all the forest types of Chungcheongnam-do, followed by deciduous forests(28.0%) and mixed forests(22.7%). The results of a comparative analysis between forest carbon stocks estimates made using the modified digital forest type map and other estimation methods showed that the method using Tasseled Cap and unsupervised classification yielded the most similar forest carbon stock estimates. The most significant difference, though, was made when only the digital forest type map was used. It is expected that if carbon stocks are estimated by integrating satellite images and digital forest type maps in the future, more accurate results can be derived in estimating forest carbon stocks at a national level.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.24-34
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• 2024

Fire, being primarily a natural phenomenon, is impossible to control, although it is feasible to map the forest fire risk zone, minimizing the frequency of fires. The spread of a fire starting in any stand in a forest can be predicted, given the burning conditions. The natural cover of the land and the safety of the population may be threatened by the spread of forest fires; thus, the prevention of fire damage requires early discovery. Satellite data and geographic information system (GIS) can be used effectively to combine different forest-fire-causing factors for mapping the forest fire risk zone. This study mainly focuses on mapping forest fire risk in the Madikhola watershed. The primary causes of forest fires appear to be human negligence, uncontrolled fire in nearby forests and agricultural regions, and fire for pastoral purposes which were used to evaluate and assign risk values to the mapping process. The majority of fires, according to MODIS events, occurred from December to April, with March recording the highest occurrences. The Risk Zonation Map, which was prepared using LULC, Forest Type, Slope, Aspect, Elevation, Road Proximity, and Proximity to Water Bodies, showed that a High Fire Risk Zone comprised 29% of the Total Watershed Area, followed by a Moderate Risk Zone, covering 37% of the total area. The derived map products are helpful to local forest managers to minimize fire risks within the forests and take proper responses when fires break out. This study further recommends including the fuel factor and other fire-contributing factors to derive a higher resolution of the fire risk map.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.446-452
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• 2014

This research aimed to provide a method to estimate growing stock and carbon stock using the characteristics of forest type map such as the age-class, DBH class and crown density class. We transformed the growing stock data of national forest inventory (mainly Kangwon-do province) onto those of time when the forest type map was established. We developed a simulation model for the growing stock using the transformed data and the characteristics of forest type map by the quantification method I. By comparing partial correlation coefficient, we found that quantification of growing stock was largely affected by age-class followed by crown density class, forest type and DBH class. The growing stock, was estimated as minimum in the broadleaved forest with age-class II, DBH class 'Small', and crown density class 'Low' as $20.0m^3/ha$, whereas showed maximum value in the coniferous forest with age-class VI, DBH class 'Large', and crown density class 'High' as $305.0m^3/ha$. The growing stock for coniferous, broadleaved, and mixed forest were estimated as $30.5{\sim}305.0m^3/ha$, $20.0{\sim}200.4m^3/ha$, and $23.8{\sim}238.1m^3/ha$, respectively. When we compared the carbon stock by forest type, the carbon stock by age class based on growing stock was maximum when DBH class was 'Large' and crown density class was 'High' regardless of forest type. This estimation of growing stock by using characteristic of forest type can be used to estimate the changes in growing stock and carbon stock resulting from deforestation or natural disaster. In addition, we hope it provide a useful advice when forest officials and policy makers have to make decisions in regard to forest management.

• Spatial Information Research
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• v.22 no.5
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• pp.53-63
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• 2014

As recent interest in ecological resources increases, an effort in three-dimensional visualization of the ecological resources has increased for the restoration and preservation of the natural environment as well as the evaluation of the landscape. However, in the case of forest resources, information extraction has been active, but the effort in trying to apply that information into an effective visualization has not happened. In other words, the effort for effective visualization is lacking when it comes to the visualization of forest resources, and numerous cases are ether non-realistic or the simulation required for analysis is inappropriate. Therefore, this paper extracts information through the use of airborne LiDAR data, aerial photograph, and forest type maps to create a vegetation layer, and then uses Flora3D forest modeling tools and ArcGlobe to accurately visualize the vegetation layer into the three dimension. An effective application for restoration and preservation of ecological resources as well as analysis on the urban landscape can be considered as a result of intuitively and realistically enabling the user's awareness of forest information within the Geographic Information System.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.1-10
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• 2011

This program was developed to operate and manage the massive digital forest cover type map using SDE(spatial database engine) in order to solve the problems of the analogue mapping system, mapping process and managing vast amounts of data. It was established the standardization process by performing the several functions of application related to the spatial DB search, mapping history and progress control, modification and inspection of the topology error, approval and reject of those maps. It can be possible to generate the effective mapping and distribute maps to the public service. It is expected that the results will be able to reduce time-cost.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.479-495
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• 2021

To improve on the efficient management of forest resources, it is necessary to create a forest soil map, which represents a comprehensive database of forest lands. Although a 1:25,000 scale forest site map has been used in Korea, the need for a large-scale forest soil map with high precision and information on forest lands that is specialized for individual purposes has been identified. Moreover, to keep pace with the advancement in forest management and transition to a digital society, it is essential to develop a method for constructing new forest soil maps that can diversify its use. Therefore, this paper presented a developmental process and used a 1:5,000 scale forest soil map to propose future directions. National maps showing the soil type, depth, and texture were produced based on the survey and analysis of forest soils, followed by the Forest Land Soil Map (1:5,000) Production Standard Manual. Alternatively, forest soil map data were the basis on which various other maps that can be used to prevent and predict forest disasters and evaluate environmental capacities were developed. Accordingly, ways to provide appropriate information to achieve the national forest plan, secure forestry big data, and accomplish sustainable forest management that corresponds to the national development plan are proposed based on results from the current study.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.2
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• pp.55-60
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• 2009

By applying NDVI(Normalized Difference Vegetation Index) and TCT(Tasseled-Cap Transformation) image algorithm on the basis of KOMSAP-2 MSC(Multi Spectral Camera) image(Jun. 12, 2007) for Naenam-myeon, Gyeongju city in this study, DN distribution map was drawn up. Discrimination analysis of image algorithm for the accuracy improvement of forest type classification was conducted through the comparative analysis between the distribution maps of NDVI and TCT DN, and forest field surveying data, and finally, the accuracy of the forest type classification was verified through the overlay analysis with the forest field surveying data. Through this study, it is thought that low cost and high efficiency will be able to be expected in the process of the examination for the automation practicality of the forest type classification and of the production of the accurate forest type classification map by using KOMPSAT-2 MSC image.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.2
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• pp.114-123
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• 2010

The Environmental Conservation Value Assessment Map (ECVAM) is a five grade assessment map created with nationally integrated environmental information and environmental values. The map is made through the evaluation of 67 items, including greenbelt area and bio-diversity. The ECVAM assesses the stability of the community using forest maps. However, the existing assessment method is problematic because the assessment grades are evaluated using higher than practical values; in part because it uses even-valued overlay and minimal indicator methods. This study was performed in order to suggest an integrated assessment method that could complement the stability evaluation based on existing methods. Accordingly, this study added forest type information, including whether the forest was natural or artificial, to the overlay method using forest diameter maps and forest density maps. As a result, the proposed ECVAM indicated a drastic grade change. After applying the method in South Korea, Grade I areas decreased 12.1%, from 52.6% to 40.6%, Grade II areas increased 11.9%, from 17.4% to 29.2%, and Grade III areas increased 0.2%, from 17.1% to 17.4%, respectively. From the results of the field survey, we found differences between natural forest and planted forest with regard to the number of mortality, species of shrubs, and vine cover. This means that natural forests are more stable than planted forests. This study suggests an improved assessment methodology to complement the existing EVCAM method. The results are expected to be used in environmental evaluations and forest conservation value assessments in ecology and environmental fields.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.328-330
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• 2003

The land cover of burned area has changed dramatically since Daxinganling forest fire in Northeastern China during May 6 ? June 4, 1987. This research focused on determining the burn severity and assessment of forest recovery. Burned severity was classified into three levels from June 1987 Landsat TM data acquired just after the fire. A regression model was established between the forest canopy closure from 1999 forest stand map and the NDVI values from June 2000 Landsat ETM+ data. The map of canopy closure was got according to the regression model. And vegetation cover was classified into four types according to forest closure density. The change matrix was built using the classified map of burn severity and vegetation recovery. Then the change conversions of every forest type were analyzed. Results from this research indicate: forest recovery status is well in most of burned scars; and vegetation change detection can be accomplished using postclassification comparison method.