• 대한원격탐사학회지
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• 제21권5호
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• 한국조경학회지
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• 제34권2호
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• pp.1-17
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• 2006

The purpose of this study was to analyze biotope types of urban land-use patterns. Forest areas were considered according to vegetation type and potential for succession. Urban ecosystem structure was analyzed according to land use, land coverage, vegetation structure (actual vegetation, diameter at breast height, layer structure, and revetment). As a results of the classification, the biotopes were divided into 71 types according to the urban ecosystem structure. In the case of the Hanam province, the biotopes were divided into 51 types: 26 forest types; 5 swampy and grass land types; 3 farm land types; 3 types of planted land, and 8 types of urbanization.

• 대한원격탐사학회지
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• 제26권6호
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• pp.665-673
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• 2010

The role of remote sensing in phenological studies is increasingly regarded as a key in understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for vegetation classification using seasonal variation patterns. The vegetation seasonal variation phase of Seoul and provinces in Korea was inferred using 8 day composite MODIS NDVI (Normalized Difference Vegetation Index) dataset of 2006. The seasonal vegetation classification approach is performed with reclassification of 4 categories as urban, crop land, broad-leaf and needle-leaf forest area. The BISE (Best Index Slope Extraction) filtering algorithm was applied for a smoothing processing of MODIS NDVI time series data and fuzzy classification method was used for vegetation classification. The overall accuracy of classification was 77.5% and the kappa coefficient was 0.61%, thus suggesting overall high classification accuracy.

• 한국측량학회지
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• 제35권1호
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• pp.23-30
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• 2017

NDVI (Normalized Difference Vegetation Index) plays an important role in surface land cover classification and LST (Land Surface Temperature Extraction). Its characteristics do not full carry the information of the surface cover typically in urban areas even though it is widely used in analyses in urban areas as well as in vegetation. However, abnormal NDVI values are frequently found in urban areas. We, therefore, examined NDVI values on whether NDVI is appropriate for LST and whether there are considerations in NDVI analysis typically in urban areas because NDVI is strongly related to the surface emissivity calculation. For the study, we observed the influence of the surface settings (i.e., geometric shape and color) on NDVI values in urban area and transition features between three land cover types, vegetation, urban materials, and water. Interestingly, there were many abnormal NDVI values systematically derived by the surface settings and they might influence on NDVI and eventually LST. Also, there were distinguishable transitions based on the mixture of three surface materials. A transition scenario was described that there are three transition types of mixture (urban material-vegetation, urban material-water, and vegetation-water) based on the relationship of NDVI and LST even though they are widely distributed.

• 한국측량학회지
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• 제31권6_2호
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• pp.521-527
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• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.598-601
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• 2007

Urban growth management is essential for sustainable urban growth. Monitoring physical urban built-up area is a task of great significance to manage urban growth. Detecting urbanized area is essential for monitoring urbanized area. Although image classifications using satellite imagery are among the conventional methods for detecting urbanized area, they requires very tedious and hard work, especially if time-series remote sensing data have to be processed. In this paper, we propose an effective urbanized area detecting method based on normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). To verify the proposed method, we extract urbanized area using two methods; one is conventional supervised classification method and the other is the proposed method. Experiments shows that two methods are consistent with 98% in 1998, 99.3% in 2000, namely the consistency of two methods is very high. Because the proposed method requires no more process without band operations, it can reduce time and effort. Compared with the supervised classification method, the proposed method using vegetation indices can serve as quick and efficient alternatives for detecting urbanized area.

• 대한공간정보학회지
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• 제21권4호
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• pp.21-27
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• 2013

최근 탄소 흡수원으로 산림자원의 체계적인 관리의 중요성이 높아지고 있다. 특히 도심지역에서의 산림자원은 탄소 흡수원 뿐만 아니라 도시자연의 환경개선 기능은 물론 사회적 정서적 측면에서도 중요한 역할을 한다. 따라서 본 연구에서는 고해상도 항공영상과 KOMPSAT-2 위성영상의 이용하여 도심지역내 산림 영역의 수종 분류를 수행하기 위하여 고해상도의 항공영상과 위성영상의 NIR밴드의 영상재배열을 수행하였으며 NDVI 등 9개의 다양한 식생지수를 분산분석을 통해 임상단위로 수종을 구분하였다. 또한 산림청에서 제공하는 임상도를 이용하여 본 연구에서 구분된 수종과 비교 분석을 수행하였다. 이와 같은 식생분류 결과를 바탕으로 도시지역 내 식생관리를 위한 기초자료를 구축하고자 하였다.

• 한국조경학회지
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• 제28권4호
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• pp.75-90
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• 2000

This study suggests the methods of the assessment and creation of biotopes in small and medium sized cities, in Korea. For this purpose, Chonju city was selected to classify and asses the biotope types. Moreover, relevant legislations to conserve and enhance urban biotopes were examined. The results of this study are as follows: 1) There were two approaches to asses the potential of urban biotopes in medium-sized cities. One was the urban scale evaluation for urban green spaces and the other was the biotope scale evaluation for the classification and evaluation of biotopes. 2) The urban scale evaluation was developed through overlaping analysis of landuse and vegetation factors. This study also included the conception of watershed. In this conception, three watersheds in Chonju city were characterized. According to these characteristics, individual programs for conservation and enhancement of urban green space were suggested. 3) For the biotope scale evaluation, Selected site was inclusively mapped and field investigation actually was carried. There were total 9 types of bitopes. Especially landuse was appeared in various evaluation items were vegetation structure, area of green space, condition of vegetation and vegetation profile. Mt, Gonji and Dukjin park, Chonbuk national University and fields were evaluated highly I the potential. 4) The biotope programs were based on the results of assessment and physical characteristics of biotopes. The uniform and simple levels on vegetation must be modified with various levels of vegetation structure and vernacular plants. And the physical characteristics like Points, Corridors and Patches can be organized by the conception of biotope networking theory. 5) The proper legislative environment was the clue elements for the biotope programs. Until now, only five types of parks and two types of green space are defined and the minimum size of green space has been proposed by the law. So, it is necessary to enlarge the conception of green space in legislation and improve the quality of green space by amending the related regulations. This study has limitation because it was selected only in Chonju. Through the continuous studies, we need to apply this other small and medium sized cities, South Korea. Also the data collection and management of theme maps such as actual vegetation, landuse and a soil must be done preliminary.

• 대한원격탐사학회지
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• 제39권2호
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• pp.223-232
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• 2023

고해상도의 위성 영상을 이용하여 지표를 모니터링하기 위한 방법으로 분석 대상 객체의 색상을 이용하여 영상을 분류하는 방법이 널리 사용된다. 고해상도 위성영상에서는 도심 지역의 경우 건물, 도로 등과 같은 주요 객체들 이외에도 수목 등과 같은 식생 객체들도 빈번하게 나타난다. 도심 지역에 나타나는 식생 객체들의 색상은 건물, 도로, 그림자 등의 객체와 유사한 경우가 많으며, 이는 색상 정보에 기초하여 객체를 분류할 경우에 분류 성능이 저하되는 요인이 된다. 본 연구에서는 건물 등과 같은 다양한 색상을 가지는 객체뿐만 아니라 식생 객체도 정확하게 분류할 수 있는 기법을 제안한다. 제안하는 방법은 식생 객체 검출에 유용한 정규식생지수 영상을 RGB 영상과 함께 사용하고 객체 클래스를 서브 클래스로 세분화하여 분류한다. 서브 클래스 분류 결과를 융합한 후에 영상 분할 결과와 결합하여 최종 분류 결과를 생성한다. 차세대중형위성1호 영상을 이용한 실험에서 정규식생지수를 사용하지 않은 서브채널 분류 기법과 서브클래스 분류 기법의 overall accuracy가 각각 73.18%, 81.79%의 결과를 보인 반면, 정규식생지수와 서브클래스 분류를 함께 적용하여 제안한 방법은 overall accuracy가 87.42%의 우수한 성능을 보였다.

• 대한지리학회지
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• 제9권
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• pp.67-75
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• 1974

본 연구는 원격탐사 기법을 이용하여 북한 지역을 포함한 한반도 전지역을 대상으로 식생활력도(vegetation activity)의 시계열적 변화를 모니터링하고, 식생지수의 연중변화 특성을 이용하여 한반도의 식생 분포도를 작성하는데 그 목적이 있다. 1997년 4월부터 11월까지 8개월 동안 NOAA-14 위성에서 수신된 AVHRR 자료를 수집하여 정규 식생지수(Nomalized Difference Vegetation Index)를 구하고 이들을 MVC(Maximum Value Composite) 방법으로 조합하여 월별 NDVI 합성도를 작성하여 식생활력도의 시계열 변화를 고찰하였다. 또한 식물의 생장시기인 5월부터 10월까지의 NDVI를 무감독 분류하여 한반도의 식생분포 유형을 도시.나대지가 4.49%, 초지 4.49%, 경작지 27.54%, 활엽수림 25.61%, 침엽수림 38.22%로 나타났다.