• 대기
• /
• 제19권2호
• /
• pp.169-182
• /
• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• 대한원격탐사학회지
• /
• 제22권3호
• /
• pp.199-209
• /
• 2006

The Global Land Cover 2000 (GLC 200) project, as a most recent issue, is to provide for the year 2000 a harmonized land cover database over the whole globe. The classifications were performed according to continental or regional scales by corresponding organization using the data of VEGETATION sensor onboard the SPOT4 Satellite. Even if the global land cover classification for Asia provided by Chiba University showed a good accuracy in whole Asian area, some problems were detected in Korean region. Therefore, the construction of new land cover database over Korea is strongly required using more recent data set. The present study focuses on the development of a new upgraded land cover map at 1 km resolution over Korea considering the widely used K-means clustering, which is one of unsupervised classification technique using distance function for land surface pattern classification, and the principal components transformation. It is based on data sets from the Earth observing system SPOT4/VEGETATION. Newly classified land cover was compared with GLC 2000 for Korean peninsula to access how well classification performed using confusion matrix.

• 한국측량학회:학술대회논문집
• /
• 한국측량학회 2007년도 춘계학술발표회 논문집
• /
• pp.383-387
• /
• 2007

The improved accuracy of the Land Cover/Land Use Map constructed using Hyperspectal Satellite Image and the possibility of real time classification of Land Use using optimal Band Selective Factor enable the change detection from automatic classification using the existed Land Cover/Land Use Map and the newly acquired Hyperspectral Satellite Image. In this study, the effective analysis techniques for automatic generation of training regions, automatic classification and automatic change detection are proposed to minimize the expert's interpretation for automatic update of the Land Cover/Land Use Map. The proposed algorithms performed successfully the automatic Land Cover/Land Use Map construction, automatic change detection and automatic update on the image which contained the changed region. It would increase applicability in actual services. Also, it would be expected to present the effective methods of constructing national land monitoring system.

• 한국측량학회:학술대회논문집
• /
• 한국측량학회 2003년도 춘계학술발표회 논문집
• /
• pp.397-408
• /
• 2003

The information about land use presents future development and vision being the basis of nation development; therefore, it is necessary to more active research that can detect wide land use and changes for the information and efficient management about land use. In this study, we wished to analyze effectively land use changes to Ansan city that is fast changing land use by the latest national land development and urbanization. this study executed land-cover classification using 4 year's Landsat TM images including Ansan city, and efficiently could manage the result of land-cover changes through Arc/Info GRID analysis. Especially, by using change detection system that is developed in this research, we could variously detect land-cover changes, and query and search easily past land-cover changes of pixels that correspond to specific region.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.116-121
• /
• 1998

Global land related datasets such as land use, land cover, vegetation cover percentage, forest cover percentage, are part of important global geospatial environmental datasets for global change studies. Since land cover varies place by place, continental production of dataset is a usual approach. Western academically developed countries have some projects to describe land cover related information in digital form using remote sensing technology in African, American continent and Oceania. In this paper, the author introduce his initiative to coordinate Asian scientists in order to develop land related dataset of Asia for our better understanding of the environment of Asia and for contribution to the development of global dataset. This paper explains activities by Land Cover Working Group (LCWG) of the Asian Association on Remote Sensing(AARS), Data and Information System(DIS) sub-committee of Japan national committee for the International Geosphere and Biosphere Program(IGBP), and the International Society for Photogrammetry and Remote Sensing(ISPRS) Working Group IV/6 on Global databases supporting environmental monitoring.

• 대한원격탐사학회지
• /
• 제39권1호
• /
• pp.99-110
• /
• 2023

Land surface temperature (LST) is a critical environmental indicator affected by land cover (LC) changes. Currently, the most convenient and fastest way to retrieve LST is to use remote sensing images due to their continuous monitoring of the Earth's surface. The work intended to investigate land cover change and temperature response inAn-Najaf province. Landsat multispectral imageries acquired inAugust 1989, 2004, and 2021 were employed to estimate land cover change and LST responses. The findings exhibited an increase in water bodies, built-up areas, plantations, and croplands by 7.78%, 7.27%, 6.98%, 3.24%, and 7.78%, respectively, while bare soil decreased by 25.27% for the period (1989-2021). This indicates a transition from barren lands to different land cover types. The contribution index (CI) was employed to depict how changes in land cover categories altered mean region surface temperatures. The highest LSTs recorded were in bare lands (42.2℃, 44.25℃, and 46.9℃), followed by built-up zones (41.6℃, 43.96℃, and 44.89℃), cropland (30.9℃, 32.96℃, and 34.76℃), plantations (35.4℃, 36.97℃, and 38.92℃), and water bodies (27.3℃, 29.35℃, and 29.68℃) respectively, in 1989, 2004, and 2021. Consequently, these changes resulted in significant variances in LST between different LC types.

• 대한원격탐사학회지
• /
• 제33권6_2호
• /
• pp.1089-1100
• /
• 2017

이 논문에서는 토지피복도 갱신을 목적으로 영상의 객체분할과 훈련 자료 수집에 과거 토지피복도의 정보를 이용하는 방법을 제안하였다. 제안한 방법에서는 영상의 객체분할 시 명확한 토지피복 경계 분할을 위해 과거 토지피복도의 객체 경계를 이용하였다. 또한 적은 수의 초기 훈련 자료를 이용한 초기 분류 결과로부터 유용한 훈련 자료를 추가로 수집하기 위해 과거 토지피복도의 분류 항목 정보를 이용하였다. 충청남도 태안군 일부 지역을 대상으로 환경부 중분류 토지피복도와 WorldView-2 영상을 이용한 토지피복 갱신 사례 연구를 통해 제안된 토지피복도 갱신 방법론의 적용 가능성을 검토하였다. 사례 연구 결과, 초기 분류 결과에서 나타난 시가지와 나지, 논/밭과 초지의 오분류 양상이 제안 방법론을 통해 완화되었다. 또한 과거 토지피복도의 경계를 이용한 객체분할을 통해 객체의 경계를 명확하게 하고 분류 정확도를 향상시켰다. 따라서, 이 연구에서 제안된 방법이 토지피복도 갱신에 유용하게 적용될 수 있을 것으로 기대된다.

• 지적과 국토정보
• /
• 제51권2호
• /
• pp.169-184
• /
• 2021

최근 초분광 영상을 기반으로 토지피복을 분류하는 연구에서 토지피복 분광 라이브러리가 많이 활용되고 있다. 해외에서는 다양한 기관에서 토지피복 분광 라이브러리를 구축 및 제공하고 있지만, 국내의 경우 토지피복 분광 라이브러리의 구축 및 제공이 부족한 실정이다. 이러한 배경에서 본 연구는 국내 토지피복의 분류 연구에서 국내외 분광 라이브러리의 활용 가능성을 제시하는데 목적이 있다. 분광 라이브러리의 비교분석 및 분광 라이브러리를 이용한 토지피복분류에는 밴드매칭이 요구되며, 본 연구에서는 이를 자동적으로 수행하기 위한 자동화 로직을 제시하였다. 또한 직접 구축한 국내 토지피복 분광 라이브러리와 기구축 해외 토지피복 분광 라이브러리를 비교분석하였으며, 그 결과 직접 구축한 토지피복 분광 라이브러리의 상관계수가 0.974로 가장 높게 나타났다. 최종적으로 정확도 평가를 위해 국내외 토지피복 분광 라이브러리를 이용하여 연구대상지역의 항공 초분광 영상을 SAM기법으로 감독분류 하였으며, 그 결과 직접 구축한 분광 라이브러리의 전체정확도가 91.78%로 가장 높게 나타났다. 정확도 평가 결과 해외 토지피복 분광 라이브러리의 분류항목 중 Soils, Artificial Materials, Coatings는 국내에서도 충분히 피복을 분류하는데 적용 가능할 것으로 판단된다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.1030-1032
• /
• 2003

This study a imed to analyze the effect of combined optical and radar image for the land cover classification in coastal region. The study area, Gyeonggi Bay area has one of the largest tidal ranges and has frequent land cover changes due to the several reclamations and rather intensive land uses. Ten land cover types were classified using several datasets of combining Landsat ETM+ and RADARSAT imagery. The synergic effects of the merged datasets were analyzed by both visual interpretation and an ordinary supervised classification. The merged optical and SAR datasets provided better discrimination among the land cover classes in the coastal area. The overall classification accuracy of merged datasets was improved to 86.5% as compared to 78% accuracy of using ETM+ only.

• Journal of Forest and Environmental Science
• /
• 제36권3호
• /
• pp.199-206
• /
• 2020

Satchari National Park is one of the most biodiverse forest in Bangladesh and home of many endangered flora and fauna. 206 tons of CO₂ per hectare is sequestrated in this national park every year which helps to mitigate climate issues. As people living near the area are dependent on this forest, degradation has become a regular phenomenon destroying the forest biodiversity by altering its forest cover. So, it is important to map land cover quickly and accurately for the sustainable management of Satchari National Park. The main objective of this study was to obtain information on land cover change using remote sensing data. Combination of unsupervised NDVI classification and supervised classification using maximum likelihood is followed in this study to find out land cover map. The analysis showed that the land cover is gradually converting from one land use type to another. Dense forest becoming degraded forest or bare land. Although it was slowed down by the establishment of 'National Park' on the study site, forecasting shows that it is not enough to mitigate forest degradation. Legal steps and proper management strategies should be taken to mitigate causes of degradation such as illegal felling.