• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.14-16
• /
• 2004

Although there have been wide range of studies to characterize forest stands based upon spectral information of satellite image, it was not fully understood the texture information of forest stand using high resolution data. The objective of this study is to evaluate several texture measures for characterizing forest stand structure, such as species composition, diameter at breast height(DBH), stand density, and age. High resolution IKONOS satellite imagery data were acquired in August 200 lover the forested area near Ulsan, Korea. Primary forest types were plantation pine, mixed forest, and natural deciduous forest of stand age ranging from 10 to 50 years old. Several GLCM-based texture measures were compared with forest stand characteristics. In overall, a texture measure (contrast) calculated using red band were better to differentiate species and age group than other texture measures and near infrared bands.

• 한국공간정보시스템학회:학술대회논문집
• /
• 2005.11a
• /
• pp.17-22
• /
• 2005

Generally, pixel-based classification, utilize the similarity of distances between the pixel values in feature space, is applied to land use mapping using satellite remote sensing data. But this method is Improper to be applied to the very high resolution satellite data (VHRS) due to complexity of the spatial structure and the variety of pixel values. In this paper, we performed the hierarchical classification of VHRS imagery by data fusion, which integrated LiDAR height and intensity information. MLC and ISODATA methods were applied to IKONOS-2 imagery with and without LiDAR data prior to the hierarchical classification, and then results was evaluated. In conclusion, the hierarchical method with LiDAR data was the superior than others in VHRS imagery and both MLC and ISODATA classification with LiDAR data were better than without.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.3
• /
• pp.21-29
• /
• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.

• The Korean Journal of Applied Statistics
• /
• v.25 no.5
• /
• pp.733-741
• /
• 2012

The successful launch of Arirang satellites allow the acquisition of high resolution satellite imagery of Korean territory and enables the transition from the conventional cultivation area survey method to new image based methods adopted in advanced nations. In this study, we suggested reasonable sizes of the primary sampling unit and the secondary sampling unit for the satellite imagery based sampling design in 8 provinces preselected for this research. The PSU size was determined mainly in consideration of intracorrelation that shows the degree of homogeneity within each cluster and the efficiency of the image process. For the SSU size, we considered the relative standard error and the differences between the land cover maps produced by the Ministry of Environment and the satellite imagery processed by the National Statistical Office.

• Spatial Information Research
• /
• v.12 no.2
• /
• pp.127-135
• /
• 2004

The operational availability of multispectral high-resolution satellite imagery, opens up new possibilities for updating forest map. Compared with information acquired by traditional methods (Panchromatic Aerial Photo), these data of for a number of advantages. In this study used 1m spatial resolution and 4 multispectral band, which are capability to update forest map of kind of tree. From the result of this study, First, the visual analysis of the colour composites of the multispectral data made it possible to distinguish some species(conifer, broad-leaved, un-stocked, arable land). Second, forest map and orthorectiffd satellite imagery are not match in the boundary of forest, therefore work have some troubles in the modification of forest map. Third, the distinguish from age-class, girth-class and density are much need experience and skillful about sample such as aerial photo.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.1271-1275
• /
• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat +ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Journal of Korean Society for Geospatial Information Science
• /
• v.17 no.1
• /
• pp.3-11
• /
• 2009

This study aims at proposing that high resolution satellite images could be used to form an urban management plan by calculating the amount of green areas and detecting land use changes in each zoning region within urban planning jurisdiction of Jinju in Gyeongsangnam-do selected as a case study area, analysing imagery of IKONOS and KOMPSAT-2 that are high resolution satellite images. In conclusion, application possibilities of high resolution satellite images as assessment data of urban management administration that help to assess changes in each zoning region are indicated after developing modules based on ArcGIS for calculation and detection of green areas and land use changes and then analysing land use changes and spatial distribution of green areas by using those modules.

• The Korean Journal of Ecology
• /
• v.26 no.2
• /
• pp.75-81
• /
• 2003

This study was performed to prove if the high resolution satellite imagery of IKONOS is suitable for preparing digital vegetation map which is becoming increasingly important in ecological science. Seven classes for forest area and five classes for non-forest area were taken for classification. Three methods, such as the pixel based classification, the segment based classification with majority principle, and the segment based classification with maximum likelihood, were applied to classify IKONOS imagery taken in April 2000. As a whole, the segment based classification shows better performance in classifying the high resolution satellite imagery of IKONOS. Through the comparison of accuracies and kappa values of the above 3 classification methods, the segment based classification with maximum likelihood was proved to be the best suitable for preparing the vegetation map with the help of IKONOS imagery. This is true not only from the viewpoint of accuracy, but also for the purpose of preparing a polygon based vegetation map. On the basis of the segment based classification with the maximum likelihood, a digital vegetation map in which each vegetation class is delimitated in the form of a polygon could be prepared.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.4
• /
• pp.27-39
• /
• 2023

Detecting greenhouses from the remote sensing datasets is useful in identifying the illegal agricultural facilities and predicting the agricultural output of the greenhouses. This research proposed a methodology for automatically detecting greenhouses from a given Planetscope satellite imagery acquired in the areas of Gimje City using the deep learning technique through a series of steps. First, multiple training images with a fixed size that contain the greenhouse features were generated from the five training Planetscope satellite imagery. Next, the YOLO(You Only Look Once) model was trained using the generated training images. Finally, the greenhouse features were detected from the input Planetscope satellite image. Statistical results showed that the 76.4% of the greenhouse features were detected from the input Planetscope satellite imagery by using the trained YOLO model. In future research, the high-resolution satellite imagery with a spatial resolution less than 1m should be used to detect more greenhouse features.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.586-589
• /
• 2006

High resolution satellite imagery is regarded as one of the important data sets to engineering application, as well as conventional scientific application. However, despite this general view, there are a few target applications using this information. In this study, the possibility for the future wide uses in associated with smart graphics of this information is investigated. The concept of smart graphics can be termed intelligent graphics with XML-based structure and knowledge related to semantic web, which is a useful component for the data dissemination framework model in a multi-layered web-based application. In the first step in this study, high resolution imagery is transformed to GML (Geographic Markup Language)-based structure with attribute schema and geo-references. In the second, this information is linked with GIS data sets, and this fused data set is represented in the X3D (eXtensible 3D), ISO-based web 3D graphic standard, with styling attributes, in the next stop. The main advantages of this approach using GML and X3D are the flourished representations of a source data according to user/clients’ needs and structured 3D visualization linked with other XML-based application. As for the demonstration of this scheme, 3D urban modelling case with actual data sets is presented.