• Korean Journal of Remote Sensing
• /
• v.11 no.2
• /
• pp.59-73
• /
• 1995

The study is focused on the analysis of geomorphological environment changes of alluvial bar in lower Kum river using satellite-based multitemporal/multisensor data. Landsat datas for environment changes analysis consists of Landset MSS(2 scenes) and Landset TM(7 scenes) acquired from 1979 to 1994. This study is to develop the analysis techniques for the environment change detection of using ratio, classification, false color composite etc, of Landsat data especially useful to the geomorphological study of tidal flats and river channels. The results of this study can be summarized as follows : 1. The lower Kum River alluvial bar have had rapid geomorphological changes after the construction of the temporary dam to block the river flowing in 1983. The most alluvial bar located in the river has both bankway growth, especially the allurival bar in the Lower Kum River had grown between 1983 to 1990. 2. After construction of the estuarine barrage, no remarkable geomorphological changes have been found in Kum River area but the growth and formation of new underwater bar has continued. The enormous materials was needed for the growth and formations of new underwater barrier oslands and bar would be supplied from the sea bottom and river sediment to diminish of stream velocity after construction of the estuarine barrage.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.426-428
• /
• 2003

Optical and microwave remote sensing data have been widely used in land cover and land use classification. Thanks to the spectral absorption characteristics of ground object in visible and near infrared region, optical data enables to extract different land cover types according to their material composition like water body, vegetation cover or bare land. On the other hand, microwave sensor receives backscatter radiance which contains information on surface roughness, object density and their 3-D structure that are very important complementary information to interpret land use and land cover. Separate use of these data have brought many successful results in practice. However, the accuracy of the land use / land cover established by this methodology still has some problems. One of the way to improve accuracy of the land use / land cover classification is just combination of both optical and microwave data in analysis. In this paper for the research, the author used LANDSAT TM scene 127/45 acquired on October 21, 1992, JERS-1 SAR scene 119/265 acquired on October 27, 1992 and aerial photographs taken on October 21, 1992. The study area has been selected in Hanoi City and surrounding area, Vietnam. This is a flat agricultural area with various land use types as water rice, secondary crops like maize, cassava, vegetables cultivation as cucumber, tomato etc. mixed with human settlement and some manufacture facilities as brick and ceramic factories. The use of only optical or microwave data could result in misclassification among some land use features as settlement and vegetables cultivation using frame stages. By combination of multitemporal JERS-1 SAR and TM data these errors have been eliminated so that accuracy of the final land use / land cover map has been improved. The paper describes a methodology for data combination and presents results achieved by the proposed approach.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1083-1094
• /
• 2021

In order to monitor nuclear activity in inaccessible areas, it is necessary to establish a methodology to analyze changesin nuclear activity-related objects using high-resolution satellite images. However, traditional object detection and change detection techniques using satellite images have difficulties in applying detection results to various fields because effects of seasons and weather at the time of image acquisition. Therefore, in this paper, an object of interest was detected in a satellite image using a deep learning model, and object changes in the satellite image were analyzed based on object detection results. An initial training of the deep learning model was performed using an open dataset for object detection, and additional training dataset for the region of interest were generated and applied to transfer learning. After detecting objects by multitemporal and multisensory satellite images, we tried to detect changes in objects in the images by using them. In the experiments, it was confirmed that the object detection results of various satellite images can be directly used for change detection for nuclear activity-related monitoring in inaccessible areas.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.37-37
• /
• 2003

Rice is one of the most important crop in the world and is a major export of Thailand. Optical sensors are not useful for rice monitoring, because most cultivated areas are often obscured by cloud during the growing period, especially in South East Asia. Spaceborne Synthetic Aperture Radar (SAR) such as RADARSAT, can see through regardless of weather condition which make it possible to monitor rice growth and to retrieve rice acreage, using the unique temporal signature of rice fields. This paper presents the result of a study of examining the backscatter behavior of rice using multi-temporal RADARSAT dataset. Ground measurements of paddy parameters and water and soil condition were collected. The ground truth information was also used to identify mature rice crops, orchard, road, residence, and aquaculture ponds. Land use class distributions from the RADARSAT image were analyzed. Comparison of the mean DB of each land use class indicated significant differences. Schematic representation of temporal backscatter of rice crop were plotted. Based on the study carried out in Pathum Thani Province test site, the results showed variation of sigma naught from first tillering vegatative phase until ripenning phase. It is suggested that at least, three radar data acquisitions taken at 3 stages of rice growth circle namely; those are at the beginning of rice growth when the field is still covered with water, in the ear differentiation period, and at the beginning of the harvest season, are required for rice monitoring. This pilot project was an experimental one aiming at future operational rice monitoring and potential yield predicttion.

• Korean Journal of Remote Sensing
• /
• v.18 no.2
• /
• pp.117-125
• /
• 2002

Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. Using an adaptive reconstruction system, dynamic compositing approach was developed to recover missing/bad observations. The reconstruction method incorporates temporal variation in physical properties of targets and anisotropic spatial optical properties into image processing. The adaptive system performs the dynamic compositing by obtaining a composite image as a weighted sum of the observed value and the value predicted according to local temporal trend. The proposed system was applied to the sequence of NDVI images of AVHRR observed on the Korean Peninsula from 1999 year to 2000 year. The experiment shows that the reconstructed series can be used as an estimated series with complete data for the observations including bad/missing values. Additionally, the gradient image, which represents the amount of temporal change at the corresponding time, was generated by the proposed system. It shows more clearly temporal variation than the data image series.

• Korean Journal of Remote Sensing
• /
• v.4 no.1
• /
• pp.31-40
• /
• 1988

Low-cost microcomputer systems can be assembled which possess computing power, color display, memory, and storage capacity approximately equal to graphic workstactions. A low-cost, flexible, and user-friendly IBM/PC/XT/AT based image processing system has been developed and named as KMIPS(KAIST (Korea Advanced Institute of Science & Technology) Map and Image Processing Station). It can be easily utilized by the resource managers who are not computer specialists. This system can: * directly access Landsat MSS and TM, SPOT, NOAA AVHRR, MOS-1 satellite imagery and other imagery from different sources via magnetic tape drive connected with IBM/PC; * extract image up to 1024 line by 1024 column and display it up to 480 line by 672 column with 512 colors simultaneously available; * digitize photographs using a frame grabber subsystem(512 by 512 picture elements); * perform a variety of image analyses, GIS and terrain analyses, and display functions; and * generate map and hard copies to the various scales. All raster data input to the microcomputer system is geographically referenced to the topographic map series in any rater cell size selected by the user. This map oriented, georeferenced approach of this system enables user to create a very accurately registered(.+-.1 picture element), multivariable, multitemporal data sets which can be subsequently subsequently subjected to various analyses and display functions.

• Journal of Korean Society of Forest Science
• /
• v.83 no.4
• /
• pp.441-449
• /
• 1994

The two reflective channels(red and near infrared spectrum) of advanced very high resolution radiometer(AVHRR) data were used to classify primary vegetation cover types in the Korean Peninsula. From the NOAA-11 satellite data archive of 1991, 27 daytime scenes of relatively minimum cloud coverage were obtained. After the initial radiometric calibration, normalized difference vegetation index(NDVI) was calculated for each of the 27 data sets. Four or five daily NDVI data were then overlaid for each of the six months starting from February to November and the maximum value of NDVI was retained for every pixel location to make a monthly composite. The six bands of monthly NDVI composite were nearly cloud free and used for the computer classification of vegetation cover. Based on the temporal signatures of different vegetation cover types, which were generated by an unsupervised block clustering algorithm, every pixel was classified into one of the six cover type categories. The classification result was evaluated by both qualitative interpretation and quantitative comparison with existing forest statistics. Considering frequent data acquisition, low data cost and volume, and large area coverage, it is believed that AVHRR data are effective for vegetation cover type mapping at regional scale.

• Journal of Ecology and Environment
• /
• v.47 no.2
• /
• pp.49-62
• /
• 2023

Background: Over the past three decades, gradual eustatic sea-level rise has been considered a primary exogenous factor in the increased frequency of flooding and biological changes in several salt marshes. Under this paradigm, the potential importance of short-term events, such as ocean storminess, in coastal hydrology and ecology is underrepresented in the literature. In this study, a simulation was developed to evaluate the influence of wind waves driven by atmospheric oscillations on sedimentary and vegetation dynamics at the Skallingen salt marsh in southwestern Denmark. The model was built based on long-term data of mean sea level, sediment accretion, and plant species composition collected at the Skallingen salt marsh from 1933-2006. In the model, the submergence frequency (number yr^-1) was estimated as a combined function of wind-driven high water level (HWL) events (> 80 cm Danish Ordnance Datum) affected by the North Atlantic Oscillation (NAO) and changes in surface elevation (cm yr^-1). Vegetation dynamics were represented as transitions between successional stages controlled by flooding effects. Two types of simulations were performed: (1) baseline modeling, which assumed no effect of wind-driven sea-level change, and (2) experimental modeling, which considered both normal tidal activity and wind-driven sea-level change. Results: Experimental modeling successfully represented the patterns of vegetation change observed in the field. It realistically simulated a retarded or retrogressive successional state dominated by early- to mid-successional species, despite a continuous increase in surface elevation at Skallingen. This situation is believed to be caused by an increase in extreme HWL events that cannot occur without meteorological ocean storms. In contrast, baseline modeling showed progressive succession towards the predominance of late-successional species, which was not the then-current state in the marsh. Conclusions: These findings support the hypothesis that variations in the NAO index toward its positive phase have increased storminess and wind tides on the North Sea surface (especially since the 1980s). This led to an increased frequency and duration of submergence and delayed ecological succession. Researchers should therefore employ a multitemporal perspective, recognizing the importance of short-term sea-level changes nested within long-term gradual trends.

• Journal of the Korean Geographical Society
• /
• v.38 no.4
• /
• pp.630-639
• /
• 2003

This study aims to analysis the distribution and change of cropland and forest, the Onseong, Saebyeol, and Eundeok counties on the lower reach of Duman(Tumen) river, northeast Korea, using 1992 year Landsat TM data, 2000 year Landsat ETM data, and digital terrain elevation data(DTED). Land cover and land use of the study areas are classified into cropland, forest, village, and water body, using the supervised classification method including 1:50,000 DTED analysis, image band composition, and principal component analysis(PCA). Results of quantitative analysis present that each growth rate of cropland of Onseong and Eundeok are 22.8% and 14.7% corresponding to decreasing rates of forest, 8% and 13.6% during 8 years from 1992 to 2000. In Onseong, Saebyeol, and Eundeok, each values of mean elevations and slope gradients increased to 192m, 95m, and 91m from 157m, 85m, and 78m, and to 6.6$^{\circ}$, 3.0$^{\circ}$, and 4.4$^{\circ}$ from 5.2$^{\circ}$, 2.5$^{\circ}$, and 3.0$^{\circ}$. Especially, in case of newly developed cropland, the values of mean elevation and mean gradient have 225m, 122m, and 127m, and 9.4$^{\circ}$, 5.1$^{\circ}$, and 8.0$^{\circ}$, in above three regions. These new croplands were developing along to deeper valleys and toward lower hill and mountain slope up to knickpoint zone of gradient change. Deforested lands for cropland have formed irregular pattern of patch-type, and become sources for the sheet erosion, rilling and gulleying in mountain slope and sedimentation in local river channel. Though there were no field checking, analysis using landsat images and GIS mapping can help understand actual environmental problems relating to cropland development of mountain slope in North Korea.

• Journal of Korean Society of Forest Science
• /
• v.88 no.3
• /
• pp.352-363
• /
• 1999

It has been rare to obtain reliable information related to the size of forest land in North Korea. Several sources of forest statistics, ranging from the first map of forest distribution in Korean Peninsula produced in 1910 to official data reported by the North Korea Government in 1997, were gathered and analyzed to define the characteristics of forest cover changes over years. In addition, Landsat satellite data obtained from 1973 to 1993 were processed for the two study areas of the provinces of Pyungyang and Heasan, where the topography and land use pattern are significantly different each other. Using three sets of multitemporal Landsat imagery, land cover ma-ps were produced by computer classification. Although forest statistics reported before 1990 are somewhat inconsistent, they mere gradually decreasing over years. The estimates of 1991 satellite data and the recent statistics reported in 1998 shows very steep decline in forest lands as compared to the ones before 1990. The abrupt decrease of forest lands after 1990 was also found on the detailed analysis of Landsat data for the two study areas of Pyungyang and Heasan. The rapid decline of forest lands may have something to do with the poor economic situation of the country and the continuing natural disasters of severe flooding and drought. Unstocked forest, which was not classified into forest land, was a very distinct and pervasive land cover type that can be easily observed on satellite imagery. Since unstocked forest land in North Korea may be a critical factor for degrading environmental quality as well as for the continuing natural disasters, further analysis is necessary to define the exact extent and the physical characteristics of the cover type.