• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.465-475
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• 2010

Spectral library is a database that archives spectral reflectance and related metadata of earth surface materials. Spectral library plays important role to assist analyzing several types of remote sensor data, to determine suitable wavelength band for detecting a certain material, and to classify hyperspectal image data. This paper describes the structure and content of a spectral library that is suitable for the environment of the Korea peninsula while existing spectral libraries have certain limitations to apply for surface materials covering the region. We designed a spectral library that includes vegetation and man-made materials indigenous to the region. The spectral library also includes spectra of mineral and rock, soil, liquid, and some man-made materials from existing spectral libraries. Newly augmented spectra of vegetation and man-made materials were obtained by spectral measurements in laboratory and field. The spectral library viewer was developed to increase efficiency of usage and searching.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.13-30
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• 1997

Recent improvements of satellite remote sensing sensors which are represented by hyperspectral imaging sensors and high spatial resolution sensors provide a large amount of data, typically several hundred megabytes per one scene. Moreover, increasing information exchange via internet and information super-highway requires the developments of more active service systems for processing and analysing of remote sensing data in order to provide value-added products. In this sense, an advanced satellite data processing system is being developed to achive high performance in computing speed and efficieney in processing a huge volume of data, and to make possible network computing and easy improving, upgrading and managing of systems. JAVA internet programming language provides several advantages for developing software such as object-oriented programming, multi-threading and robust memory managent. Using these features, a satellite data processing system named as GeoPixel has been developing using JAVA language. The GeoPixel adopted newly developed techniques including object-pipe connect method between each process and multi-threading structure. In other words, this system has characteristics such as independent operating platform and efficient data processing by handling a huge volume of remote sensing data with robustness. In the evaluation of data processing capability, the satisfactory results were shown in utilizing computer resources(CPU and Memory) and processing speeds.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.589-597
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• 2019

The purpose of this study was improve accuracy the IOPs inversion model(IOPs-IM) developed in 2016 for phycocyanin(PC) concentration estimation in the Nakdong River. Additionally, two optimum models were developed and evaluated with 2017 measurement field spectral data for the Geum River and the Yeongsan River. The used measurement data for IOPs-IM analyzation was randomly classified as training and verification materials at the ratio of 2:1 in all data sets. Using the training data set from 2015-2017, accuracy results of the IOPs-IM generally improved for the Nakdong River. The RMSE(Root Mean Square Error) decreased by 14 % compared to 2016. For the GeumRiver, the results of the IOPs-IM were suitable, except for some point results in 2016. Results of the IOPs-IM in the Yeongsan River followed the overall 1:1 line and MAE(Mean Absolute Error) was lower than other rivers. But the RMSE and MAE values were higher. As a result of applying the validation data to the IOPs-IM, the accuracy of the Nakdong River was reduced to RMSE 17.7 % and MRE 16.4 %, respectively compared with 2016. However, the MRE(Mean Relative Error) was estimated to be higher by 400 % in the Geum River, and the RMSE was more than 100 mg/㎥ of the Yeongsan River. Therefore, it is necessary to get the continuously data with various sections of each river for obtain objective and reliable results and the models should be improved.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.2
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• pp.103-108
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• 2023

Due to the recent impact of global warming, heavy rainfall and droughts have been occurring regardless of the season, affecting the growth of Italian ryegrass (IRG), a winter forage crop. Particularly, delayed sowing due to frequent heavy rainfall or autumn droughts leads to poor growth and reduced winter survival rates. Therefore, techniques to improve yield through additional sowing in spring have been implemented. In this study, the growth of IRG sown in Spring and Autumn was compared and analyzed using vegetation indices during the months of April and May. Spectral data was collected using an Unmanned Aerial Vehicle (UAV) equipped with a hyperspectral sensor, and the following vegetation indices were utilized: Normalized Difference Vegetation Index; NDVI, Normalized Difference Red Edge Index; NDRE (I), Chlorophyll Index, Red Green Ratio Index; RGRI, Enhanced Vegetation Index; EVI and Carotenoid Reflectance Index 1; CRI1. Indices related to chlorophyll concentration exhibited similar trends. RGRI of IRG sown in autumn increased during the experimental period, while IRG sown in spring showed a decreasing trend. The results of RGRI in IRG indicated differences in optical characteristics by sowing seasons compared to the other vegetation indices. Our findings showed that the timing of sowing influences the optical growth characteristics of crops by the results of various vegetation indices presented in this study. Further research, including the development of optimal vegetation indices related to IRG growth, is necessary in the future.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.187-187
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• 2022

Purple-discoloration of the uppermost leaves has been observed in some soybean cultivars in recent years. The purpose of this study was to characterize the novel phenotypic changes between the uppermost and middle leaves via multiple approaches. First, quantitative trait loci mapping was conducted to detect loci associated with the novel phenotype using 85 recombinant inbred lines (RILs) of the 'Daepung' × PI 96983 population. 180K SNP data, a major quantitative trait locus (QTL) was identified at around 60 cM of chromosome 6, which accounts for 56% of total phenotypic variance. The genomic interval is about ~700kb, and a list of annotated genes includes the T-gene which is known to control pubescence and seed coat color and is presumed to encode flavonoid 35-hydroxylase (F3'H). Based on Hyperspectral imaging, the reflectance at 528-554 nm wavelength band was extremely reduced in the uppermost leaves compared to the middle (green leaves), which is presumed die to the accumulation of anthocyanins. In addition, purple-discolored leaf tissues were observed and compared to normal leaves using a transmission electronic microscope (TEM). Base on observations of the cell organelles, the purple-discolored uppermost leaves had many pigments formed in the epidermal cells unlike the normal middle leaves, and the cell wall thickness was twice as thick in the discolored leaves. The thickness of the thylakoid layer in the chloroplast the number of starch grains, the size of starch all decreased in the discolored leaves, while the number of plastoglobule and mitochondria increased.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1523-1535
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• 2020

In order to produce crop information using remote sensing, we use classification and growth monitoring based on crop phenology. Therefore, time-series satellite images with a short period are required. However, there are limitations to acquiring time-series satellite data, so it is necessary to use fusion with other earth observation satellites. Before fusion of various satellite image data, it is necessary to overcome the inherent difference in radiometric characteristics of satellites. This study performed Korea Multi-Purpose Satellite-3 (KOMPSAT-3) cross calibration with Landsat-8 as the first step for fusion. Top of Atmosphere (TOA) Reflectance was compared by applying Spectral Band Adjustment Factor (SBAF) to each satellite using hyperspectral sensor band aggregation. As a result of cross calibration, KOMPSAT-3 and Landsat-8 satellites showed a difference in reflectance of less than 4% in Blue, Green, and Red bands, and 6% in NIR bands. KOMPSAT-3, without on-board calibrator, idicate lower radiometric stability compared to ladnsat-8. In the future, efforts are needed to produce normalized reflectance data through BRDF (Bidirectional reflectance distribution function) correction and SBAF application for spectral characteristics of agricultural land.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.167-175
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• 2019

Water color analysis allows non-destructive estimation of abundance of optically active water constituents in the water body. Recently, there have been increasing needs for light-weighted multispectral cameras that can be integrated with low altitude unmanned platforms such as drones, autonomous vehicles, and heli-kites, for the water color analysis by spectroradiometers. This study performs the preprocessing of the Micasense Rededge-M camera which recently receives a growing attention from the earth observation community for its handiness and applicability for local environment monitoring, and investigates the applicability of Rededge-M data for water color analysis. The Vignette correction and the band alignment were conducted for the radiometric image data from Rededge-M, and the sky, water, and solar radiation essential for the water color analysis, and the resultant remote sensing reflectance were validated with an independent hyperspectral instrument, TriOS RAMSES. The experiment shows that Rededge-M generally satisfies the basic performance criteria for water color analysis, although noticeable differences are observed in the blue (475 nm) and the near-infrared (840 nm) band compared with RAMSES.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1369-1382
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• 2018

As the number of multispectral satellites increases, it is expected that it will be possible to acquire and use images for periodically. However, there is a problem of data discrepancy due to different overpass time, period and spatial resolution. In particular, the difference in band bandwidths became different reflectance even for images taken at the same time and affect uncertainty in the analysis of vegetation activity such as vegetation index. The purpose of this study is to estimate the band adjustment factor according to the difference of bandwidth with other multispectral satellites for the application of KOMPSAT-3 satellite in agriculture field. The Spectral band adjustment factor (SBAF) were calculated using the hyperspectral satellite images acquired in the desert area. As a result of applying SBAF to the main crop area, the vegetation index showed a high agreement rate of relative percentage difference within 3% except for the Hapcheon area where the zenith angle was 25. For the estimation of SBAF, this study used only one set of images, which did not consider season and solar zenith angle of SBAF variation. Therefore, long-term analysis is necessary to solve SBAF uncertainty in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1817-1826
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• 2022

After the hydrogen fluoride leak in Gumi in 2012, the government has been systemizing the disaster management system, such as responding to and managing chemical accidents. In particular, the Ministry of the Interior and Safety (MOIS) is in charge of evacuation of residents following chemical accidents based on the Framework Act on Management of Disaster and Safety. In this study, an application plan was presented to support and utilize the decision-making support for evacuation of residents after a chemical accident using the chemical accident investigation equipment of the National Disaster Management Research Institute (NDMI). In the equipment operation system for scientific information collection due to chemical accidents, the roles and purpose of use of long/short distance measurement equipment were presented according to regular and emergency situations. Using the data acquired through long/short distance measurement equipment, it can be used as basic data for resident evacuation decision-making by monitoring whether chemicals are detected in an emergency and managing data on detected substances by company in a regular situation. As a result of measuring chemical substances in order to verify on-site usability by equipment only for the regular operation system, it was confirmed that real-time detection of chemical substances is possible with long distance measuring equipment. In addition, it was confirmed that it was necessary to check the measurable distance and range of the equipment in the future. In the case of short distance measurement equipment, hydrocarbon-based substances were mainly detected, and it was confirmed that it was measured at a higher level in Ulsan-Mipo National Industrial Complex than in Onsan National Industrial Complex. It is expected that it can be used as basic data to support decision-making in the event of chemical accidents through continuous data construction in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.