• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.18 no.1
• /
• pp.59-66
• /
• 2000

This study describes the precise DTM by image processing method through scanning the positive film of aerial photo using scanner instead of plotter. First, scanned the positive film of aerial photo by drum scanner and flatbed scanner in different resolution, and then compared the height from image processing method using auto correlation method with height which is taken using $50^m{\times}50^m$ grid in 1 :5,000 geographical map. It shows that heights from aerial photo image of high resolution obtained from scanner are comparable to the heights from 1：5,000 geographical map.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.260-262
• /
• 2006

One of future remote sensing techniques for transportation application is vehicle detection from the space, which could be the basis of measuring traffic volume and recognizing traffic condition in the future. This paper introduces an approach to vehicle detection using image object segmentation approach. The object-oriented image processing is particularly beneficial to high-resolution image classification of urban area, which suffers from noisy components in general. The project site was Dae-Jeon metropolitan area and a set of true color aerial images at 10cm resolution was used for the test. Authors investigated a variety of parameters such as scale, color, and shape and produced a customized solution for vehicle detection, which is based on a knowledge-based hierarchical model in the environment of eCognition. The highest tumbling block of the vehicle detection in the given data sets was to discriminate vehicles in dark color from new black asphalt pavement. Except for the cases, the overall accuracy was over 90%.

• Korean Journal of Agricultural Science
• /
• v.42 no.3
• /
• pp.269-276
• /
• 2015

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we discussed the state-of-the-art of the domestic and international use of UAV in agricultural sector as well as assessed its utilization and applicability for agricultural environment in Korea. Association of robotic, computer vision and geomatic technologies have established a new paradigm of low-altitude aerial remote sensing that has now been receiving attention from researchers all over the world. In a field study, it has been found that use of UAV imagery in an agricultural subsidy program can reduce the farmers' complain and provide objective evidence. UAV high resolution photography can also be helpful in monitoring the disposal zone for animal carcasses. Due to its expeditiousness and accuracy, UAV imagery can be a very useful tool to evaluate the damage in case of an agricultural disaster for both parties insurance companies and the farmers. Also high spatial and temporal resolution in UAV system can increase the prediction accuracy which in turn help to maintain the agricultural supply and demand chain.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.247-249
• /
• 2007

Crown parameters are important roles in tree species identification, because the canopy is the aggregate of all the crowns. However, crown measurements with spaceborne image data have remained more difficult than on aerial photographs since trees show more structural detail at higher resolutions. This recognized problem led to the initiation of the research to determine if high resolution satellite image data could be used to identify and classify single tree species. In this paper, shape parameters derived from pixel-based crown area measurements and texture features derived from GLCM parameters in QuickBird image were tested and compared for individual tree species identification. As expected, initial studies have shown that the crown parameters and the canopy texture parameters provided a differentiating method between coniferous trees and broad-leaved trees within the compartment(less than forest stand) for single extraction from spaceborne high resolution image.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.1
• /
• pp.80-93
• /
• 2016

Parcel boundary demarcation in agricultural area is commonly performed by terrestrial surveying methods, which have been pointed out as drawbacks to require consuming too much time and heavy expenditure. With the developments of high performance digital aerial cameras, however, studies on cadastral boundary demarcation with an aerial photogrammetric method attract a great attention in recent years. In this paper, an approach is presented to rapidly demarcate parcel boundaries coinciding with real ground ones in agricultural areas by extracting boundaries from the high resolution aerial orthoimages based on aerial targets. In order to investigate the feasibility of the proposed method, the accuracy of coordinates and area of parcel boundaries extracted from the aerial targets appeared in orthoimages compared with that of terrestrial boundary surveying results over the selected two test agricultural areas. Aerial image data were processed taken by a ADS80 digital camera with a GSD of 8cm in Changwon region, and by a DMCII camera with a GSD of 5cm in Suwon respectively. The result shows that the accuracy of parcel demarcation using aerial images is within the tolerance limits of coordinates and areas compared with that of terrestrial surveying. The proposed method using aerial target-based high resolution aerial images is therefore expected to be usefully applied in the agricultural parcel demarcation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.1
• /
• pp.1-10
• /
• 2017

An UAV (Unmanned Aerial Vehicle) is a flight system that is designed to conduct missions without a pilot. Compared to traditional airborne-based photogrammetry, UAV-based photogrammetry is inexpensive and can obtain high-spatial resolution data quickly. In this study, we aimed to classify the land cover using high-spatial resolution images obtained using a UAV. An RGB camera was used to obtain high-spatial resolution orthoimage. For accurate classification, multispectral image about same areas were obtained using a multispectral sensor. A DSM (Digital Surface Model) and a modified NDVI (Normalized Difference Vegetation Index) were generated using images obtained using the RGB camera and multispectral sensor. Pixel-based classification was performed for twelve classes by using the RF (Random Forest) method. The classification accuracy was evaluated based on the error matrix, and it was confirmed that the proposed method effectively classified the area compared to supervised classification using only the RGB image.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.215-218
• /
• 2007

Recently, information-oriented whole domain and scientific management method for nation-wide territory is widly being used due to the remarkable development such as GIS and RS. In addition to this, request for analyzing forest spatial information has been increasing to manage forest resources efficiently. Although forest information using satellite image and GIS has been built to analyze a large amount of forest information scientifically, there are many difficulties to gather information because normally forest area is large and difficult to access.. This research uses high resolution satellite and digital aerial photograph around Kyungju city area to classify forest area, and stratifies forest area through a spot survey and a comparison of sample area. It will be possible for us to draw a more detailed map of forest area than 1/25000 map of forest area through these works.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.555-563
• /
• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.5
• /
• pp.775-784
• /
• 2023

Drone images are being used more and more actively in the fields of surveying and spatial information, and are rapidly replacing existing aerial and satellite images. The technology of quickly acquiring real-time data at low cost and processing it is now being applied to actual industries beyond research. However, there are also problems encountered as this progresses. When high-resolution spatial information is acquired using a general 2D flight plan for a terrain with sever undulations, problems arise due to the difference in resolution of the data. In particular, when a low-altitude high-resolution image is taken using a drone in a mountainous or steep terrain, there may be a problem in image matching due to a resolution difference caused by terrain undulations. This problem occurs because a drone acquires data while flying on a 2D plane at a fixed altitude, just like conventional aerial photography. In order to acquire high-quality 3D data using a drone, the scale difference for the shooting distance should be considered. In addition, in order to obtain facade images of large structures, it is necessary to take images in 3D space. In this study, in order to improve the disadvantages of the 2D flight method, a 3D flight plan was established for the study area, and it was confirmed that high-quality 3D spatial information could be obtained in this way.

• Journal of Korean Society of Rural Planning
• /
• v.15 no.4
• /
• pp.199-211
• /
• 2009

The aim of this paper is to investigate the applicability of high spatial resolution remote sensing images for conducting the rural amenity resources survey. There are a large number of rural amenity resources and field reconnaissance without a sufficient preliminary survey involves a big amount of cost and time even if the data quality cannot always be satisfied with the advanced study. Therefore, a new approach should be considered like the state-of-the-art remote sensing technology to support field survey of rural amenity resources as well as to identify the spatial attributes including the geographical location, pathway, area, and shape. Generally high-resolution satellite or aerial photo images are too expensive to cover a large area and not free of meteorological conditions, but recently rapidly-advanced internet-based image services, such as Google Earth, Microsoft Bing maps, Bluebirds, Daum maps, and so on, are expected to overcome the handicaps. The review of the different services shows that Google Earth would be the most feasible alternative for the survey of rural amenity resources in that it provides powerful tools to build spatial features and the attributes and the data format is completely compatible with other GIS(Geographic information system) software. Hence, this study tried to apply the Google Earth service to interpret the amenity resources and proposed the reformed work process conjugating the internet-based high-resolution images like satellite and aerial photo data.