• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.04a
• /
• pp.267-273
• /
• 2004

The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study is used to the high-resolution (6.6m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data(36 bands).We accomplished FCM classification technique with MLC technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.313-315
• /
• 2003

Tarim River is the longest continental river in China. Its downstream ecological environment declination and valley remedy got great concern. To improve ecological environment of lower Tarim River, “Emergent water transportation project for Tarim river valley remedy” was carried out from May 2000. Water was transported five times till May 2003. Several periods MODIS image was used to monitor water body in river channel. Two periods ETM image was used to interpreter changes of environment. Area of vegetation in 1999 was similar with 2001, but become better in total. The normalized difference vegetation index (NDVI) and vegetative coverage reflected environment changed better.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_2
• /
• pp.1829-1836
• /
• 2021

Cloud detection means determining the presence or absence of clouds in a pixel in a satellite image, and acts as an important factor affecting the utility and accuracy of the satellite image. In this study, among the satellites of various advanced organizations that provide cloud detection data, we intend to perform quantitative and qualitative comparative analysis on the difference between the cloud detection data of GK-2A/AMI, Terra/MODIS, and Suomi-NPP/VIIRS. As a result of quantitative comparison, the Proportion Correct (PC) index values in January were 74.16% for GK-2A & MODIS, 75.39% for GK-2A & VIIRS, and 87.35% for GK-2A & MODIS in April, and GK-2A & VIIRS showed that 87.71% of clouds were detected in April compared to January without much difference by satellite. As for the qualitative comparison results, when compared with RGB images, it was confirmed that the results corresponding to April rather than January detected clouds better than the previous quantitative results. However, if thin clouds or snow cover exist, each satellite were some differences in the cloud detection results.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.51 no.5
• /
• pp.25-34
• /
• 2009

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.

• Journal of Korean Society for Atmospheric Environment
• /
• v.34 no.3
• /
• pp.493-507
• /
• 2018

Due to high spatio-temporal variability of amount and optical/microphysical properties of atmospheric aerosols, satellite-based observations have been demanded for spatiotemporal monitoring the major aerosols. Observations of the heavy aerosol episodes and determination on the dominant aerosol types from a geostationary satellite can provide a chance to prepare in advance for harmful aerosol episodes as it can repeatedly monitor the temporal evolution. A new geostationary observation sensor, namely the Advanced Himawari Imager (AHI), onboard the Himawari-8 platform, has been observing high spatial and temporal images at sixteen wavelengths from 2016. Using observed spectral visible reflectance and infrared brightness temperature (BT), the algorithm to find major aerosol type such as volcanic ash (VA), desert dust (DD), polluted aerosol (PA), and clean aerosol (CA), was developed. RGB color composite image shows dusty, hazy, and cloudy area then it can be applied for comparing aerosol detection product (ADP). The CALIPSO level 2 vertical feature mask (VFM) data and MODIS level 2 aerosol product are used to be compared with the Himawari-8/AHI ADP. The VFM products can deliver nearly coincident dataset, but not many match-ups can be returned due to presence of clouds and very narrow swath. From the case study, the percent correct (PC) values acquired from this comparisons are 0.76 for DD, 0.99 for PA, 0.87 for CA, respectively. The MODIS L2 Aerosol products can deliver nearly coincident dataset with many collocated locations over ocean and land. Increased accuracy values were acquired in Asian region as POD=0.96 over land and 0.69 over ocean, which were comparable to full disc region as POD=0.93 over land and 0.48 over ocean. The Himawari-8/AHI ADP algorithm is going to be improved continuously as well as the validation efforts will be processed by comparing the larger number of collocation data with another satellite or ground based observation data.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.590-593
• /
• 2006

Timber inventory management includes to measure and update forest attributes, which is crucial information for private companies and public organizations in property assessment and environment monitoring. Field measurement would be accurate, but time-consuming and inefficient. For the reason, remote sensing technology has been an alternative to field measurement from an economic perspective. Among several sensors, LiDAR and Radar interferometry are known for their efficiency for forest monitoring because they are less influenced by weather and light conditions, and provide reasonably accurate vertical/horizontal measurement for a large area in a short period. For example, Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED) in the U.S. can provide tree height information and DSM. On the other hand, LiDAR DSM (the first return) and DEM (the last return) can also present tree height estimation. With respect to project site of loblolly pine plantation in Louisiana in the U.S., the accuracy of SRTM C-Band approach estimating tree height was assessed by the LiDAR approaches. In addition, SRTM X-Band and NED were also compared with the results. Plantation year in inventory GIS, which is directly related to forest age, is high correlated with the difference between SRTM C-Band and NED. As a byproduct, several stands of age mismatch could be recognized using an outlier detection algorithm, and optical satellite image (ETM+) were used to verify the mismatch. The findings of this study were (1) the confirmation of usefulness of the SRTM DSM for forest monitoring and (2) Multi-sensors- Radar, LiDAR, ETM+, MODIS can be used for accuracy improvement of forest inventory GIS altogether.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.236-238
• /
• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands from Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-functional Transport Satellite-1 Replacement (MTSAT-1R) data. The algorithm is the hybrid algorithm that has used two methods combined together. The first method used the differential absorption in brightness temperature difference between $11{\mu}m$ and $12{\mu}m$ (BTD1). The radiation at 11 ${\mu}m$ is absorbed more than at 12 ${\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m$ and $11{\mu}m$ (BTD2). The technique would be most sensitive to dust loading during the day when the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. We have applied the three methods to MTSAT-1R for derivation of the yellow sand dust and in conjunction with the Principle Component Analysis (PCA), a form of eigenvector statistical analysis. As produced Principle Component Image (PCI) through the PCA is the correlation between BTD1 and BTD2, errors of about 10% that have a low correlation are eliminated for aerosol detection. For the region of aerosol detection, aerosol index (AI) is produced to the scale of BTD1 and BTD2 values over land and ocean respectively. AI shows better results for yellow sand detection in comparison with the results from individual method. The comparison between AI and OMI aerosol index (AI) shows remarkable good correlations during daytime and relatively good correlations over the land.

• KCID journal
• /
• v.21 no.1
• /
• pp.78-88
• /
• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.820-823
• /
• 2006

Nonlinear internal waves (NLIW) were studied as a unusual phenomena in the ocean decades ago. As the quality, quantity and variety of satellite images improve over decades, it is founded that NLIW is a ubiquitous phenomenon. Over the continental shelf of northern South China Sea (SCS), both optical and microwave images show that there are trains of NLIW packets near Dongsha Atoll (20.7N, 116.8E). Each packet contains several NLIW fronts. These NLIW packets are nearly parallel to each other and they are refracted, reflected or diffracted by the change of ocean bottom topography. Based on Korteweg de Vries (KdV) theory and the assumption that the bright/dark lines in the satellite images are centers of convergence/divergence of NLIW fronts, one may (1) sort NLIW packets in the same satellite image into groups of the same source, but generated at different tidal cycles, (2) relate NLIW packets in consecutive satellite images of one day apart, (3) locating faint signals of NLIW fronts in a satellite image. The NLIWs travel more than 100 km/day near Dongsha Atoll, with higher speed in deeper water. The bias and standard deviation of predicted location of NLIW front from its true location is about 1% and 5.1%, respectively.

• Korean Journal of Remote Sensing
• /
• v.34 no.5
• /
• pp.787-799
• /
• 2018

Accurate and effective mapping is critical step to monitor the spatial distribution and change of flood inundated area in large scale flood event. In this study, we try to suggest methods to use low spatial resolution satellite optical imagery for flood mapping, which has high temporal resolution to cover wide geographical area several times per a day. We selected the Sebou watershed flood in Morocco that was occurred in early 2010, in which several hundred $km^2$ area of the Gharb lowland plain was inundated. MODIS daily surface reflectance product was used to detect the flooded area. The study area showed several distinct spectral patterns within the flooded area, which included pure turbid water and turbid water with vegetation. The flooded area was extracted by thresholding on selected band reflectance and water-related spectral indices. Accuracy of these flooding detection methods were assessed by the reference map obtained from Landsat-5 TM image and qualitative interpretation of the flood map derived. Over 90% of accuracies were obtained for three methods except for the NDWI threshold. Two spectral bands of SWIR and red were essential to detect the flooded area and the simple thresholding on these bands was effective to detect the flooded area. NIR band did not play important role to detect the flooded area while it was useful to separate the water-vegetation mixed flooded classes from the purely water surface.