• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.151-167
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• 2019

Korea's current Land Category Classification System(LCCS) can not accurately register of complex and diverse Status of land use in Cadastral Record. Therefore, in order to draw implications for the improvement of LCCS in Korea, Shin SW and four others published a paper titled 'A Study on Land Category System of Domestic and Foreign Country' in 2013. This paper compared the 'land category', 'land use' and 'land cover' of six countries on the same line, and Some non-factual content was described. So, presented a new perspective on this. Looking forward, I hope that reasonable alternative will be presented based on the understanding of LCCS of Germany, Japan and Taiwan. In the future research project, to study the history of LCCS in Germany and Taiwan and suggest to refer to improvement of LCCS of Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.32-44
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• 1999

Texture features can be incorporated in classification procedure to resolve class confusions. However, there have been few application-oriented studies made to evaluate the relative powers of texture analysis methods in a particular environment. This study evaluates the increases in the land-cover classification accuracy of the SPOT HRV multispectral data of Pusan Metropolitan area from texture processing. Twenty-four texture measures were derived from the SPOT HRV band 3 image. Each of these features were used in combination with the three spectral images in the classification of 10 land-cover classes. Supervised training and a Gaussian maximum likelihood classifier were used in the classification. It was found that while entropy produces the best empirical results in terms of the overall classification, other texture features can also largely improve the classification accuracies obtained by the use of the spectral images only. With the inclusion of texture, the classification for each category improves. Specially, urban built-up areas had much increase in accuracy. The results indicate that texture size 5 by 5 and 7 by 7 may be suitable at land cover classification of Pusan Metropolitan area.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.570-570
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• 2016

홍수해석을 위해서는 DEM, 토지피복도, 토양도 등을 이용해서 대상 유역의 수문지형학적 매개변수를 도출해야 한다. 이때 북한과 같은 비접근 지역이나, 지상 관측에 의한 자료가 부족한 해외 지역에 대한 유출해석을 위해서는 대상 지역에 대한 상세한 자료를 얻기 어려우므로, 위성영상이나 전지구 데이터베이스 등과 같은 글로벌 자료를 이용하는 것이 대안이 될 수 있다. 글로벌 지형공간 자료로는 ASTER GDEM과 같은 DEM, Global Map과 같은 토지피복도, HWSD(Harmonized World Soil Database)와 같은 토양도를 이용할 수 있다. 본 연구에서는 이 중 HWSD의 적용성을 평가하였다. HWSD는 UN FAO(Food and Agriculture Organization of the United Nations)의 토지이용변경 프로그램에 따른 지도와 지역 및 국가 토양데이터베이스를 조합해서 만들어 졌으며, 30 arc-second(약 1km)의 해상도를 가진다. 유출해석은 물리적 분포형 모형인 GRM(Grid based Rainfall-runoff Model)을 이용하였으며, 낙동강 수계의 향석 수위관측소 유역을 대상으로 2008년과 2009년에 발생한 2개의 수문사상을 이용하여 연구를 진행하였다. 토양도를 제외한 자료(DEM, 토지피복도 등)는 모두 국내에서 구축된 자료를 이용하였다. 우리나라의 정밀토양도를 이용해서 보정된 모형(매개변수)에 HWSD 자료를 적용한 유출해석 결과, 두 사상에서 모두 유량이 크게 모의되었다. 이는 HWSD에서는 유역 전체가 양토(수리전도도 0.34cm/h)로 정밀토양도(향석 유역 평균 수리전도도 1.07cm/h)에 비해 약 1/3의 수리전도도 값을 가지고, 정밀토양도를 적용한 경우의 평균 토양심은 70cm이지만 HWSD에서는 37cm로 상대적으로 작기 때문에 토양 침투량은 작아지고, 유출량이 크게 계산되는 것으로 판단된다. HWSD를 이용한 모형 보정에서는 토양 수리전도도와 토양심 매개변수를 중심으로 보정하였으며, 그 결과 관측 유량을 잘 재현할 수 있었다. 위성영상을 이용해서 구축되는 토지피복도와는 달리, 토양정보는 원시 자료가 구축된 지역에 따라서 구축방법, 정확도 등에서 크게 차이가 날 수 있다. 그러므로 글로벌 자료를 이용한 유출해석에서는 토양 자료의 적용 및 이와 관련된 매개변수의 주의가 필요할 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1035-1046
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• 2022

This study evaluated the applicability of multi-resolution data fusion for land-cover classification. In the applicability evaluation, a spatial time-series geostatistical deconvolution/fusion model (STGDFM) was applied as a multi-resolution data fusion model. The study area was selected as some agricultural lands in Iowa State, United States. As input data for multi-resolution data fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite images were used considering the landscape of study area. Based on this, synthetic Landsat images were generated at the missing date of Landsat images by applying STGDFM. Then, land-cover classification was performed using both the acquired Landsat images and the STGDFM fusion results as input data. In particular, to evaluate the applicability of multi-resolution data fusion, two classification results using only Landsat images and using both Landsat images and fusion results were compared and evaluated. As a result, in the classification result using only Landsat images, the mixed patterns were prominent in the corn and soybean cultivation areas, which are the main land-cover type in study area. In addition, the mixed patterns between land-cover types of vegetation such as hay and grain areas and grass areas were presented to be large. On the other hand, in the classification result using both Landsat images and fusion results, these mixed patterns between land-cover types of vegetation as well as corn and soybean were greatly alleviated. Due to this, the classification accuracy was improved by about 20%p in the classification result using both Landsat images and fusion results. It was considered that the missing of the Landsat images could be compensated for by reflecting the time-series spectral information of the MODIS images in the fusion results through STGDFM. This study confirmed that multi-resolution data fusion can be effectively applied to land-cover classification.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.199-204
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• 2006

도시의 변화에 대하여 보다 체계적으로 계획하고 관리하기 위해서는 도시지역에 대한 정확한 지리 정보의 획득이 필요하며 이와 더불어 정보의 신속한 갱신이 필요하다. 도시 변화를 판단하기 위한 지리정보는 여러 가지 정책과 연구에 사용될 수 있을 뿐만 아니라 그 자체만으로도 도시의 성장을 기록하는 중요한 자료로 이용될 수 있다. 지리 정보의 획득 방법 중 하나인 영상분류 방법은 여러 가지가 있으나, 그 중 건물, 도로, 수목, 논, 밭 등 지상의 물체들의 분광특성을 이용한 방법이 가장 효율적이라고 할 수 있다. 따라서 본 연구에서는 도심지의 토지피복분류 현황을 기존의 방법보다 더욱 정확히 분석하기 위해서 IKONOS 영상을 이용하여 분석방법에 따른 정확도를 비교 분석하고 GIS를 이용하여 토지피목 현황을 분류기법별로 나타내며, 대상지역의 분류 정확도와 정보를 제시하였다. 연구 결과 도심지에서는 최대우도법을 이용한 감독 분류의 정확도가 가장 높은 정확도를 나타내었으며, 주관성을 배제한 분류 방법에는 신경망을 이용한 분류 방법이 높은 정확도를 나타내었다. 또한 분류 기법 별로 분류된 토지피복도를 이용하여 분류 정확도와 분류항목에 대한 속성 자료를 GIS데이터베이스로 구축하여 사용자가 요구하는 정확도에 따라 분류 방법별 토지피복도를 제공함으로써 보다 신뢰성 있고 다양한 정보를 제공할 수 있었다.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.4
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• pp.25-33
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• 2015

The study of ecosystem assessment(ES) is based on land cover information, and primarily it is performed at the global scale. However, these results as data for decision making have a limitation at the aspects of range and scale to solve the regional issue. Although the Ministry of Environment provides available land cover data at the regional scale, it is also restricted in use due to the intrinsic limitation of on screen digitizing method and temporal and spatial difference. This study of objective is to generate UAV land cover map. In order to classify the imagery, we have performed resampling at 5m resolution using UAV imagery. The results of object-based image segmentation showed that scale 20 and merge 34 were the optimum weight values for UAV imagery. In the case of RapidEye imagery;we found that the weight values;scale 30 and merge 30 were the most appropriate at the level of land cover classes for sub-category. We generated land cover imagery using example-based classification method and analyzed the accuracy using stratified random sampling. The results show that the overall accuracies of RapidEye and UAV classification imagery are each 90% and 91%.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1771-1777
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• 2023

With the advancements of deep learning, many semantic segmentation-based methods for land cover classification have been proposed. However, existing deep learning-based models only use image information and cannot guarantee spatiotemporal consistency. In this study, we propose a land cover classification model using geographical coordinates. First, the coordinate features are extracted through the Coordinate Hash Encoder, which is an extension of the Multi-resolution Hash Encoder, an implicit neural representation technique, to the longitude-latitude coordinate system. Next, we propose an architecture that combines the extracted coordinate features with different levels of U-net decoder. Experimental results show that the proposed method improves the mean intersection over union by about 32% and improves the spatiotemporal consistency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.139-145
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• 2006

The advantage of the lidar data is in fast acquisition and process time as well as in high accuracy and high point density. However lidar data itself is difficult to classify the earth surface because lidar data is in the form of irregularly distributed point clouds. In this study, we investigated land cover classification using both lidar data and optical image through a supervised classification method. Firstly, we generated 1m grid DSM and DEM image and then nDSM was produced by using DSM and DEM. In addition, we had made intensity image using the intensity value of lidar data. As for optical images, the red, blue, green band of CCD image are used. Moreover, a NDVI image using a red band of the CCD image and infrared band of IKONOS image is generated. The experimental results showed that land cover classification with lidar data and optical image together could reach to the accuracy of 74.0%. To improve classification accuracy, we further performed re-classification of shadow area and water body as well as forest and building area. The final classification accuracy was 81.8%.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.305-317
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• 2002

The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.57-64
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• 2003

필지는 지번, 지목, 경계, 면적이라는 기본적인 구성요소를 가지고 있다. 그 가운데 토지의 가치는 대부분 지목에 의해 결정된다. 때문에 많은 수익이나 산출이 기대되는 용도로 토지를 이용하려는 욕구의 증가로 토지이용의 전환이 많이 이루어지고 있다. 결국, 이것은 토지의 불법형질변경, 난개발 등의 원인이 되고 있고, 지목불부합의 발생을 가중시키고 있다. 그러나 이에 대한 대처나 정리는 상대적으로 미흡한 편이다. 본 연구에서는 고해상도 위성영상과 수치지형도를 이용하여 지목을 기반으로 한 필지별 토지이용/토지피복을 분류할 수 있는 방법을 제안하였다. 그리고, 이렇게 분류된 필지별 토지이용/토지피복도와 편지지적도상의 지목을 비교·분석하여 지목불부합 정도를 통계적으로 측정하였다. 그 결과 연구지역의 불부합 정도에 대한 통계적인 해석이 가능하여, 향후 지적불부합지를 정량적으로 자동 해석할 수 있는 가능성을 제시할 수 있었다.