• Title/Summary/Keyword: 다중시기 영상분석

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A Study for Monitoring Soil Liquefaction Occurred by Earthquakes Using Soil Moisture Indices Derived from the Multi-temporal Landsat Satellite Imagery Acquired in Pohang, South Korea (다중시기 Landsat 위성영상으로부터 산출한 토양 수분 지수를 활용하여 지진 발생으로 인한 토양 액상화 모니터링에 관한 연구: 포항시를 사례로)

  • PARK, Insun;KIM, Kyoung-Seop;HAN, Byeong Cheol;CHOUNG, Yun-Jae;GU, Bon Yup;HAN, Jin Tae;KIM, Jongkwan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.1
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    • pp.126-137
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    • 2021
  • Recently, the number of damages on social infrastructure has increased due to natural disasters and the frequency of earthquake events that are higher than magnitude 3 has increased in South Korea. Liquefaction was found near the epicenter of a 5.4 magnitude earthquake that occurred in Pohang, South Korea, in 2017. To explore increases in soil moisture index due to soil liquefaction, changes in the remote exploration index by the land cover before and post-earthquake occurrence were analyzed using liquefaction feasibility index and multi-cyclical Landsat-8 satellite images. We found that the soil moisture index(SMI) in the liquefaction region immediately after the earthquake event increased significantly using the Normal Vegetation Index(NDVI) and Surface Temperature(LST).

A Study on Monitoring the Land Surface Temperature Changes Caused by Constructions of Rainwater Villages Using the Multi-temporal Landsat-8 Satellite Images (다중시기 Landsat-8 위성영상을 활용한 빗물마을 조성 사업에 의한 지표면 온도 변화 모니터링에 관한 연구)

  • CHOUNG, Yun-Jae;YU, Ki-Kwang;LEE, Yong Ik
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.1
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    • pp.30-40
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    • 2020
  • Monitoring the urban environmental changes caused by the urban regeneration project is necessary for evaluating the effect of the various types of urban regeneration projects that have been carried out in Seoul, South Korea. However, there is few available data and professional expert for evaluating the effect of these urban regeneration projects. This research evaluated the effect of the construction of rainwater village in Jangwi-dong area, constructed through the Seoul urban regeneration project, by utilizing the land surface temperatures derived from the multi-temporal Landsat-8 satellite images through the following steps. In the first step, the land surface temperature images were generated using the multispectral bands of the Landsat-8 satellite images. In the final step, the effect of constructing the rainwater villages was assessed by calculating the seasonal LST statistics for Jangwi-dong area, its neighbor area and entire Seoul area. The experimental results led the following conclusion: the construction of rainwater villages did not have the significant effect on the land surface temperature changes in Jangwi-dong area.

Comparison of Spatio-temporal Fusion Models of Multiple Satellite Images for Vegetation Monitoring (식생 모니터링을 위한 다중 위성영상의 시공간 융합 모델 비교)

  • Kim, Yeseul;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.35 no.6_3
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    • pp.1209-1219
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    • 2019
  • For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

Analysis of UAV-based Multispectral Reflectance Variability for Agriculture Monitoring (농업관측을 위한 다중분광 무인기 반사율 변동성 분석)

  • Ahn, Ho-yong;Na, Sang-il;Park, Chan-won;Hong, Suk-young;So, Kyu-ho;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1379-1391
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    • 2020
  • UAV in the agricultural application are capable of collecting ultra-high resolution image. It is possible to obtain timeliness images for phenological phases of the crop. However, the UAV uses a variety of sensors and multi-temporal images according to the environment. Therefore, it is essential to use normalized image data for time series image application for crop monitoring. This study analyzed the variability of UAV reflectance and vegetation index according to Aviation Image Making Environment to utilize the UAV multispectral image for agricultural monitoring time series. The variability of the reflectance according to environmental factors such as altitude, direction, time, and cloud was very large, ranging from 8% to 11%, but the vegetation index variability was stable, ranging from 1% to 5%. This phenomenon is believed to have various causes such as the characteristics of the UAV multispectral sensor and the normalization of the post-processing program. In order to utilize the time series of unmanned aerial vehicles, it is recommended to use the same ratio function as the vegetation index, and it is recommended to minimize the variability of time series images by setting the same time, altitude and direction as possible.

Development of Monitoring System for Forests Type Based on Web (Web 기반의 산림형태 모니터링시스템 개발)

  • Kim, Jin-Soo;Seo, Dong-Ju
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.2
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    • pp.321-327
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    • 2008
  • In recently, researches which appling satellite image are introduced target to the forest area. Especially, it is satellite image analysis's advantage that collecting information of terrain at the direct accesses are dangerous and impassible area. But, the studies approaching to a inflectional paradigm of forests and change detection system for the distinguished forests type are leaves much to be desired. In this study, therefore, change of forests type was analyzed using Landsat TM satellite image which have multi-spectral bands. Furthermore, change detection system for forests type was constructed on web for the periodical monitoring.

A Study on Object-Based Image Analysis Methods for Land Cover Classification in Agricultural Areas (농촌지역 토지피복분류를 위한 객체기반 영상분석기법 연구)

  • Kim, Hyun-Ok;Yeom, Jong-Min
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.4
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    • pp.26-41
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    • 2012
  • It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.

Analysing of Forest Types in Chungnam Coastal area Using Multi-Temporal Satellite imagery and ASTER DEM Data (다중시기 위성영상과 ASTER DEM자료를 이용한 충남해안지역의 임상 변화 분석)

  • KIM, Jang-soo;JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.19 no.1
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    • pp.69-81
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    • 2012
  • This study analyzed the relationship between the geomorphic factor and changes in forest types of the Chungnam coastal area using ASTER DEM and multi-temporal satellite imagery. The results showed that in case coniferous forests vary by altitudinal segments, reduction rate continuously increased up to 500m, but dropped upon exceeding 550 meters. Next, the variation rate of mixed forests by altitudinal segments decreased from less than 50m. However, the variation rate of mixed forests increased from more than 50m to 700m, but dropped upon exceeding 700m. Lastly, the variation rate of deciduous forests according to altitudinal segments increased at all altitudes. A sharp increase was found in segments of more than 550 meters. With regard to the changes in the distribution area of forest types according to slope aspects, coniferous forests showed a reduction in all slope aspects. The reduction rate was especially higher in northern, northwestern, western and northeastern aspects. Mixed forests manifested a high growth rate in northwestern, northern and western aspects, but slightly decreased in eastern and southeastern aspects. In addition, deciduous forests increased in all slope aspects, but the growth rate was especially high in eastern, southeastern, northeastern and southern aspects.

Analysis of Relationships between Features Extracted from SAR Data and Land-cover Classes (SAR 자료에서 추출한 특징들과 토지 피복 항목 사이의 연관성 분석)

  • Park, No-Wook;Chi, Kwang-Hoon;Lee, Hoon-Yol
    • Korean Journal of Remote Sensing
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    • v.23 no.4
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    • pp.257-272
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    • 2007
  • This paper analyzed relationships between various features from SAR data with multiple acquisition dates and mode (frequency, polarization and incidence angles), and land-cover classes. Two typical types of features were extracted by considering acquisition conditions of currently available SAR data. First, coherence, temporal variability and principal component transform-based features were extracted from multi-temporal and single mode SAR data. C-band ERS-1/2, ENVISAT ASAR and Radarsat-1, and L-band JERS-1 SAR data were used for those features and different characteristics of different SAR sensor data were discussed in terms of land-cover discrimination capability. Overall, tandem coherence showed the best discrimination capability among various features. Long-term coherence from C-band SAR data provided a useful information on the discrimination of urban areas from other classes. Paddy fields showed the highest temporal variability values in all SAR sensor data. Features from principal component transform contained particular information relevant to specific land-cover class. As features for multiple mode SAR data acquired at similar dates, polarization ratio and multi-channel variability were also considered. VH/VV polarization ratio was a useful feature for the discrimination of forest and dry fields in which the distributions of coherence and temporal variability were significantly overlapped. It would be expected that the case study results could be useful information on improvement of classification accuracy in land-cover classification with SAR data, provided that the main findings of this paper would be confirmed by extensive case studies based on multi-temporal SAR data with various modes and ground-based SAR experiments.

Development of Change Detection Technique Using Time Seriate Remotely Sensed Satellite Images with User Friendly GIS Interface (사용자 중심적 GIS 인터페이스를 이용한 시계열적 원격탐사 영상의 변화탐지 기법의 개발)

  • 양인태;한성만;윤희천;김흥규
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.2
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    • pp.151-159
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    • 2004
  • The diversity, expansion of human activity and rapid urbanization make modem society to faced with problems like damage of nature and drain of natural resources. Under these circumstances rapid and accurate change detection techniques, which can detect wide range utilization changes, are needed for efficient management and utilization plan of national territory. In this study to perform change detection from remote sensing images, space analysis technique contained in Geographic Information System is applied. And from this technique, the software. that can execute new change detection algorithm, query, inquiry and analysis, is produced. This software is on the basis of graphic user interface and has many functions such as format conversion, grid calculation, statistical processing, display and reference. In this study, simultaneously change detection for multi-temporal satellite images can be performed and integrated one change image about four different periods was produced. Further more software user can acquire land cover change information for an specific area through querying and questioning about yearly changes. Finally making of every application module for change detection into one window based visual basic program, can be produced user convenience and automatic performances.

Analytic Techniques for Change Detection using Landsat (Landast 영상을 이용한 변화탐지 분석 기법 연구)

  • Choi, Chul-Uong;Lee, Chang-Hun;Suh, Yong-Cheol;Kim, Ji-Yong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.3
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    • pp.13-20
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    • 2009
  • Techniques for change detection using satellite images enable efficient detection of natural and artificial changes in use of land through multi-phase images. As for change detection, different results are made based on methods of calibration of satellite images, types of input data, and techniques in change analysis. Thus, an analytic technique that is appropriate to objectives of a study shall be applied as results are different based on diverse conditions even when an identical satellite and an identical image are used for change detection. In this study, Normalized Difference Vegetation Index (NDVI) and Principal Component Analysis (PCA) were conducted after geometric calibration of satellite images which went through absolute and relative radiometric calibrations and change detection analysis was conducted using Image Difference (ID) and Image Rationing (IR). As a result, ID-NDVI showed excellent accuracy in change detection related to vegetation. ID-PCA showed 90% of accuracy in all areas. IR-NDVI had 90% of accuracy while it was 70% and below as for paddies and dry fields${\rightarrow}$grassland. IR-PCA had excellent change detection over all areas.

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