Simultaneous measurements using a scanning spectrograph system and transmissometer were performed for the first time over an urban site in Gwangju, Korea, to derive the ambient $NO_2$ volume mixing ratio. The differential slant column densities retrieved from the scanning spectrograph system were converted to volume mixing ratios using the light traveling distance along the scanning line of sight derived from the transmissometer light extinction coefficients. To assess the performance of this system, we compared the derived $NO_2$ volume mixing ratios with those measured by an in situ chemiluminescence monitor under various atmospheric conditions. For a cloudless atmosphere, the linear correlation coefficient (R) between the two data sets (i.e., data derived from the scanning spectrograph and from the in situ monitor) was 0.81; the value for a cloudy atmosphere was 0.69. The two sets of $NO_2$ volume mixing ratios were also compared for various wind speeds. We also consider the measurement errors, as estimated from an error propagation analysis.
The NDVI(normalized difference vegetation index) dataset is unique or main tool to assess the global, multi seasonal, multi annual, and multi spectral changes over the World. These features are useful for environmental studies in particular, for the vegetation coverage monitoring of the country as Mongolia, where are large pastureland and pastoral animal husbandry, which dependent on natural conditions. Pasture vegetation cover is changing accordingly with both of global climate change and anthropogenic effect or human impacts. Using past 20 years (1982-2001) NDVI derived from NOAA satellite, its dynamical trend has been decreased in all natural zones differently. Also applied the method named "Two Years Differences" which could calculate the number of years with increased or decreased NDVI values at the same place. From May to September have occurred the 9 years maximum decreases of NDVI over Mongolia, but it obtained differently in spatial and temporal scale. In 24.4 ? 32.7% of all territory occurred one year decrease of NDVI and in 18% occurred more than 3 years frequent decrease of NDVI. According to the linear trend of NDVI and in 18% occurred more than 3 years frequent decrease of NDVI dynamics over 69% of whole territory of Mongolia NDVI values had been decreased due to both natural and human induced impacts to the pasture condition. In this paper also included some results of the integrated analyses of NOAA/NDVI and ground truth data over Monglia separately by natural zones.
Ground-based remote sensing can be used as one of the non-destructive, fast, and real-time diagnostic tools for quantifying yield, biomass, and nitrogen (N) stress during growing season. This study was conducted to assess biomass and nitrogen (N) status of paddy rice (Oryza sativa L.) plants under N stress using passive and active ground-based remote sensors. Nitrogen application rates were 0, 70, 100, and 130 kg N $ha^{-1}$. At each growth stage, reflectance indices measured with active sensor showed higher correlation with DW, N uptake and N concentration than those with the passive sensor. NIR/Red and NIR/Amber indices measured with Crop Circle active sensors generally had a better correlation with dry weight (DW), N uptake and N content than vegetation indices from Crop Circle passive sensor and NDVIs from active sensors. Especially NIR/Red and NIR/amber ratios at the panicle initiation stage were most closely correlated with DW, N content, and N uptake. Rice grain yield, DW, N content and N uptake at harvest were highly positively correlated with canopy reflectance indices measured with active sensors at all sampling dates. N application rate explains about 91~92% of the variability in the SI calculated from NIR/Red or NIR/Amber indices measured with Crop Circle active sensors on 12 July. Therefore, the in-season sufficiency index (SI) by NIR/Red or NIR/Amber index from Crop Circle active sensors can be used for determination of N application rate.
PARK DOO-YOUL;KIM JIN-KWANG;LEE HO-NAM;WON JOONG-SUN
Proceedings of the KSRS Conference
/
2005.10a
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pp.667-670
/
2005
Ground control points(GCPs) can be extracted from SAR data given precise orbit for DTM generation using optic images and other SAR data. In this study, we extract GCPs from ERS SAR data and SRTM DEM. Although it is very difficult to identify GCPs in ERS SAR image, the geometry of optic image and other SAR data are able to be corrected and more precise DTM can be constructed from stereo optic images. Twenty GCPs were obtained from the ERS SAR data with precise Delft orbit information. After the correction was applied, the mean values of planimetric distance errors of the GCPs were 3.7m, 12.1 and -0.8m with standard deviations of 19.9m, 18.1, and 7.8m in geocentric X, Y, and Z coordinates, respectively. The geometries of SPOT stereo pair were corrected by 13 GCPs, and r.m.s. errors were 405m, 705m and 8.6m in northing, easting and height direction, respectively. And the geometries of RADARS AT stereo pair were corrected by 12 GCPs, and r.m.s. errors were 804m, 7.9m and 6.9m in northing, easting and height direction, respectively. DTMs, through a method of area based matching with pyramid images, were generated by SPOT stereo images and RADARS AT stereo images. Comparison between points of the obtained DTMs and points estimated from a national 1 :5,000 digital map was performed. For DTM by SPOT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. For DTM by RADARSAT stereo images, the mean values of distance errors in northing, easting and height direction were respectively -7.6m, 9.6m and -3.1m with standard deviations of 9.1m, 12.0m and 9.1m. These results met the accuracy of DTED level 2
The Journal of the Korea institute of electronic communication sciences
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v.6
no.4
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pp.523-531
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2011
Many of the wells which were constructed to use ground water resource are abandoned and not managed efficiently after its use. And a variety of heavy metals and organic compounds are released from the abandoned wells and this can cause ground water pollution. Therefore in this paper implemented to monitor locational information drill holes and underground water sensing information on real time basis using u-GIS environment to combined ubiquitous sensor node and GIS technology to improve these problems. In addition, this system suggests using system by UML 2.0 by analyzing variety requirement of user and between system internal modules interaction and data flow. It provides graphical user interfaces (GUI) to system users to monitor water-well related property information and its managements for each water-well at remote site by variety platform by GIS map and web environment and mobile device based on smart phone.
IKONOS 1m satellite imagery is particularly well suited for 3-D feature extraction and 1 :5,000 scale topographic mapping. Because the image line and sample calculated by given RPCs have the error of more than 11m, in order to be able to perform feature extraction and topographic mapping, rational polynomial coefficients(RPCs) camera model that are derived from the very complex IKONOS sensor model to describe the object-image geometry must be refined by several Ground Control Points(GCPs). This paper presents a quantitative evaluation of the geometric accuracy that can be achieved with IKONOS imagery by refining the offset and scaling factors of RPCs using several GCPs. If only two GCPs are available, the offsets and scale factors of image line and sample are updated. If we have more than three GCPs, four parameters of the offsets and scale factors of image line and sample are refined first, and then six parameters of the offsets and scale factors of latitude, longitude and height are updated. The stereo images acquired by IKONOS satellite are tested using six ground points. First, the RPCs model was refined using 2 GCPs and 4 check points acquired by GPS. The results from IKONOS stereo images are reported and these show that the RMSE of check point acquired from left images and right are 1.021m and 1.447m. And then we update the RPCs model using 4 GCPs and 2 check points. The RMSE of geometric accuracy is 0.621 m in left image and 0.816m in right image.
Kim, Youn-Soo;Jeun, Gab-Ho;Jeun, Jung-Nam;Blet, Didier
Proceedings of the KSRS Conference
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v.2
/
pp.808-811
/
2006
The KOMPSAT-2 was developed by KARI and it was successfully launched from Plesetsk, Russia on 28th July 2006. The Korean government decided the commercialization of the KOMPSAT-2 image data and direct reception services worldwide. SPOT Image, based in Toulouse (France) was selected by KARI through an international open bidding as a foreign company for the KOMPSAT-2 image promotion over the entire world except the territory of Republic of Korea including the North Korea, the United States of America, UAE, Saudi Arabia, Kuwait, Qatar, Oman, Yemen, Egypt, Iran, Iraq, Jordan, Lebanon, and Syria. KAI (Korea Aerospace Industry Ltd.) is an engaged Korean company for this area. KARI has responsibility to operate the satellite, data acquisition, archiving for the worldwide commercialization. For the processing and delivery of the KOMPSAT-2 image data to the users of KAI and SPOT Image, KAI has the binding contract with KARI. So KAI has the responsibility for the commercial ground station operation such as user support, data processing, and the data delivery. The KOMPSAT-2 ground station is hosted in KARI, so KARI has developed the concept of KOCUST (KOMPSAT-2 Commercial User Support Team) jointly with KAI to support the data processing and delivery as KOMPSAT-2 developer and satellite operator. The main purpose of the KOCUST is to support the operational activities to provide the data and service quality to satisfy customers. KOCUST will be organized by the members of KARI and KAI together. KARI members will mainly take the role of KOCUST coordination, data processing and user support in a public sector. KAI members are going to take user desk, data validation and delivery et cetera, which are related with users. This paper describes a summarized concepts of KOCUST like organization, dedicated tasks of each part and work flow of daily operation.
New Orleans located in the estuary of the Mississippi River was attacked by Hurricane Katrina and suffered big flood on August 2005. Since unconsolidated Holocene to middle Miocene strata is the main basement rocks, land subsidence has been occurred steadily due to soil compaction and normal faulting. It was reported that the maximum subsidence rate from 2002 to 2005 was -29 mm/yr. Many studies in the area have been carried out for understanding the subsiding and potential risks caused by ground subsidence are weighted by the fact that a large area of the city is located below the mean sea level. A small baseline subset (SBAS) method is applied for effectively measuring time-series LOS (Line-of sight) surface deformation from differential synthetic aperture radar interferograms in this study. The time-series surface deformation at New Orleans was measured from RADARSAT-1 SAR images. The used dataset consists of twenty-one RADARSAT-1 fine beam mode images on descending orbits from February 2005 to February 2007 and another twenty-one RADARSAT-1 standard beam mode images on ascending orbits from January 2005 to February 2007. From this dataset, 25 and 38 differential interferograms on descending and ascending orbits were constructed, respectively. The vertical and horizontal components of surface deformation were extracted from ascending and descending LOS surface deformations. The result from vertical component of surface deformation indicates that subsidence is not significant with a mean rate of -3.1${\pm}$3.2 mm/yr.
The COMS provides the LRIT/HRIT services to users. The COMS LRIT/HRIT broadcast service should satisfy the 15 minutes timeliness requirement. The requirement is important and critical enough to impact overall performance of the LHGS. HRIT image data is acquired from INRSM output receiving but LRIT image data is generated by sub-sampling HRIT image data in the LHGS. Specially, since LRIT is acquired from sub-sampled HRIT image data, LRIT processing spent more time. Besides, some of data loss for LRIT occurs since LRIT is compressed by lossy JPEG. Therefore, algorithm with the fastest processing speed and simplicity to be implemented should be selected to satisfy the requirement. Investigated sub-sampling algorithm for the LHGS were nearest neighbour algorithm, bilinear algorithm and bicubic algorithm. Nearest neighbour algorithm is selected for COMS LHGS considering the speed, simplicity and anti-aliasing corresponding to the guideline of user (KMA: Korea Meteorological Administration) to maintain the most cloud itself information in a view of meteorology. But the nearest neighbour algorithm is known as the worst performance. Therefore, it is studied in this paper that the selection of nearest neighbour algorithm for the LHGS is reasonable. First of all, characteristic of 3 sub-sampling algorithms is studied and compared. Then, several sub-sampling algorithm were applied to MTSAT-1R image data corresponding to COMS HRIT. Also, resized image was acquired from sub-sampled image with the identical sub-sampling algorithms applied to sub-sampling from HRIT to LRIT. And the difference between original image and resized image is compared. Besides, PSNR and MSE are calculated for each algorithm. This paper shows that it is appropriate to select nearest neighbour algorithm for COMS LHGS since sub-sampled image by nearest neighbour algorithm is little difference with that of other algorithms in quality performance from PSNR.
Electro-Optical Camera(EOC) is the main payload of Korea Multi-Purpose SATellite(KOMPSAT) with the mission of cartography to build up a digital map of Korean territory including Digital Terrain Elevation Map(DTEM). This instrument which comprises EOC Sensor Assembly and EOC Electronics Assembly produces the panchromatic images of 6.6 m GSD with a swath wider than 17 km by push-broom scanning and spacecraft body pointing in a visible range of wavelength, 510 ~ 730 nm. The high resolution panchromatic image is to be collected for 2 minutes during 98 minutes of orbit cycle covering about 800 km along ground track, over the mission lifetime of 3 years with the functions of programmable rain/offset and on-board image data storage. The image of 8 bit digitization, which is collected by a full reflective type F8.3 triplet without obscuration, is to be transmitted to Ground Station at a rate less than 25 Mbps. EOC was elaborated to have the performance which meets or surpasses its requirements of design phase. The spectral response the modulation transfer function, and the uniformity of all the 2592 pixel of CCD of EOC are illustrated as they were measured for the convenience of end-user. The spectral response was measured with respect to each gain setup of EOC and this is expected to give the capability of generating more accurate panchromatic image to the EOC data users. The modulation transfer function of EOC was measured as greater than 16% at Nyquist frequency over the entire field of view which exceeds its requirement of larger than 10%, The uniformity that shows the relative response of each pixel of CCD was measured at every pixel of the Focal Plane Array of EOC and is illustrated for the data processing.
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