• Journal of the Korean Association of Geographic Information Studies
• /
• v.7 no.4
• /
• pp.57-64
• /
• 2004

In order to decrease the area damaged by forest fires and to prevent the occurrence of forest fires, the forest fire danger rating system was developed to estimate forest fire risk by means of weather, topography, and forest type. Forest fires occurrence prediction needs to improve continually. Logistic regression and spatial analysis was used in developing the forest fire occurrence probability model. The forest fire danger index in accordance to the probability of forest fire occurrence was used in the classification of forest fire occurrence risk regions.

• Korean Journal of Environment and Ecology
• /
• v.28 no.2
• /
• pp.182-196
• /
• 2014

In this study, for the forest vegetation classification and the quantitative analysis of the Picea jezoensis and Abies hollophylla stand, the type classification of the vegetation structure was performed with Z-M phytosociological method, and as a result, it was classified into the Picea jenoensis community and the Abies holophylla community in the community unity. The Picea jezoensis community was subdivided into the Rosa koreana group and the Acer ukurunduense group in the group unity and the Abies holophylla community was subdivided into the Acer mandshuricum group and the Lindera obtusiloba group. In the results of estimating the importance value based on the classified vegetation unity, it was deemed that the dominance of the Picea jezoensis would be continued for a while as the importance value from the tree layers of vegetation unity 1 and 2 represented relatively high with 30.73% and 20.25%. In addition, in the results of analyzing the species diversity to estimate the maturity of the community, the species diversity index of the vegetation unity 4 was the lowest with 0.6976 and that of vegetation unity 2 was the highest with 1.1256. As in the similarity between the communities, the vegetation unit 1 and 4 and the vegetation unit 2 and 4 represented low with 0.2880 and 0.3626, respectively, and the similarity between the vegetation unit 1 and 2 and between 2 and 4 represented 0.5411 and 0.5041, respectively, it was deemed that they were the communities that the difference in the composition species between the communities was not big. In the results of analyzing the Chi-square matrix and the catalog of constellations for the interspecific, they were divided mainly into two types, and type 1 plant species were mostly differential species and the characteristic species, which appeared in the Picea jezoensis community classified phytosociologically, and type II plant species were mostly the species appearing in the Abies holophylla community growing in the relatively damp places. Such results is deemed that the positive (+) correlation is recognized among the species, of which growing environments are similar, and the negative (-) correlation .represents among the species, of which preferential environments are different.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.5 no.1
• /
• pp.35-50
• /
• 2002

This study aims to understand wetland distribution and type-specific classification features with a focus on Tumen River downstream in China by adjusting and improving the classification system used in Korea with a reference to international wetland classification systems and their criteria & methods. In this study, wetland types were determined based on hydrology, vegetation, and soil conditions, which are the most basic elements of wetlands. Also, topography analytical map, vegetation analytical map, and soil analytical map for wetland classification were developed and used based on currently available topography map, vegetation map, and soil map. In addition, codes were defined based on topography, location, hydrology, and vegetation. The result shows that, in the Tumen River downstream, wetlands are often found near natural revetment and terrace land & river-bed lakes. In the discovered wetlands, riverine, lacustrine, and inland wetlands were mostly found at system level. Riparian and human-made wetlands were also identified. At a sub-system level, perennial and seasonal wetlands were found to a similar degree. At a class level, perennial open water, herbal plants, and shrubs were mostly found and sandy plain, hydrophytes, and forest tree types were also observed. An overall detailed classification shows that a total of 17 wetland types were found and a large distribution of sand dunes and river-bed lakes, which are scarce in Northeast Asia, indicates that other rare wetland types such as palustrine seasonal sand plain wetland and lacustrine seasonal sand plain wetland may be discovered.

• Korean Journal of Remote Sensing
• /
• v.27 no.4
• /
• pp.457-466
• /
• 2011

The objectives of this study are to produce level 3 type LULC map and analysis of phenological features of North Korea, ISODATA clustering of the 88scenes of MVC of MODIS NDVI in 2008 and 8scenes in 2009 was carried out. Analysis of phenological phases based mapping method was conducted, In level 2 type map, the confusion matrix was summarized and Kappa coefficient was calculated. Total of 27 typical habitat types that represent the dominant species or vegetation density that cover land surface of North Korea in 2008 were made. The total of 27 classes includes the 17 forest biotopes, 7 different croplands, 2 built up types and one water body. Dormancy phase of winter (${\sigma}^2$ = 0.348) and green up phase in spring (${\sigma}^2$ = 0.347) displays phenological dynamics when much vegetation growth changes take place. Overall accuracy is (851/955) 85.85% and Kappa coefficient is 0.84. Phenological phase based mapping method was possible to minimize classification error when analyzing the inaccessible land of North Korea.

• Korean Journal of Environment and Ecology
• /
• v.12 no.2
• /
• pp.119-130
• /
• 1998

The purposes of this study were to investigate vegetation structure and to present management plan of mountain type green space in Kangwhado, Inchon. The actual vegetation in survey sites(11,331ha) was divided into 19 community types. It was consisted of secondary forest(92.32%) which was Quercus acutissima, Pinus densiflora-Q. acutissima, and Q. mongolica community so on. Artificial planting forest area, such as Robinia pseudoacacia and Pinus rigida forest and others, was 5.40%(612ha) and it was less than cases in other cities in the Metropolitan area. According to the classification by TWINSPAN, 57 survey plots were divided into seven community types; P rigida(community A), Q. acutissima(community B) P. densiflora-Q. acutissima(community C), Q. acutissima-P. densiflora (community D), P. densiflora-Carpinus laxiflora-Q. serrata-Q. acutissima(community E), Q. serrata-Q. mongolica(community F), and Zelkova serrata-Acer mono(community G). From this result, ecological succession trend of vegetation in this area seems to be change from P. densiflora forest through Q. acutissima forest to Q. mongolica, Q. serrata, and C. laxiflora forest. It was similar to the ordinary successional trend of temperate deciduous forest in middle area, Korea. In addition, this study area was showed acid soil(pH 4.17). Therefore, there is a need for managing the soil environment for effective vegetation management.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.439-442
• /
• 1999

It is important to analyze the seasonal change profiles of land cover type in large scale for establishing preservation strategy and environmental monitoring. Because the NOAA-AVHRR data sets provide global data with high temporal resolution, it is suitable for the land cover classification of the large area. The objectives of this study were to classify land cover of Korea, to investigate the phenological profiles of land cover. The NOAA-AVHRR data from Jan. 1998 to Dec. 1998 were received by Korea Ocean Research & Development Institute(KORDI) and were used for this study. The NDVI data were produced from this data. And monthly maximum value composite data were made for reducing cloud effect and temporal classification. And the data were classified using the method of supervised classification. To label the land cover classes, they were classified again using generalized vegetation map and Landsat-TM classified image. And the profiles of each class was analyzed according to each month. Results of this study can be summarized as follows. First, it was verified that the use of vegetation map and TM classified map was available to obtain the temporal class labeling with NOAA-AVHRR. Second, phenological characteristics of plant communities of Korea using NOAA-AVHRR was identified. Third, NDVI of North Korea is lower on Summer than that of South Korea. And finally, Forest cover is higher than another cover types. Broadleaf forest is highest on may. Outline of covertype profiles was investigated.

• Korean Journal of Environment and Ecology
• /
• v.23 no.3
• /
• pp.258-271
• /
• 2009

Various environmental parameters change and ecological succession often lead to decline of Pinus densiflora forest in Seoul. Due to decline of it, we proposed the ecological management for conserving and improving from decrease of its dominant area on there. We analysed the P. densiflora forest's classification and suggested its ecological management that based on relation to competition between dominant species in the upper tree layer, the presence of competitive species in shrub layer and vegetation management standard. The Pinus densiflora forest types has been classified 6 types by ecological characteristics. The results from categorized its types are following as; 1) Pinus densiflora pure forest type; edaphic climax Pinus densiflora forest(26.1%), Pinus densiflora pure forest(21.5%). 2) the forest of Pinus densiflora and other species that compete with each other type; Pinus densiflora-Quercus mongolica forest(28.0%), Pinus densiflora-Pinus rigida forest(13.1%), Pinus densiflora-Quercus acutissima(4.2%). We conclude that the results in these kind of 4 types; Pinus densiflora pure forest type where possible to maintain the forest by edaphic climax, human trampling damage, vegetation management(e.x. remove the competition species, shrub layers management etc.) are mainly need to negative management. Whereas, the others 4 types; Pinus densiflora and other species(Quercus variabilis, foreign species, naturalized species etc.) that compete with each other types are need to positive management such as manage the same niche competition species, shrub layers management, remove the foreign species, naturalized species etc.. In these kinds of ecological management are very necessary to maintain Pinus densiflora forest.

• Korean Journal of Remote Sensing
• /
• v.34 no.4
• /
• pp.661-670
• /
• 2018

This study aims to develop a methodology of convolutional neural networks (CNNs) to produce thematic maps from remote sensing data. Optimizing the image size for CNNs was studied, since the size of the image affects to accuracy, working as hyper-parameter. The selected study area is Mt. Ung, located in Dangjin-si, Chungcheongnam-do, South Korea, consisting of both coniferous forest and deciduous forest. Spatial structure analysis and the classification of forest type using CNNs was carried in the study area at a diverse range of scales. As a result of the spatial structure analysis, it was found that the local variance (LV) was high, in the range of 7.65 m to 18.87 m, meaning that the size of objects in the image is likely to be with in this range. As a result of the classification, the image measuring 15.81 m, belonging to the range with highest LV values, had the highest classification accuracy of 85.09%. Also, there was a positive correlation between LV and the accuracy in the range under 15.81 m, which was judged to be the optimal image size. Therefore, the trial and error selection of the optimum image size could be minimized by choosing the result of the spatial structure analysis as the starting point. This study estimated the optimal image size for CNNs using spatial structure analysis and found that this can be used to promote the application of deep-learning in remote sensing.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.258-261
• /
• 2007

Although there have been lack of studies using X-band SAR data particularly for forestry application as compared to C-, and L-band SAR data, it has a potential to distinguish tree species because most signals are backscattered on the top of canopy. This study aimed to compare signal characteristics of multi-band SAR data including X-band for classifying tree species. The data used for the study are SIR-C/X-SAR data (X-, C-, L-band) obtained on Oct. 3, 1994 over the forest area near Seoul, S. Korea. Thirty ground sample plots were collected per each tree species. Initial comparison of backscattering coefficients among three SAR bands shows that X-band data showed better separation of tree species than C- and L-band SAR data irrespective of polarization. The weak penetrating in canopy layer might be possible source of information for X-band data to be useful for the classification of forest species and cover type mapping.

• Advances in nano research
• /
• v.14 no.3
• /
• pp.225-234
• /
• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.