• Proceedings of the KSRS Conference
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• v.2
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• pp.848-851
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• 2006

Green vegetation is one of the most critical factors for environment conditions thorough modulating evapotranspiration and absorption of solar radiation. Thus, fractional green vegetation cover (FVC) plays an important role in observing and managing environment. Remote sensing provides a seemingly obvious data source for quantifying FVC over large area. Therefore we compared a set of methods for estimating FVC using hyperspectral remote sensing data. For our study, we used Hyperion imagery acquired in April, 2002. In order to achieve our efforts, we analyzed simple NDVI-based method and spectral mixture analysis (SMA) models that were applied a variety of combinations of possible endmembers.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1052-1054
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• 2003

RAZAKSAT is a second micro-satellite mission by Malaysian Satellite Program and is expected for launch in June 2004. Designed to orbit the earth at low-equatorial orbit, RAZAKSAT will meet Malaysia’s immediate needs to rapid data acquisition (real time and more repetitions) to address many operational issues of remote sensing applications, which require availability of current data sets. RAZAKSAT will be among the first remote sensing satellite to orbit the earth at low inclination along the equator, 9$^{\circ}$ with 685km altitude, hence, allows optimal geographical information and environment change within equatorial region be observed with a unique revisit characteristics. The satellite primary payload is MAC, a push-broom type camera with 2.5m of ground sampling distance (GSD) in panchromatic band and 5m of GSD in four multi-spectral bands. This paper describes on the variation of illumination anticipated from simulated RAZAKSAT image, examine its implication to its ground leaving radiances for major applications.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.795-808
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• 2020

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

• Journal of the Korean Professional Engineers Association
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• v.25 no.5
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• pp.58-64
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• 1992

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1171-1173
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• 2003

There are two datasets to estimate the area-mean and time-mean precipitation rate. For one, an array of surface rain gauges represents a series of rods that have to the time axis of the volume. And another data is that of a remote sensing make periodic overpasses at a fixed interval such as radar. The problem of optimally combining data from surface rain gauge data and remote sensed data is considered. In order to combining remote sensed data with Automatic Weather Station (AWS), we use optimal weighting method, which is similar to the method of [2]. They had suggested optimal weights that minimized value of the mean square error. In this paper, optimal weight is evaluated for the cases such as Changma, summer Monsoon, Typhoon and orographic rain.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1359-1361
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• 2003

A set of microwave remote sensing data collected with the newly developed UMass Imaging Wind and Rain Airborne Profiler (IWRAP) during the 2002 Atlantic Hurricane Season was analyzed to further our understanding of the effect of precipitation on scatterometer wind vector retrieval. Coincident surface wind speed and precipitation measurements were provided by the UMass Simultaneous Frequency Microwave Radiometer (SFMR). The differences between the wind estimations from IWRAP and SFMR under precipitation conditions of 0-100mm/hr and wind speed of 0-60m/s was calculated, from which the effect of precipitation on the wind vector retrieval using scatterometry is analyzed qualitatively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.123-125
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• 2003

Satellite IKONOS images are one of important remote sensing data sources as today because of their very high spatial resolution. Their detections for islands and offshore oceanic features with multi-dimension and multi-scales information, specially some small islands, are of great potential. Their application abilities in islands and offshore detections are addressed at the first of the paper. And image processing technologies and the information extracting methodologies are described. Some results on remote sensing of the islands and their nearby object features are shown in details. Discussions and conclusions are carried out simply at the final.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.55-58
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• 2007

The prototype radiometric calibration algorithm of the imagers for IR channels has been developed according to the Weinreb's method. Applying the algorithm to the GOES-12 count data, we have shown that the calibration coefficients (slope and intercept) evaluated by the algorithm gives good agreement with the NESDIS's ones, and that the scanning error due to the scan mirror emissivity and stripe error are almost eliminated by the East/West angle dependent scan-mirror correction and the respective calculation of intercept for each North/South scan line, respectively.

• Current Research on Agriculture and Life Sciences
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• v.31 no.2
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• pp.113-123
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• 2013

The carbon-offset mechanism based on forest management has been recognized as a meaningful tool to sequestrate carbons already existing in the atmosphere. Thus, with an emphasis on the forest-originated carbon-offset mechanism, the accurate measurement of the carbon stock in forests has become important, as carbon credits should be issued proportionally with forest carbon stocks. Various remote sensing techniques have already been developed for measuring forest carbon stocks. Yet, despite the efficiency of remote sensing techniques, the final accuracy of their carbon stock estimations is disputable. Therefore, minimizing the uncertainty embedded in the application of remote sensing techniques is important to prevent questions over the carbon stock evaluation for issuing carbon credits. Accordingly, this study reviews the overall procedures of carbon stock evaluation-related remote sensing techniques and identifies the problematic technical issues when measuring the carbon stock. The procedures are sub-divided into four stages: the characteristics of the remote sensing sensor, data preparation, data analysis, and evaluation. Depending on the choice of technique, there are many disputable issues in each stage, resulting in quite different results for the final carbon stock evaluation. Thus, the establishment of detailed standards for each stageis urgently needed. From a policy-making perspective, the top priority should be given to establishinga standard sampling technique and enhancing the statistical analysis tools.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.277-279
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• 2003

The study utilizes remote sensing as the main monitoring means. With different spatial high-resolution, multichannel ASTER remote sensing image as the main information in Beijing city zone; with regional border and statistical data as auxiliary factor a study between the thermal space distribution character and the underground medium is analyzed based on the GIS logical algorithm and synthetic analysis technology. Results show thermal forming mechanism and the rule of distribution is mainly related to the underground medium and the change of the city distribution. Different underground medium has different degree and intensity influence on the thermal space distribution. Furthermore, urban greenbelt and water areas can reduce the thermal effect and large-scale greenbelt creates green island effect. In addition, Road net, residential area, population density, heat resources and so on have some positive effect on the thermal distribution, which increase the local temperature and intensity on the other hand. It is important to study the thermal distribution and its related factors, which contributes to the plan, construction and development of the city.