• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.433-438
• /
• 1999

The land use type of Korea is high-density. So, the image classification using coarse resolution satellite image may not provide land cover classification results as good as expected. The purpose of this paper is to compare the result of visual interpretation with that of digital image classification of 20 m resolution SPOT satellite image at Kwangju-eup, Kyunggi-do, Korea. Classes are forest, cultivated field, pasture, water and residential area, which are clearly discriminated in visual interpretation. Maximum likelihood classifier was used for digital image classification. Accuracy assessment was done by comparing each classification result with ground truth data obtained from field checking. The classification result from the visual interpretation presented an total accuracy 9.23 percent higher than that of the digital image classification. This proves the importance of visual interpretation for the area with high density land use like the study site in Korea.

• Journal of Korean Society of Forest Science
• /
• v.107 no.2
• /
• pp.113-125
• /
• 2018

Subalpine zone is geographically vulnerable to climate change. Forest vegetation in this zone is one of the important basic indicator to observe the influence of climate change. This study was conducting phytosociological community classification and endemic-rare plants investigation based on vulnerable species to climate change at the subalpine zone, Mt. Jiri. Vegetation data were collected by 37 quadrate plots from March to October, 2015. In order to understand the species composition of plant sociological vegetation types and the ecological impacts of species, we analyzed the layer structure of vegetation type using important values. Vegetation type was classified into eight species groups and five vegetation units. The vegetation types can be suggested as an indicator on the change of species composition according to the future climate change. There were 9 taxa endemic plants and 17 taxa rare plants designated by KFS(Korea Forest Service) where 41.2% of them were the northern plant. Endemic-rare plants increased as the altitude of vegetation unit increase. Importance value analysis showed that the mean importance value of Abies koreana was highest of all vegetation units. Based on analysis of each layer, all units except vegetation unit 1 were considered to be in competition with the species such as Quercus mongolica and Acer pseudosieboldianum. The results of this study can be a basic data to understand the new patterns caused by climate change. In addition, it can be a basic indicator of long-term monitoring through vegetation science approach.

• Journal of Korean Society of Forest Science
• /
• v.78 no.3
• /
• pp.263-273
• /
• 1989

Accurate and cost-effective classification of forest vegetation is the primary goal for forest management and utilization of forest resources. Aerial photograph and remote sensing are the most frequent and effective method in forest resources inventories. TM and MSS are the principal observing instruments on the Landsat-4 and -5 earth observing satellite. Especially TM has considerably greater spatial, spectral, and radiometric resolution power than MSS, that is, the IFOV of TM at a nadir is 30m compared to 80m for MSS. In this study, we used TM data to classify forest types and compared the result with forest type map manufactured by interpretation of B/W infrared photographs. As a result, land use types were well defined with TM data. But classifying forest types was a little difficult and indistinct. However, the spectral signatures of forest in every season and growing stages remained as problems to be solved, and also the most effective selection and combination method of bands for differentiating the spectral plots among classes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.9
• /
• pp.2904-2926
• /
• 2022

Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_2
• /
• pp.1037-1052
• /
• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• Journal of Environmental Science International
• /
• v.21 no.2
• /
• pp.135-144
• /
• 2012

This study aims at classifying and analyzing the vegetation structure of Castanopsis sieboldii forest, one of the evergreen broad-leaved forests found under the warm-temperate climate of Korea. It is also compared with the ones of the Castanopsis sieboldii forest in Japan where most similar such forest of Korea, to find unique vegetation structures of the only Korean forest. Vegetation structure of Korean Castanopsis sieboldii forest was divided into two units at the level of community units both of Ardisia japonica-Castanopsis sieboldii community and Ardisio-Castanopsietum sieboldii association. The association carries similar type with the vegetation system of Japan, but any subunits differentiated with the Japan were found vary much. Hierarchical cluster analysis brings in similar result with the analysis on the vegetation structure as well.

• Korean Journal of Agricultural Science
• /
• v.49 no.2
• /
• pp.317-330
• /
• 2022

Recently, the policy regarding climate change in Korea and overseas has been to promote the utilization of forest biomass to achieve net zero emissions. In addition, with the implementation of the unused forest biomass system in 2018, the size of the Korean market for manufacturing wood pellets and wood chips using unused forest biomass is rapidly expanding. Therefore, it is necessary to estimate the total amount of unused forest biomass that can be used as an energy source and to identify the capacity that can be continuously produced annually. In this study, we estimated the actual forest area that can be produced of logging residue and the potential amount of unused forest biomass resources based on GT (green ton). Using a forest functions classification map (1 : 25,000), 5th digital forest type map (1 : 25,000), and digital elevation model (DEM), the forest area with a slope of 30° or less and mountain ridges of 70% or less was estimated based on production forest and IV age class or more. The total forest area where unused forest biomass can be produced was estimated to be 1,453,047 ha. Based on GT, the total amount of unused forest biomass potential resources in Korea was estimated to be 117,741,436 tons. By forest type, coniferous forests were estimated to be 48,513,580 tons (41.2%), broad-leaved forests 27,419,391 tons (23.3%), and mixed forests 41,808,465 tons (35.5%). Data from this research analysis can be used as basic data to estimate commercial use of unused forest biomass.

• Ecology and Resilient Infrastructure
• /
• v.8 no.2
• /
• pp.97-111
• /
• 2021

This study was conducted to develop a habitat type classification system and its map based on the ecological characteristics of species, spatial type, vegetation, topography, and geological conditions preferred by species. To evaluate the relationships between species and their habitats in Korean national parks, we prepared a classification standard table for systematic classification of habitat types. This classification system divides habitats into 6 low-level and 59 mid-level ecological classes based on habitat structure. The mid-level system divided forest ecosystems into 20 subtypes, stream and wetland ecosystems into 8 types, coastal ecosystems into 7 types, arable land into 6 types, development land into 9 types, and 1 type of marine ecosystem. A habitat classification map was drawn utilizing square images, detailed vegetation maps, and forest stand maps, based on the above habitat classification system, and it covered 1,461 plots spanning 21 national parks. The habitat classification system and survey protocol, which consider domestic habitat conditions, should be further developed and applied to habitat assessment, to enhance the utility of this study.

• Journal of Korean Society of Forest Science
• /
• v.47 no.1
• /
• pp.27-36
• /
• 1980

To establish an easy classification method of bamboos observation of the shapes of vascular bundle sheath of Sasa, one of the important natural resources available in Korea, was made on the basis of vascular bundle sheath of bamboo culms because Sasa has a unique vascular bundle sheath as discussed by Grosser and Liese et al. Morphological characteristics of Saw observed are summarized as follows: 1. The thickness of culm wall showed no distinctive difference between upper and low parts of culms of Sasa grown at the ground level. 2. In relation to the taxonomical classification of bamboo, Sasa showed a and a' type but did not e.f.h. and e' type was not identified. 3. Two typical types of bamboo vascular bundle sheath, i.e. b.c.d.e. and g type and d and e type, were found in Sasa but sometimes b.c.g. type was not observed. 4. The results mentioned above seem to be an important key for classification of Sasa.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.23 no.5
• /
• pp.99-112
• /
• 2020

This study aims to propose biotope field datasheet and biotope type classification based on habitat-based by analyzing the German biotope system. The German system began in 1976 and has established a habitat-based national biotope classification system. On the other hand, Korea institutionalized in 2018 to build a classification system based on land use and land cover, which is a classification system that does not fully reflect ecosystem in Korea. Germany operates 44 biotope classification systems and 40 biotope field datasheet. Korea uses a single biotope field datasheet regardless of the biotope type. This classification system may not reflect the characteristics of Korea's biotope ecological habitat. The biotope classification system of Korea was proposed by dividing it into five categories: mountain ecology, freshwater ecology, land ecology, coastal ecology, and development area to reflect ecosystem habitat. The biotope type was designed as a system of large-classification-middle-small classification and subdivided into medium-classification and subdivided in each biotope system. The major classifications were classified into 44 categories according to the mountainous biotope(11), freshwater biotope(8), terrestrial biotope (12), coastal biotope(6), and development biotope(7). Unlike Germany, Korea's biotope field datasheet was proposed in five ways according to the classification of major ecosystem types. The results of this study are expected to contribute to the policy suggestion and the utilization of ecosystem conservation because the biotope classification system is classified to reflect the characteristics of ecosystem habitats.