• Title/Summary/Keyword: Korean Journal of Remote Sensing

Search Result 3,010, Processing Time 0.025 seconds

Assessment of riparian buffers for reducing pollution according to land-cover pattern using RS and GIS

  • Ha, Sung-Ryong;Lee, Seung-Chul;Ko, Chang-Hwan;Jo, Yun-Won
    • Korean Journal of Remote Sensing
    • /
    • v.22 no.5
    • /
    • pp.445-449
    • /
    • 2006
  • Diffuse pollution has been considering as a major source of the quality deterioration of water resources. The establishment of riparian vegetation strips or buffers along those areas of water bodies is used to reduce the threat of diffuse pollution. Remote sensing offers a means by which critical areas could be identified, so that subsequent action toward the establishment of riparian zones can be taken. On the behalf of KOMPSAT-2 satellite imagery as a high resolution spatial data, Landsat TM satellite data are used to aquire the land cover for the riparian buffers studied. This investigation aims to assess the riparian buffers established on the upper Geum river as a pollution mitigation. Through comparing the delineation of riparian buffer zones developed with the existing zones established by the government, we can find the critical distortion points of the existing riparian buffer zone.

A Study on the Subdivision of Water Body in Watersheds Classified by Remote Sensing

  • Choi, Hyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.38 no.2
    • /
    • pp.87-95
    • /
    • 2020
  • South korea has been developing and managing the complete dimensions, around the rivers to rapid economic growth. In Korea, where water resources are scarce, administration and work are complicated and diversified in the computerization of related facilities and hydrologic data due to the indiscriminate development of river facilities. In general, dividing the water system based on object in remote sensing is relatively accurate in the image with the same spectral characteristics. However, the distinction between the reservoir and the river must be made manually due to the characteristics of remote sensing. Therefore, this study performed three classifications using GIS (Geographic Information System) to classify reservoirs and rivers. For the purpose of accuracy analysis, the land cover map provided by EGIS (Environmental Geographic Information Service) was used to evaluate the accuracy, and the average of 85.63% was found to be 75.40% of rivers, 89.50% of reservoirs, and 92.00% of others.

A Sequential LiDAR Waveform Decomposition Algorithm

  • Jung, Jin-Ha;Crawford, Melba M.;Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
    • /
    • v.26 no.6
    • /
    • pp.681-691
    • /
    • 2010
  • LiDAR waveform decomposition plays an important role in LiDAR data processing since the resulting decomposed components are assumed to represent reflection surfaces within waveform footprints and the decomposition results ultimately affect the interpretation of LiDAR waveform data. Decomposing the waveform into a mixture of Gaussians involves two related problems; 1) determining the number of Gaussian components in the waveform, and 2) estimating the parameters of each Gaussian component of the mixture. Previous studies estimated the number of components in the mixture before the parameter optimization step, and it tended to suggest a larger number of components than is required due to the inherent noise embedded in the waveform data. In order to tackle these issues, a new LiDAR waveform decomposition algorithm based on the sequential approach has been proposed in this study and applied to the ICESat waveform data. Experimental results indicated that the proposed algorithm utilized a smaller number of components to decompose waveforms, while resulting IMP value is higher than the GLA14 products.

Upwelling Proxy Improvement and Validation Using Satellite Remote Sensing along Southwest of the East Sea: Case Study in 2019

  • Kim, Deoksu;Bae, Dukwon;Choi, Jang-Geun;Jo, Young-Heon
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.4
    • /
    • pp.387-394
    • /
    • 2022
  • Coastal upwelling is a significantly imperative process for understanding the interactions between physical and ecological processes and has been investigated incessantly. In this study, we explored the upwelling index, specifically upwelling age (UA). UA enabled us to observe the initiating, sustaining, and decaying upwelling processes. Although the sensitivity of many other geophysical parameters to estimate UA has been investigated, the wind direction has not been evaluated. Thus, we assessed the appropriate wind direction for the UA and obtained efficient upwelling signals from the four coastal stations. Furthermore, we applied the UA and compared it with the satellite sea level anomaly, sea surface temperature, and chlorophyll-a changes to validate how UA depicts their spatial extents. Thus, UA can predict the timing of coastal upwelling events using predicted geophysical parameters.

Future Trends in Microcomputer Image Processing Technology

  • Yang, Young-Kyu;Miller, Lee-D.
    • Korean Journal of Remote Sensing
    • /
    • v.2 no.1
    • /
    • pp.35-47
    • /
    • 1986
  • The progress in computer technology has significantly improved the capabilities of the microcomputer image processing systems and brought down their hardware costs. This on-going trend of technological development seems to bring further substantive improvements in microcomputer image processing and decreasing hardware costs. The technical development in microcomputer image processing system including VLSI technology, semiconductor memory, disk and tape storage, and image display subsystems have been reviewed and their future trend have been projected. The impact of this technology to the development of image processing has been assessed in the time period of immediate future (2-3 years) and near future (5 years).

Radar Remote Sensing of Soil Moisture and Surface Roughness for Vegetated Surfaces

  • Oh, Yi-Sok
    • Korean Journal of Remote Sensing
    • /
    • v.24 no.5
    • /
    • pp.427-436
    • /
    • 2008
  • This paper presents radar remote sensing of soil moisture and surface roughness for vegetated surfaces. A precise volume scattering model for a vegetated surface is derived based on the first-order radiative transfer technique. At first, the scattering mechanisms of the scattering model are analyzed for various conditions of the vegetation canopies. Then, the scattering model is simplified step by step for developing an appropriate inversion algorithm. For verifying the scattering model and the inversion algorithm, the polarimetric backscattering coefficients at 1.85 GHz, as well as the ground truth data, of a tall-grass field are measured for various soil moisture conditions. The genetic algorithm is employed in the inversion algorithm for retrieving soil moisture and surface roughness from the radar measurements. It is found that the scattering model agrees quite well with the measurements. It is also found that the retrieved soil moisture and surface roughness parameters agree well with the field-measured ground truth data.

Biotop Mapping Using High-Resolution Satellite Remote Sensing Data, GIS and GPS

  • Shin Dong-Hoon;Lee Kyoo-Seock
    • Korean Journal of Remote Sensing
    • /
    • v.20 no.5
    • /
    • pp.329-335
    • /
    • 2004
  • Biotop map can be utilized for nature conservation and assessment of environmental impact for human activities in urban area. High resolution satellite images such as IKONOS and KOMPSAT1-EOC were interpreted to classify land use, hydrology, impermeable pavement ratio and vegetation for biotop mapping. Wildlife habitat map and detailed vegetation map obtained from former study results were used as ground truth data. Vegetation was investigated directly for the area where the detailed vegetation map is not available. All these maps were combined and the boundaries were delineated to produce the biotop map. Within the boundary, the characteristics of each polygon were identified, and named. This study investigates the possibility of biotop mapping using high resolution satellite remote sensing data together with field data with the goal of contributing to nature conservation in urban area.

Evaluation of Geo-based Image Fusion on Mobile Cloud Environment using Histogram Similarity Analysis

  • Lee, Kiwon;Kang, Sanggoo
    • Korean Journal of Remote Sensing
    • /
    • v.31 no.1
    • /
    • pp.1-9
    • /
    • 2015
  • Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

Automatic Road Extraction by Gradient Direction Profile Algorithm (GDPA) using High-Resolution Satellite Imagery: Experiment Study

  • Lee, Ki-Won;Yu, Young-Chul;Lee, Bong-Gyu
    • 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.