• Title/Summary/Keyword: land classification

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Development of Ridge Distinction Program of The Mountainous Districts using GIS Program (GIS를 이용한 산지의 능선구분 프로그램 개발)

  • Park, Young-Kyu;Kwon, Soon-Duk;Kim, Tae-Kyun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.4
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    • pp.87-96
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    • 2007
  • In this study, a Ridge Distinction Program was developed to improve the elevation standard, which is one of standards for mountainous districts conversion permission regulated by the Management of Mountainous Districts Act. To distinguish mountainous districts from other land types, this program assumed that the lower end of the mountainous districts is the outlet points where catchment size is 30ha. Also the program used the halfway line between the ridge and the lower end of the mountainous districts to recognize the upper slope areas. To prevent potential errors within the classification process, the areas that were classified as non-mountainous districts by the current forest type map were removed. According to the classification results by using the developed program, the 58% of the mountainous districts ($696,300m^2$) was classified into the upper slope area, while the only 3% of the mountainous districts ($30,956m^2$) were classified by adopting the current standards for the mountainous districts conversion permission. This result shows that the size of the upper slope areas tends to be altered by the standards defining the area. Therefore, for better acceptance of the Ridge Distinction Program in the associated fields, it is necessary to prove the effectiveness of the program and to revise the current standards for the mountainous districts conversion permission.

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Distribution of the Kentish Plover (Charadrius Alexandrinus) Based on the 3rd National Ecosystem Survey and Its Adequacy as a Bioindicator (제 3차 전국자연환경조사를 이용한 흰물떼새(Charadrius alexandrinus)의 분포현황과 생물지표종의 제안)

  • Kim, Woo-Yuel;Bae, So-Yeon;Oh, Su-Jeung;Yoon, Hee-Nam;Lee, Jung-Hyo;Paek, Woon-Kee;Sung, Ha-Cheol
    • Korean Journal of Environment and Ecology
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    • v.30 no.2
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    • pp.155-164
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    • 2016
  • In this study we analyzed the spatial and temporal distribution and preferred habitat type of the Kentish plover (Charadrius alexandrinus) based on the 3rd National Ecosystem Survey. Kentish plovers were observed in 97 maps out of a total 842 maps (11.8%) between 2006 and 2012, mainly along the western and southern coasts of Korea. They were also observed in the eastern coast of Korea, inland rivers (Han, Geum, Nakdong, Seomjin, and Yongsan River), the western and eastern coast of Jeju island, and Daecheong Island in the Yellow Sea. The observations were mainly made during the spring breeding season and migration seasons in spring and autumn. The occurrence of kentish plovers was positively influenced by the area of water and wetland according to the middle classification level of land cover type analysis and the area of coastal wetlands in the detailed classification level of land cover types. Most (90%) of the kentish plovers recorded maps had coastal wetlands. Kentish plovers were known to be susceptible to change of habitat. As the occurrence of kentish plovers could be associated with the habitat-change of coastal wetlands and it is possible to estimate the number of individuals, it is recommended that kentish plovers be used as a bioindicator species for the ecological assessment of ecosystem in intertidal zones.

A Study on the Improvement classification accuracy of Land Cover using the Aerial hyperspectral image with PCA (항공 하이퍼스펙트럴 영상의 PCA기법 적용을 통한 토지 피복 분류 정확도 개선 방안에 관한 연구)

  • Choi, Byoung Gil;Na, Young Woo;Kim, Seung Hyun;Lee, Jung Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.1
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    • pp.81-88
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    • 2014
  • The researcher of this study applied PCA on aerial hyper-spectral sensor and selectively combined bands which contain high amount of information, creating five types of PCA images. By applying Spectral Angle Mapping-supervised classification technique on each type of image, classification process was carried out and accuracy was evaluated. The test result showed that the amount of information contained in the first band of PCA-transformation image was 76.74% and the second accumulated band contained 98.40%, suggesting that most of information were contained in the first and the second PCA components. Quantitative classification accuracy evaluation of each type of image showed that total accuracy, producer's accuracy and user's accuracy had similar patterns. What drew the researcher's attention was the fact that the first and the second bands of the PCA-transformation image had the highest accuracy according to the classification accuracy although it was believed that more than four bands of PCA-transformation image should be contained in order to secure accuracy when doing the qualitative classification accuracy.

A Study on the Development of BIM Property Classification System in Road and River Field (도로 및 하천분야 BIM 속성분류체계 개발방안 연구)

  • Nam, Jeong-Yong;Kim, Min-Jeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.773-784
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    • 2019
  • With the recent development of 4th industrial revolution technology, BIM information systems are spreading to civil engineering fields as a link to this technology. Accordingly, the Land, Infrastructure and Transport Ministry is announcing a technical policy to introduce the BIM information system into the construction sector from 2020. Usually, SOC-related facilities are complex, making it difficult to implement BIM without a standards framework. To overcome these problems, it is urgent to develop a BIM standard classification system. In this study, the BIM property classification system was developed to link the previously developed object classification system by analyzing domestic and foreign prior studies and working standards. This includes property information of businesses, facilities, parts of facilities and components that correspond to the level of object composition in the road and river sectors. It also suggested ways to apply expansion to various SOC areas and to organize spatial information by facility. The results of this study were applied to road facilities to verify the possibility of information building. The development of the BIM Standards Classification System through this R&D will contribute to the development of construction IT by providing conditions for convenient modeling and information system.

Mapping 3D Shorelines Using KOMPSAT-2 Imagery and Airborne LiDAR Data (KOMPSAT-2 영상과 항공 LiDAR 자료를 이용한 3차원 해안선 매핑)

  • Choung, Yun Jae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.1
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    • pp.23-30
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    • 2015
  • A shoreline mapping is essential for describing coastal areas, estimating coastal erosions and managing coastal properties. This study has planned to map the 3D shorelines with the airborne LiDAR(Light Detection and Ranging) data and the KOMPSAT-2 imagery, acquired in Uljin, Korea. Following to the study, the DSM(Digital Surface Model) is generated firstly with the given LiDAR data, while the NDWI(Normalized Difference Water Index) imagery is generated by the given KOMPSAT-2 imagery. The classification method is employed to generate water and land clusters from the NDWI imagery, as the 2D shorelines are selected from the boundaries between the two clusters. Lastly, the 3D shorelines are constructed by adding the elevation information obtained from the DSM into the generated 2D shorelines. As a result, the constructed 3D shorelines have had 0.90m horizontal accuracy and 0.10m vertical accuracy. This statistical results could be concluded in that the generated 3D shorelines shows the relatively high accuracy on classified water and land surfaces, but relatively low accuracies on unclassified water and land surfaces.

Surface Water Mapping of Remote Sensing Data Using Pre-Trained Fully Convolutional Network

  • Song, Ah Ram;Jung, Min Young;Kim, Yong Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.5
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    • pp.423-432
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    • 2018
  • Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.

An intercomparison of two satellite data-based evapotranspiration approaches (인공위성 데이터 기반의 두 공간 증발산 산정 모형 비교 분석)

  • Sur, Chan-Yang;Choi, Min-Ha
    • Journal of Wetlands Research
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    • v.13 no.3
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    • pp.471-479
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    • 2011
  • Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

Distribution Characteristics and Background Air Classification of PM2.5 OC and EC in Summer Monsoon Season at the Anmyeondo Global Atmosphere Watch (GAW) Regional Station (안면도 기후변화감시소의 여름철 PM2.5 OC와 EC 분포 특성 및 배경대기 구분)

  • Ham, Jeeyoung;Lee, Meehye;Ryoo, Sang-Boom;Lee, Young-Gon
    • Atmosphere
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    • v.29 no.4
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    • pp.429-438
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    • 2019
  • Organic carbon (OC) and elemental carbon (EC) in PM2.5 were measured with Sunset Laboratory Model-5 Semi-Continuous OC/EC Field Analyzer by NIOSH/TOT method at Anmyeondo Global Atmosphere Watch (GAW) Regional Station (37°32'N, 127°19'E) in July and August, 2017. The mean values of OC and EC were 3.7 ㎍ m-3 and 0.7 ㎍ m-3, respectively. During the study period, the concentrations of reactive gases and aerosol compositions were evidently lower than those of other seasons. It is mostly due to meteorological setting of the northeast Asia, where the influence of continental outflow is at its minimum during this season under southwesterly wind. While the diurnal variation of OC and EC were not clear, the concentrations of O3, CO, NOx, EC, and OC were evidently enhanced under easterly wind at night from 20:00 to 8:00. However, the high concentration of EC was observed concurrently with CO and NOx under northerly wind during 20:00~24:00. It indicates the influence of thermal power plant and industrial facilities, which was recognized as a major emission source during KORUS-AQ campaign. The diurnal variations of pollutants clearly showed the influence of land-sea breeze, in which OC showed good correlation between EC and O3 in seabreeze. It is estimated to be the recirculation of pollutants in land-sea breeze cycle. This study suggests that in general, Anmyeondo station serves well as a background monitoring station. However, the variation in meteorological condition is so dynamic that it is primary factor to determine the concentrations of secondary species as well as primary pollutants at Anmyeondo station.

Detection and Classification of Major Aerosol Type Using the Himawari-8/AHI Observation Data (Himawari-8/AHI 관측자료를 이용한 주요 대기 에어로솔 탐지 및 분류 방법)

  • Lee, Kwon-Ho;Lee, Kyu-Tae
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.3
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    • pp.493-507
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    • 2018
  • Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

Vegetation Interannualvariavility Over Korea Using 10-Years 1KM NDVI Data (1KM NDVI 10년 자료를 이용한 한반도 식생의 경년변동 분석)

  • Kim, In-Hwan;Han, Kyung-Soo;Kim, Sang-Il
    • Korean Journal of Remote Sensing
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    • v.27 no.1
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    • pp.17-24
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    • 2011
  • Global warming and climatic changes due to human activities impact on marine and terrestrial ecosystems, which feedbacks to climate system. These negative feedbacks amplify or accelerate again global climate change. In particular, it is important to analyze vegetation change. This study attempts to analyze quantitatively vegetation change in Korea peninsula by using harmonic analysis. Harmonic-Analysis based on Fourier Transform is the method to effectively demonstrate for time series data. Especially, Harmonic-Analysis is very suitable method to analyze vegetation change because the vegetation repeats the cycle growth and extinction every year. The result of harmonic-analysis shows vegetation change as time passes. In this study, SPOTNEGETATION S10 MVC NDVI data was used during last 10 years (1999-2008) in Korea Peninsula. Also, land type classification used MODIS Land Cover Map data. The study estimated that phase values moved up approximately 0.5 day per year in cropland and 0.8 day per year in forest.