• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.229-233
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• 2007

This study is to test the applicability of QuickBird image for non-point source pollution assessment. SWAT (Soil and Water Assessment Tool) model was adopted and the model was calibrated for a stream watershed of 255.4 $km^2$ Landsat land use data. For model application with QuickBird image, a precise agricultural land use map of 1.16 $km^2$ area located in the upstream watershed was produced by field investigation. The model was run with the combination of land use and soil map scales (1:5,000, 1:25,000 and 1:50,000). The results were compared and analyzed for the contribution of non-point source pollution by the land use scale and contents.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.37-42
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• 2009

This study extracted Near Infrared (NIR) band using Image Processing Technology (IPT), and calculated Normalized Difference Vegetation Index (NDVI). Aerial photography from Daum portal in combination with high resolution satellite image was employed to improve vegetation sensitivity by extracting NIR band and calculating NDVI with comparison to QuickBird result. The extracted NIR band and NDVI through IPT presented similar distribution pattern. In addition, a regression analysis by land cover character showed high correlation paddy and forest Therefore, this approach could be acceptable to acquire vegetation environment information.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.540-547
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• 2011

This study was conducted to compare classification accuracy by tree species using QuickBird imagery for pixel- and segment-based classifications that have been mostly applied to classify land covers. A total of 398 points was used as training and reference data. Based on this points, the points were classified into fourteen land cover classes: four coniferous and seven deciduous tree species in forest classes, and three non-forested classes. In pixel-based classification, three images obtained by using raw spectral values, three tasseled indices, and three components from principal component analysis were produced. For the both classification processes, the maximum likelihood method was applied. In the pixel-based classification, it was resulted that the classification accuracy with raw spectral values was better than those by the other band combinations. As resulted that, the segment-based classification with a scale factor of 50% provided the most accurate classification (overall accuracy:76% and ${\hat{k}}$ value:0.74) compared to the other scale factors and pixel-based classification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.621-626
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• 2010

For geometric correction of high-resolution images, the authors matched corresponding objects between a large-scale digital map and a QuickBird image to obtain the coefficients of the first order polynomial. Proximity corrections were performed, using the Boolean operation, to perform automated matching accurately. The modified iterative closest point (ICP) algorithm was used between the point data of the surface linear objects and the point data of the edge objects of the image to determine accurate transformation coefficients. As a result of the automated geometric correction for the study site, an accuracy of 1.207 root mean square error (RMSE) per pixel was obtained.

• Proceedings of the KSRS Conference
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• v.2
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• pp.602-605
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• 2006

This study is to apply QuickBird satellite image for the simulation of storm runoff in a small rural watershed. For a 1.05 $km^2$ watershed located in Goesan-Gun of Chungbuk Province, the land use from the QuickBird image was produced by on-screening digitising after ortho-rectifying using 2 m DEM. For 3 cases of land use, soil and elevation scale (1:5,000, 1:25,000 and 1:50,000), SCS (Soil Conservation Service)-CN (Curve Number) and the watershed physical parameters were prepared for the storm runoff model, HEC-HMS (Hydrological Modelling System). The model was evaluated for each case and compared the simulated results with couple of selected storm events.

• Proceedings of the KSRS Conference
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• v.1
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• pp.409-412
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• 2006

Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.153-160
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• 2007

Forest cover density studies using high resolution satellite data and object oriented classification are limited in India. This article focuses on the potential use of QuickBird satellite data and object oriented classification in forest density mapping. In this study, the high-resolution satellite data was classified based on NDVI/pixel based and object oriented classification methods and results were compared. The QuickBird satellite data was found to be suitable in forest density mapping. Object oriented classification was superior than the NDVI/pixel based classification. The Object oriented classification method classified all the density classes of forest (dense, open, degraded and bare soil) with higher producer and user accuracies and with more kappa statistics value compared to pixel based method. The overall classification accuracy and Kappa statistics values of the object oriented classification were 83.33% and 0.77 respectively, which were higher than the pixel based classification (68%, 0.56 respectively). According to the Z statistics, the results of these two classifications were significantly different at 95% confidence level.

• Journal of the Korean association of regional geographers
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• v.11 no.4
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• pp.453-462
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• 2005

The study deals with surface erosion patterns due to the development of cropland toward hillslope and hilltop in the Oncheon-gun, pyeongbuk province and Nampo city of west coast area in the North Korea, using Quick Bird satellite images with 60cm resolution. In North Korea, for national economic difficult after 1980 year, newly developed croplands have been along the gentle hillslope, in which it is possible for individual man power different from the tideland which needs large scaled man-power and equipment. The new croplands are named Darakbat(terraced farm with embankment) and Bitalbat(titled farm developed on the original hill slope), neighboring with orchard and grouped settlement in lower valley. For supplying agricultural water, irrigation ditches and temporal crop storages have been constructed, connecting Darakbat, Bitalbat and orchard. These cropland developments have caused surface erosion composed of 3 types such as pit, linear and headward erosion, together with rill and gully. Owing to poor management of cropland and irrigation system, topsoil erosion and, collapse and sedimentation of ditch and pool, caused the decrease of agricultural productivity. These analysis using Quick Bird images can suggest original raw data about geographical facts on North Korea agriculture and help to recover their agricultural system and plan future national unified land.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.123-125
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• 2005

Many researchers conducted the effort for improving the classification accuracy of satellite image. Most of the study has used optical spectrum information of each pixel for image classification. By applying this method for high resolution satellite image, number of class becomes increase. This situation is remarkable for house, because the roof of house has variety of many colors. Even if the classification is carried out for many classes, roof color information of each house is not necessary. Most of the case, we need the information that object is house or not. In this study, we propose the method for detecting the object by using Genetic Algorithms (GA). Aircraft was selected as object. It is easy for this object to detect in the airport. An aircraft was taken as a template. Object image was taken from QuickBird. Target image includes an aircraft and Haneda Airport. Chromosome has four or five parameters which are composed of number of template, position (x,y), rotation angle, rate of enlarge. Good results were obtained in the experiment.