Kim, Chang-Hwan;Jeong, Eui-Young;Park, Chan-Hong;Jou, Hyeong-Tae;Lee, Seung-Hoon;Kim, Ho
한국지구물리탐사학회:학술대회논문집
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2008.10a
/
pp.207-212
/
2008
Bathymetry, side scan sonar, and magnetic survey data for the summit area of Dokdo obtained by Korea Ocean Research & Development Institute in 1999, 2004, and 2007 were analyzed to investigate the geophysical characteristics of the summit. Bathymetry and topographic data for the summit of Dokdo show uneven seabed and irregular undulations from costal line to -90 m in water depth, indicating the effects of partial erosions and taluses. The stepped slope in the bathymetry is supposed to be a coastal terrace suggesting repetition of transgressions and regressions in the Quaternary. The bathymetry and the side scan sonar data show a small crater, assumed to be formed by post volcanisms, at depth of $-100\;{\sim}\;-120\;m$ in the northeastern and the northwestern parts of the survey area. Except some areas with shallow sand sedimentary deposits, there are rocky seafloor and lack of sediments in the side scan sonar images of the survey area, dominantly. The analytic signal of the magnetic anomaly coincides with other geophysical results regarding to the location of the residual crater. The geophysical constraints of the summit of Dokdo propose that the islets and the rocky seabed elongated northeastward and northwestward from the islets might be the southern crater of the Dokdo volcano.
An intertidal topography is continuously changed due to morphodynamics processes. Detection and measurement of topographic change for a tidal flat is important to make an integrated coastal area management plan as well as to carry out sedimentologic study. The objective of this study is to generate intertidal DEM using leveling data and waterlines extracted from optical and microwave remotely sensed data in a relatively short period. Waterline is defined as the border line between exposed tidal flat and water body. The contour of the terrain height in tidal flat is equivalent to the waterline. One can utilize satellite images to generate intertidal DEM over large areas. Extraction of the waterline in a SAR image is a difficult task to perform partly because of the presence of speckle and partly because of similarity between the signal returned from the sea surface and that from the exposed tidal flat surface or land. Waterlines in SAR intensity and coherence map can effectively be extracted with MSP-RoA edge detector. From multiple images obtained over a range of tide elevation, it is possible to build up a set of heighted waterline within intertidal zone, and then a gridded DEM can be interpolated. We have tested the proposed method over the Gomso Bay, and succeeded in generating intertidal DEM with relatively high accuracy.
Satellite images have been used to obtain land cover information that is one of important factors for hydrological analysis over a large area. In urban area, more detailed land cover data are often required for hydrological analysis because of the relatively complex land cover types. The number of land cover classes that can be classified with traditional multispectral data is usually less than the ones required by most hydrological uses. In this study, we present the capabilities of hyperspectral data (Hyperion) for the classification of hydrological land cover types in urban area. To obtain 17 classes of urban land cover defined by the USDA SCS, spectral mixture analysis was applied using eight endmembers representing both impervious and pervious surfaces. Fractional values from the spectral mixture analysis were then reclassified into 17 cover types according to the ratio of impervious and pervious materials. The classification accuracy was then assessed by aerial photo interpretation over 10 sample plots.
GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.
Snow Cover is a form of precipitation that is defined by snow on the surface and is the single largest component of the cryosphere that plays an important role in maintaining the energy balance between the earth's surface and the atmosphere. It affects the regulation of the Earth's surface temperature. However, since snow cover is mainly distributed in area where human access is difficult, snow cover detection using satellites is actively performed, and snow cover detection in forest area is an important process as well as distinguishing between cloud and snow. In this study, we applied the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to the geostationary satellites for the snow detection of forest area in existing polar orbit satellites. On the rest of the forest area, the snow cover detection using $R_{1.61{\mu}m}$ anomaly technique and NDSI was performed. As a result of the indirect validation using the snow cover data and the Visible Infrared Imaging Radiometer (VIIRS) snow cover data, the probability of detection (POD) was 99.95 % and the False Alarm Ratio (FAR) was 16.63 %. We also performed qualitative validation using the Himawari-8 Advanced Himawari Imager (AHI) RGB image. The result showed that the areas detected by the VIIRS Snow Cover miss pixel are mixed with the area detected by the research false pixel.
Sejeong Bae ;Bokyung Son ;Taejun Sung ;Yeonsu Lee ;Jungho Im ;Yoojin Kang
Korean Journal of Remote Sensing
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v.39
no.5_3
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pp.1009-1029
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2023
Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R2 of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R2 of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.
Journal of the Korean Institute of Landscape Architecture
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v.40
no.5
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pp.8-18
/
2012
Urban nature plays an important role not only in the improvement of the physical environment but also from the perspective of psychological and social function. In particular, schoolyards as well as the green spaces near school surroundings function as a primary space for urban children to experience nature in Korea, as they spend most of their time at school. In this study, the status of urban green spaces near school surroundings was examined. For the analysis, 185 elementary schools in Seoul were selected and the green spaces within a radius of 300m(defined as 'school zone' in this study) were analyzed using the Rapid Eye multispectral satellite image data. The mean green space ratio of school zone accounts to about 21% with a high variation from 74% to 0.7% and more than half of the school zone have a green space ratio of less than 20%. Schools with a high green space ratio in their school zone are mostly located near urban forests, so forest areas particularly contribute to increase the green space ratio. Furthermore, forest vegetation shows relatively higher vitality than other green spaces located in urbanized areas. In contrast, schools with a low green space ratio in their school zone are mostly situated in high-density residential areas and the green spaces show relatively low vegetation vitality. Except for the urban forest, the majority of urban green spaces in urbanized areas are landscape green facilities in apartment districts. The other types of urban open spaces such as environmentally shaped schoolyards or street parks account only for a very small proportion of school surroundings. Therefore, it is needed to establish countermeasures in the context of urban planning; e.g. to promote the school forest projects preferentially by selecting schools with a extremely low green space ratio in their school zone, to foster roof greening in near surroundings, and to connect schoolyards organically with nearby apartment landscape green facilities as an easily accessible urban open space.
According to the advancement of the GNSS satellite positioning system, the module of hardware and operation software reflecting accuracy and economical efficiency is implemented in the user sector including the multi-channel GNSS receiver, the multi-frequency external antenna and the mobile app (App) base public positioning analysis software etc., and the multichannel GNSS RTK positioning of the active configuration method (DIY, Do it yourself) is possible according to the purpose of user. Especially, as the infrastructure of multi-GNSS satellite is expanded and the potential of expansion of utilization according to various modules is highlighted, interest in the utilization of multi-channel low-cost GNSS receiver module is gradually increasing. The purpose of this study is to review the multi-channel low-cost GNSS receivers that are appearing in the mass market in various forms and to analyze the utilization plan of the "address information facility investigation project" of the Ministry of Public Administration and Security by constructing the multi-channel low-cost GNSS positioning module based RTK survey system (hereinafter referred to as "multi-channel GNSS RTK module positioning system"). For this purpose, we constructed a low-cost "multi-channel GNSS RTK module positioning system" by combining related modules such as U-blox's F9P chipset, antenna, Ntrip transmission of GNSS observation data and RTK positioning analysis app through smartphone. Kinematic positioning was performed for circular trajectories, and static positioning was performed for address information facilities. The results of comparative analysis with the Static positioning performance of the geodetic receivers were obtained with 5 fixed points in the experimental site, and the good static surveying performance was obtained with the standard deviation of average ±1.2cm. In addition, the results of the test point for the outline of the circular structure in the orthogonal image composed of the drone image analysis and the Kinematic positioning trajectory of the low cost RTK GNSS receiver showed that the trajectory was very close to the standard deviation of average ±2.5cm. Especially, as a result of applying it to address information facilities, it was possible to verify the utility of spatial information construction at low cost compared to expensive commercial geodetic receivers, so it is expected that various utilization of "multi-channel GNSS RTK module positioning system"
Land Remote Sensing' is defined as the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. Narrowly speaking, this is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information. Remote sensing technology was initially developed with certain purposes in mind ie. military and environmental observation. However, after 1970s, as these high-technologies were taught to private industries, remote sensing began to be more commercialized. Recently, we are witnessing a 0.61-meter high-resolution satellite image on a free market. While privatization of land remote sensing has enabled one to use this information for disaster prevention, map creation, resource exploration and more, it can also create serious threat to a sensed nation's national security, if such high resolution images fall into a hostile group ie. terrorists. The United States, a leading nation for land remote sensing technology, has been preparing and developing legislative control measures against the remote sensing industry, and has successfully created various policies to do so. Through the National Oceanic and Atmospheric Administration's authority under the Land Remote Sensing Policy Act, the US can restrict sensing and recording of resolution of 0.5 meter or better, and prohibit distributing/circulating any images for the first 24 hours. In 1994, Presidential Decision Directive 23 ordered a 'Shutter Control' policy that details heightened level of restriction from sensing to commercializing such sensitive data. The Directive 23 was even more strengthened in 2003 when the Congress passed US Commercial Remote Sensing Policy. These policies allow Secretary of Defense and Secretary of State to set up guidelines in authorizing land remote sensing, and to limit sensing and distributing satellite images in the name of the national security - US government can use the civilian remote sensing systems when needed for the national security purpose. The fact that the world's leading aerospace technology country acknowledged the magnitude of land remote sensing in the context of national security, and it has made and is making much effort to create necessary legislative measures to control the powerful technology gives much suggestions to our divided Korean peninsula. We, too, must continue working on the Korea National Space Development Act and laws to develop the necessary policies to ensure not only the development of space industry, but also to ensure the national security.
Spatial distribution of Phytoplankton Pigment Concentration (PPC) and Sea Surface Temperature (SST) around the East Korean Warm Current (EKWC) was described, using both Coastal Zone Color Scanner (CZCS) images and Advanced Very High Resolution Radiometer (AVHRR) images in May, 1980. Water mass in this region can be classified into five categories in the horizontal profile of PPC and SST, nLw (normalized water-leaving radiance) images: (1) coastal cold water region associated with concentrations of dissolved organic material or yellow colored substances and suspended sediments, (2) cold water region of thermal frontal occurred by a combination of phytoplankton absorption and suspended materials, (3) warm water overlay region by the phytoplankton absorption than the suspended materials; (4) warm water region occurred by the low phytoplankton absorption, and (5) offshore region occurred by the high phytoplankton absorption. In particular, the highest PPC (>2.0 mg/m^3) area appeared in the CZCS and AVHRR images with a band shaped distribution of the thermal front and ocean color front region, which is located the coastal cold waters alonB western thermal front of the warm streamer of the EKWC. In this region, the highest PPC occurred by a combination of the high absorption of the phytoplankton (443 nm) and highest reflectance of suspended materials (550 nm). Another high PPC ($\simeq$$6\;mg/m^3$) appeared in the warm water overlay region inside warm streamer. High phytoplankton pigment concentration of this region was corresponding to the short wavelength of 443 nm, which represented phytoplankton absorption of the CZCS image.
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