• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.235-244
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• 2004

This study focuses on the assessment for proposed algorithm to discriminate cloudy pixels from snowy pixels through use of visible, near infrared, and short wave infrared channel data in VEGETATION-1 sensor embarked on SPOT-4 satellite. Traditional threshold algorithms for cloud and snow masks did not show very good accuracy. Instead of these independent masking procedures, K-Means clustering scheme is employed for cloud/snow discrimination in this study. The pixels used in clustering were selected through an integration of two threshold algorithms, which group ensemble the snow and cloud pixels. This may give a opportunity to simplify the clustering procedure and to improve the accuracy as compared with full image clustering. This paper also compared the results with threshold methods of snow cover and clouds, and assesses discrimination capability in VEGETATION channels. The quality of the cloud and snow mask even more improved when present algorithm is implemented. The discrimination errors were considerably reduced by 19.4% and 9.7% for cloud mask and snow mask as compared with traditional methods, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.201-210
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• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.79-90
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• 2013

The altitude range of habitats in which Fairy Pitta inhabited in 1960s is different from the present in Jeju Island. We studied on the habitat environment to understand the causes of difference through the comparison of satellite image data(Landsat) between 1975 and 2002, the literature review in relation to habitats, vegetations, and forest landscapes. The area of below 600m asl.(above sea level) where is mainly Fairy Pitta inhabited at the present with a lot of forests, was massive pasture with small isolated forests nearby valley. The forests were broad-leaved evergreen forests, and second forests with poor condition in the size and forest structure. The forests around 700m asl. were also second forests with approximately 3m height trees. The forests from 800m to 1300m asl. were also disturbed by mushroom cultivation by local people. The authors believe that Fairy Pitta could not inhabited in the area above 1300m because of the poor forest conditions in the size and structure in which consist of Ilex crenata, Rhododendron mucronulatum var. ciliatum and coppice forests. Therefore it might be possible that the best forests for the Fairy Pitta habitat were located in the area of 1,000m to 1,300m above sea level in 1960s. Compared to present habitats, forests at 100m up to 800m above sea level, the authors believe that the size of habitats were smaller with less population of Fairy Pitta. Since 1960s the forest landscape of Jeju Island has been improved successfully, and because of that the population of Fairy Pitta also has been increased. To protect the Fairy Pitta and habitats in Jeju Island, it is suggested that sustainable forest management focusing on the species composition and stand structure maintain or enhance the biodiversity.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.4 s.31
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• pp.3-12
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• 2004

It is necessary to manage water resources in rural areas in order to achieve proper development of new water resources, sustainable usage and reasonable distribution. This paper aims to analyze multi-temporal Landsat-7 ETM+data for soil moisture that is essential for crops in Ahnsung area. The ETM data was also fused with KOMPSAT-1 images in order to be used as backdrop watershed maps at first. Multi-temporal Images showed also the characteristics of soil moisture distribution. Images taken in April showed that rice paddy had as low reflectance as artificial features. Compared with April scenes, those taken in Hay and June showed wetness index increased in the rice paddies. The mountainous areas have almost constant moisture index, so the difference between the dates was very low while reservoirs and livers had dramatic changes. We can calculate total potential areas of distribution of moisture content within the basin and estimate the areas being sensitive to drought. Finally we can point out the sites of small rice paddies lack of water and visualize their distribution within the same basin. It can be said that multi-temporal Landsat-7 ETM+ and KOMPSAT data can be used to show broad drought with quick and simple analysis. Drought sensitiveness maps may enable the decision makers on rural water to evaluate the risk of drought and to measure mitigation, accompanied with proper data on the hydrological and climatic drought.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.597-604
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• 2001

The objective of the paper was to estimate the changes in acreages of tidal flats after the seawall construction at the Asan Bay and the Chunsu Bay from topographic maps, hydrographic charts, and Landsat TM images. The tidal floats from topographic maps published in one year differ significantly from that in the other, which appears to be attributed to the tide levels at the time of photographing. The hydrographic charts showed that tidal flats increase at rates of 22.3 ha/yr at the Asan Bay and 56.6 ha/yr at the Chunsu Bay after the dike construction. Applying the ISODATA method of unsupervised classifications for the Landsat TM images, the tidal flats were identified, and the resulting acreages for each image estimated. The resulting tidal flats increased at the rates of 21.3 ha/yr at the Asan Bay and 47.3 ha/yr at the Chunsu Bay during twelve years after the dike construction. It was found that the rates of the annual increases from the two data are very close and the differences result from the coastal lines at the charts and the TM images.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.162-175
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• 2018

The purpose of this study was to analyze the surface temperature of surface fabrics using UAV TIR images, to mitigate problems in the thermal environment of urban areas. Surface temperature values derived from UAV images were compared with those measured in-situ during the similar period as when the images were taken. The difference in the in-situ measured and UAV image derived surface temperatures is the highest for gray colored concrete roof fabrics, at $17^{\circ}C$, and urethane fabrics show the lowest difference, at $0.3^{\circ}C$. The experiment power of the scatter plot of in-situ measured and UAV image derived surface temperatures was 63.75%, indicating that the correlation between the two is high. The surface fabrics with high temperature are metal roofs($48.9^{\circ}C$), urethane($43.4^{\circ}C$), and gray colored concrete roofs($42.9^{\circ}C$), and those with low temperature are barren land($30.2^{\circ}C$), area with trees and lawns($30.2^{\circ}C$), and white colored concrete roofs($34.9^{\circ}C$). These results show that accurate analysis of the thermal characteristics of surface fabrics is possible using UAV images. In future, it will be necessary to increase the usability of UAV images via comparison with in-situ data and linkage to satellite imagery.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.191-202
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• 2012

A high resolution satellite imagery such as KOMPSAT-2 includes a material containing rational polynomial coefficient (RPC) for three-dimensional geopositioning. However, image geometries which are calculated from the RPC must have inevitable systematic errors. Thus, it is necessary to correct systematic errors of the RPC using several ground control points (GCPs). In this paper, we propose an efficient method for automatic correction of image geometries using tie points of a stereo pair and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) without GCPs. This method includes four steps: 1) tie points extraction, 2) determination of the ground coordinates of the tie points, 3) refinement of the ground coordinates using SRTM DEM, and 4) RPC adjustment model parameter estimation. We validates the performance of the proposed method using KOMPSAT-2 stereo pair. The root mean square errors (RMSE) achieved from check points (CPs) were about 3.55 m, 9.70 m and 3.58 m in X, Y;and Z directions. This means that we can automatically correct the systematic error of RPC using SRTM DEM.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.637-647
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• 2019

The detection of crop stress is an important issue for the accurate assessment of yield decline. The photochemical reflectance index (PRI) was developed as a remotely sensed indicator of light use efficiency (LUE). The PRI has been tested in crop stress detection and a number of studies demonstrated the feasibility of using it. However, only few studies have focused on the use of PRI from remote sensing imagery. The monitoring of PRI using drone and satellite is made difficult by the low spectral resolution image captures. In order to estimate PRI from multispectral sensor, we propose a band fusion method using adjacent bands. The method is applied to the drone-based hyperspectral and multispectral imagery and estimated PRI explain 79% of the original PRI. And time series analyses showed that two PRI data (drone-based and SRS sensor) had very similar temporal variations. From these results, PRI from multispectral imagery using band fusion can be used as a new method for evaluation of crop stress.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.361-370
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• 2020

Long-term observation of the life cycle of plants allows the identification of critical signals of the effects of climate change on plants. Indeed, plant phenology is the simplest approach to detect climate change. Observation of seasonal changes in plants using digital repeat imaging helps in overcoming the limitations of both traditional methods and satellite remote sensing. In this study, we demonstrate the utility of camera-based repeat digital imaging in this context. We observed the biological events of plants and quantified their phenophases in the northern temperate type deciduous broadleaf forest of Jeombong Mountain. This study aimed to identify trends in seasonal characteristics of Quercus mongolica (deciduous broadleaf forest) and Pinus densiflora (evergreen coniferous forest). The vegetation index, green chromatic coordinate (GCC), was calculated from the RGB channel image data. The magnitude of the GCC amplitude was smaller in the evergreen coniferous forest than in the deciduous forest. The slope of the GCC (increased in spring and decreased in autumn) was moderate in the evergreen coniferous forest compared with that in the deciduous forest. In the pine forest, the beginning of growth occurred earlier than that in the red oak forest, whereas the end of growth was later. Verification of the accuracy of the phenophases showed high accuracy with root-mean-square error (RMSE) values of 0.008 (region of interest [ROI]1) and 0.006 (ROI3). These results reflect the tendency of the GCC trajectory in a northern temperate type deciduous broadleaf forest. Based on the results, we propose that repeat imaging using digital cameras will be useful for the observation of phenophases.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.