• Atmosphere
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• v.21 no.4
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• pp.337-347
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• 2011

In this paper, we developed a detection and correction method of noisy pixels embedded in the time series of normalized difference vegetation index (NDVI) data based on the spatio-temporal continuity of vegetation conditions. For the application of the method, 25-year (1982-2006) GIMMS (Global Inventory Modeling and Mapping Study) NDVI dataset over the Korean peninsula were used. The spatial resolution and temporal frequency of this dataset are $8{\times}8km^2$ and 15-day, respectively. Also the land cover map over East Asia is used. The noisy pixels are detected by the temporal continuity check with the reference values and dynamic threshold values according to season and location. In general, the number of noisy pixels are especially larger during summer than other seasons. And the detected noisy pixels are corrected by the iterative method until the noisy pixels are completely corrected. At first, the noisy pixels are replaced by the arithmetic weighted mean of two adjacent NDVIs when the two NDVI are normal. After that the remnant noisy pixels are corrected by the weighted average of NDVI of the same land cover according to the distance. After correction, the NDVI values and their variances are increased and decreased by 5% and 50%, respectively. Comparing to the other correction method, this correction method shows a better result especially when the noisy pixels are occurred more than 2 times consistently and the temporal change rates of NDVI are very high. It means that the correction method developed in this study is superior in the reconstruction of maximum NDVI and NDVI at the starting and falling season.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.297-304
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• 2015

The change detection algorithms, based on remotely sensed satellite imagery, can be applied to various applications, such as the hazard/disaster analysis and the land monitoring. However, unchanged areas sometimes detected as the changed areas due to various errors in relief displacements and noise pixels, included in the original multi-temporal dataset at the application of unsupervised change detection algorithm. In this research, the object-based changed detection for the high-spatial resolution satellite images is applied by using the IR-MAD (Iteratively Reweighted- Multivariate Alteration Detection), which is one of those representative change detection algorithms. In additionally, we tried to increase the accuracy of change detection results with using the additional information, based on the cross-sharpening method. In the experiment, we used the KOMPSAT-2 satellite sensor, and resulted in the object-based IR-MAD algorithm, representing higher changed detection accuracy than that by the pixel-based IR-MAD. Also, the object-based IR-MAD, focused on cross-sharpened images, increased in accuracy of changed detection, compared to the original object-based IR-MAD. Through these experiments, we could conclude that the land monitoring and the change detection with the high-spatial-resolution satellite imagery can be accomplished efficiency by using the object-based IR-MAD algorithm.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.192-195
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• 2004

Products of gridded surface wind and windstress vectors over the world ocean have been constructed by satellite scatterometer data with highly temporal and spatial resolutions. Even if the ADEOS-II/SeaWinds has supplied surface wind data only for short duration in Apr. to Oct. 2003 to us, it permits us to construct a product with higher resolution together with the Qscat/SeaWinds. In addition to our basic product with its resolution of $1^{\circ}\times1^{\circ}$ in space and daily in time, we try to construct products with $1/2^{\circ}\times1/2^{\circ}$ and semi- and quarter-daily resolution. These products are validated by inter-comparison with in-situ data (TAO and NDBC buoys), and also compared with numerical weather prediction(NWP) ones (NCEP reanalysis). Result reveals that our product has higher reliability in the study area than the NCEP's. For the open ocean regions in the middle and high latitudes where there are no in-situ data, we find that there are clear differences between them. Especially in the southern westerly region of 400-600S, the' wind-stress magnitudes by the NCEP are significantly larger than the others, suggesting that they are overestimated. We also calculate wind-stress curl field that is an important factor for ocean dynamics and focus its spatial character in the northwestern Pacific around Japan. Positive curl areas are found to cover from southwest to northeast in our focus region and almost correspond to the Kuroshio path. It is suggested that the vorticity field in the lower atmosphere is related to the upper oceanic one, and thus an aspect of air-sea interaction process.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.83-94
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• 2003

All the urban planning process require land use informations, which should be obtained after through intensive investigation and accurate analysis about the past and current situations and conditions of a city. Until now, the generation of land use informations from remotely sensed imagery has had many limitation because of its spatial resolution. It is now expected that the availability of high resolution satellite imagery whose spatial resolution less than 10m will reduce these limitations. For the purpose of urban growth monitoring we must first establish a urban land use classification nomenclature. In this study, we would like to establish a land use nomenclature for land use classification using remotely sensed data, especially using KOMPSAT EOC imagery.

• Journal of Korea Water Resources Association
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• v.50 no.6
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• pp.429-440
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• 2017

A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images were analyzed to detect the geographical changes in four different tidal flats in the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from the satellite images, which were used as the input of the temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps extracted from the KOMPSAT images indicate that these multispectral high-resolution satellite data is highly applicable to generate good quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the tidal flat area of Gyeonggi and Jeollabuk provinces was estimated to have changed due to tidal effects, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in Jeollanam province revealed that the social and environmental policies can effectively protect coastal wetlands from degradation. Therefore, monitoring for wetland change using high resolution KOMPSAT is expected to be useful to coastal environment management and policy making.

• BMB Reports
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• v.53 no.8
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• pp.393-399
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• 2020

Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.89-98
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• 2018

Satellite data have attracted attention on research such as natural disaster and climate changes because satellite data is very advantageous for observing a wide range of variability. However, there are still limited spatial and temporal resolutions in satellite data. To overcome these limitations, fusion of various sensors and combination of primary products are used. In this study, surface temperature data of 500 m spatial resolution was produced by fusion of GOCI and MI data of COMS. Also these LST are used with NDVI for estimating TVDI. Soil moisture condition of the Korean peninsula was evaluated by these TVDI and it was compared with SSMI derived from ASCAT surface soil moisture data. As a result, COMS TVDI and ASCAT SSMI showed similar spatial distribution and suggested the possibility of observing the soil moisture using COMS. Therefore, the TVDI estimations can be used as a basis for estimating the high resolution soil moisture, and the application of the COMS can be expanded for various studies.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.81-90
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• 2002

Remote Sensing has been very useful tool in monitoring of cities and updating of GIS database compare to traditional methods due to its benefit; wide range covering on low cost and advanced data collection. However it had come to a limited method in limited researches because of its relatively poor spatial resolution in scanning. Recently launched satellites are able to produce improved imageries, and new commercial services have been commenced for the use of general public with higher spatial resolution up to $1m{\times}1m$. This study tackled a potential use of these improved satellite imageries in urban planning based on the Multi-temporal satellite imagery with particular reference to monitoring on urban areas, for example urbanization and its expanding. i) Portion of individual features and elements in each pixel of satellite imagery was computed based on 'Endmember' of targeted elements. ii) Urbanized areas were categorized based on the 'Fraction imagery' derived from the 'SMA algorithm'. iii) Alterations and expanding of urban areas were identified based on the Multi-temporal satellite imageries. Tested method showed a strong potential to produce more advanced monitoring skills of urban areas.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.555-566
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• 2009

Precipitable water vapor (PWV) derived from a numerical weather prediction (NWP) model were compared to observations derived from ground-based Global Positioning System (GPS) receivers. The model data compared were from the Weather Research and Forecasting (WRF) model short-range forecasts on nested grids. The numerical experimets were performed by selecting the cloud microphysics schemes and for the comparisons, the Changma period of 2008 was selected. The observational data were derived from GPS measurements at 9-sites in South Korea over a 1-month period, in the middle of June-July 2008. In general, the WRF model demonstrated considerable skill in reproducing the temporal and spatial evolution of the PWV as depicted by the GPS estimations. The correlation between forecasts and GPS estimates of PWV depreciated slowly with increasing forecast times. Comparing simulations with a resolution of 18 km and 6 km showed no obvious PWV dependence on resolution. Besides, GPS and the model PWV data were found to be in quite good agreement with data derived from radiosondes. These results indicated that the GPS-derived PWV data, with high temporal and spatial resolution, are very useful for meteorological applications.