• Korean Journal of Remote Sensing
• /
• v.19 no.5
• /
• pp.393-402
• /
• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.238-240
• /
• 2003

As remote sensing is weighty in GIS updating, it is indispensable to get spatial information quickly and exactly. In this study, we have designed and implemented the program by two algorithms of GDPA (Gradient Direction Profile Analysis) and Hough transformation to extract linear features automatically from high-resolution imagery. We applied the software to embody both algorithms to KOMPSAT-EOC, IKONOS, and Landsat-ETM and made a comparative study of results.

• Korean Journal of Remote Sensing
• /
• v.20 no.4
• /
• pp.261-274
• /
• 2004

The feature extraction using remotely sensed imagery has been recognized one of the important tasks in remote sensing applications. As the high-resolution imagery are widely used to the engineering purposes, need of more accurate feature information also is increasing. Especially, in case of the automatic extraction of linear feature such as road using mid or low-resolution imagery, several techniques was developed and applied in the mean time. But quantitatively comparative analysis of techniques and case studies for high-resolution imagery is rare. In this study, we implemented a computer program to perform and compare GDPA (Gradient Direction Profile Analysis) algorithm and Hough transformation. Also the results of applying two techniques to some images were compared with road centerline layers and boundary layers of digital map and presented. For quantitative comparison, the ranking method using commission error and omission error was used. As results, Hough transform had high accuracy over 20% on the average. As for execution speed, GDPA shows main advantage over Hough transform. But the accuracy was not remarkable difference between GDPA and Hough transform, when the noise removal was app]ied to the result of GDPA. In conclusion, it is expected that GDPA have more advantage than Hough transform in the application side.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.775-779
• /
• 2002

Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.243-246
• /
• 2006

Wavelet approach is regarded as a useful methodology for geo-environment analysis with respect to spatial objects with periodicity and spatial pattern, compared to autocorrelation analysis, Fourier analysis, variogram analysis and so on. However, there are a few case studies for geo-lineament characterization with the actual geo-based information such as remotely sensed imagery and DEM. In this study, wavelet approach in the Uiseung caldera region are carried out to delineate characterization for geolineament spatial pattern. There are high possibilities of the development of radial lineaments from the centre of round crater due to the eruption of a volcano and the subsidence of a crater. We have grasped the directionality of the whole linear structures of the caldera via rose diagram, and then performed wavelet analysis on the profiles of orthogonal directions for main directions of the lineaments. The result of this study is likely to be used as a fundamental data in order to grasp the outline of caldera structure prior to the close estimation