• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.79-92
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• 2017

To offer the basic data of vegetation restoration by buried seed of soil, this research was conducted at bare land and abandoned field in Yesan-gun. Germination plants of buried seed were consisted of 40 taxa (37 species, 3 varieties) in bare land, and 41 taxa (37 species, 4 varieties) in abandoned field. Classification of germination plants by family was the most in Gramineae, and emergent frequency of plots was the highest of Digitaria ciliaris. The soil depth of the most plants appearance was 2~5cm in bare land and 5~10cm in abandoned field, and the soil depth of the most population appearance was 0~2cm both in bare land and in abandoned field. Population number of buried seed germination was decreased according to soil depth. Crepidiastrum sonchifolium was a plant that population number of buried seed germination is the most. Similarity index was 0.33 in aerial part plants and buried seed plants, and 0.55 in bare land and abandoned field.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.102-106
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• 2005

As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.421-425
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• 2006

It can be important framework data to monitor the change of land-use pattern of river boundary in design and management of river. This study analyzed the change of land-use pattern of Gab and Yudeung River using time-series aerial images. To do this, we carried out radiation and geometric correction of image, and estimated land-use changes in inland and floodplain. As the analysis of inland, the ratio of residential, commercial, industrial, educational and public area, that is urbanized element, increases, but that of agricultural area shows a decline on the basis of 1990. Also, Minimum Distance Method, which is a kind of supervised classification method, is applied to extract water-body and sand bar layer in floodplain. As the analysis of land-use, the ratio of level-upped riverside land and water-body increases, but that of sand bar decreases. These time-series land use information can be important decision making data to evaluate the urbanization of river boundary, and especially it gives us goodness in river development project such as the composition of ecological habitat.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.2
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• pp.53-69
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• 2011

Classification of estuaries based on their multi-component and multidisciplinary processes is important for the systematic management of estuaries. In this study, an integrated GlS-based analysis system including high resolution aerial photographies and topographic maps was used to classify 463 estuaries based on estuarine circulation pattern, geomorphological feature, natural habitat distribution and characteristics of land use. These estuaries were divided into two basic types, open and closed. Two hundred and thirty five systems were open estuaries comprising of forty one mountainous type (OM), eighty sevcn sandpit type (OS) and one hundred seven funnel type (OF). Each type of open estuary was further classified into three types based on habitat distribution and land use characteristics resulting in total ninc types of open estuaries. Two hundred and twenty eight estuaries were closed systems comprising of one hundred and forty four blocked type (CB directly) and eighty four lake type (CL, indirectly). CB type estuary was further classified into three types based on habitat distribution and land use characteristics. This estuarine classification scheme can be applied to provide a framework for effective management strategies of individual estuaries to estimate the management priority and strategy.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.454-461
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• 2015

This study aims to classify the biotope types based on the vegetation community in built-up areas by different land use and to map the plant communities. By classifying biotopes according to a taxonomic system, the characteristics of a biological community can be well-represented. The biotope classification indexes for the target area include human behavioral factors such as land use intensity, land-use patterns and land-cover types. The type classification was divided into four hierarchic ranks starting with Biotope Class, next by Biotope Group and Biotope Type and lastly by Biotope Sub-Type. The Biotope Class was first divided into two areas: the areas improved by humans and the areas unimproved by humans. The improved areas were again divided into permeable and non-permeable regions on the Biotope Group level. In the Biotope Type level, permeable paving areas were divided into areas with wide gap pavers and those with narrow gap pavers. The differential species of each biotope type are Lindera glauca, Conyza canadensis, Mazus pumilus, Vicia tetrasperma, Crepidiastrum sonchifolium, Zoysis japonica, Potentilla supina and Festuca arundinacea. The results of this study suggest that the biotope classification methodology, using a subjective phytosociological approach, is a useful and valuable tool and the results also suggest the possibility of applying more objective and scientific methods in mapping and classifying various environments.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.353-364
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• 2016

Yangon city is experienced a rapid urban expansion over the last two decades due to accelerate with the socioeconomic development. This research work studied an investigation into the application of the integration of the Remote Sensing (RS) and Geographic Information System (GIS) for observing Land Use and Land Cover (LULC) patterns and evaluate its impact on Land Surface Temperature (LST) of the downtown, suburban 1 and suburban 2 of Yangon city. The main purpose of this paper was to examine and analyze the variation of the spatial distribution property of the LULC of urban spatial information related with the LST and Normalized Difference Vegetation Index (NDVI) using RS and GIS. This paper was observed on image processing of LULC classification, LST and NDVI were extracted from Landsat 8 Operational Land Imager (OLI) image data. Then, LULC pattern was linked with the variation of LST data of the Yangon area for the further connection of the correlation between surface temperature and urban structure. As a result, NDVI values were used to examine the relation between thermal behavior and condition of land cover categories. The spatial distribution of LST has been found mixed pattern and higher LST was located with the scatter pattern, which was related to certain LULC types within downtown, suburban 1 and 2. The result of this paper, LST and NDVI analysis exhibited a strong negative correlation without water bodies for all three portions of Yangon area. The strongest coefficient correlation was found downtown area (-0.8707) and followed suburban 1 (-0.7526) and suburban 2(-0.6923).

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.76-88
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• 2015

This paper presents a classification method based on the combination of active learning with temporal contextual information extracted from past land-cover maps for the classification of crop cultivation areas. Iterative classification based on active learning is designed to extract reliable training data and cultivation rules from past land-cover maps are quantified as temporal contextual information to be used for not only assignment of training data but also relaxation of spectral ambiguity. To evaluate the applicability of the classification method proposed in this paper, a case study with MODIS time-series vegetation index data sets and past cropland data layers(CDLs) is carried out for the classification of corn and soybean in Illinois state, USA. Iterative classification based on active learning could reduce misclassification both between corn and soybean and between other crops and non crops. The combination of temporal contextual information also reduced the over-estimation results in major crops and led to the best classification accuracy. Thus, these case study results confirm that the proposed classification method can be effectively applied for crop cultivation areas where it is not easy to collect the sufficient number of reliable training data.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.5
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• pp.432-449
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• 2009

In this study, the effects of high-resolution land cover on the simulation of near-surface meteorological fields were evaluated in two different coastal regions using Weather Research and Forecasting (WRF) model. These analyses were performed using the middle classification land cover data upgraded by the Korean Ministry of Environment (KME). For the purpose of this study, two coastal areas were selected as follows: (1) the southwestern coastal (SWC) region characterized by complex shoreline and (2) the eastern coastal (EC) region described a high mountain and a simple coastline. The result showed that the application of high-resolution land cover were found to be notably distinguished between the SWC and EC regions. The land cover improvement has contributed to generate the realistic complex coastline and the distribution of small islands in the SWC region and the expansion of urban and built-up land along the sea front in the EC region, respectively. The model study indicated that the improvement of land cover caused a temperature change on wide areas of inland and nearby sea for the SWC region, and narrow areas along the coastal line for the EC region. These temperature variations in the two regions resulted in a decrease and an increase in land-breeze and sea-breeze intensity, respectively (especially the SWC region). Interestingly, the improvement of land cover can contribute large enough to change wind distributions over the sea in coastal areas.

• Spatial Information Research
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• v.15 no.1
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• pp.67-80
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• 2007

The land cover map represent the state of earth surfaces. It can be used as basic data to explore present conditions of earth surfaces and develop future plans for local areas. To produce the land cover map with efficiency, gathering geographic information from satellite images is important. Exporting, building, and managing processes on the land cover information are needed as well. In this study we aim to review the producing process of the level-2 land cover map in detail and enhance it. h present status of the producing process of the land cover map in Korea is reviewed, problems of the process are explored, and measures for improving it are proposed. The criteria for fixing boundaries and providing attributes for the land cover map are proposed. This proposed criteria may solve problems in a present producing process. The improving measures proposed in this study should be continuously revised in future studies.