• Korean Journal of Remote Sensing
• /
• v.33 no.6_3
• /
• pp.1233-1242
• /
• 2017

In this study, we tried to analyze deforestation due to forest fire by using KOMPSAT satellite imagery. For deforestation analysis, unsupervised change detection algorithm is applied to multitemporal images. Through ITPCA (ITerative Principal Component Analysis) of NDVI (Normalized Difference Vegetation Index) generated from multitemporal satellite images before and after forest fire, changed areas due to deforestation are extracted. In addition, a post-processing method using SRTM (Shuttle Radar Topographic Mission) data is involved in order to minimize the error of change detection. As a result of the experiment using KOMPSAT-2 and 3 images, it was confirmed that changed areas due to deforestation can be efficiently extracted.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1467-1475
• /
• 2023

The public-interest direct payment program involves providing direct payments to agricultural producers and rural residents through public funds, premised on performing public functions such as environmental conservation, stable food supply, and maintaining rural communities via agricultural activities. Scientific estimation of crop cultivation areas and production levels is crucial for formulating agricultural policies linked to regulating food supply, which increasingly impacts the national economy. Conducting comprehensive on-site inspections for compliance monitoring of direct payment programs has shown very low efficiency in relation to budget and time. The expansion of areas subject to compliance monitoring and various challenges in on-site inspections necessitate streamlining current monitoring methods and devising effective strategies. As a solution, the application of Remote Sensing technology and spatial information utilization, allowing swift acquisition of necessary information for policies without overall on-site visits, is being discussed as an efficient compliance monitoring method. Therefore, this study evaluated the potential use of remote sensing for improving operational efficiency in monitoring compliance with public-interest direct payment programs. Using satellite images during farming seasons in Gimje and Hapcheon, vegetation indices and spatial variations were utilized to identify cultivated areas, presence of mixed crops, validated against on-site inspection data.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_2
• /
• pp.929-937
• /
• 2020

In this manuscript, the UNet++ model, which is one of the representative deep learning techniques for semantic segmentation, was used to detect changes in temporal satellite images. To analyze the learning results according to various loss functions, we evaluated the change detection results using trained UNet++ models by binary cross entropy and the Jaccard coefficient. In addition, the learning results of the deep learning model were analyzed compared to existing pixel-based change detection algorithms by using WorldView-3 images. In the experiment, it was confirmed that the performance of the deep learning model could be determined depending on the characteristics of the loss function, but it showed better results compared to the existing techniques.

• Korean Journal of Remote Sensing
• /
• v.24 no.4
• /
• pp.341-349
• /
• 2008

This study proposes new automatic thresholding method, which is important step for detecting binary change/non-change information using satellite images. Result value through pixel-based similarity measurement is calculated cumulatively with regular interval, and thresholding is pointed at the steep slope position. The proposed method is assessed in comparison with expectation-maximization algorithm and coner method using synthetic images, ALI images, and Hyperion images. Throughout the results, we validated that our method can guarantee the similar accuracy with previous algorithms. It is simpler than EM algorithm, and can be applied to the binormal histogram unlike the coner method.

• Korean Journal of Remote Sensing
• /
• v.24 no.1
• /
• pp.35-43
• /
• 2008

The purpose of this study is to evaluate the hydrological impact due to temporal land cover change by gradual urbanization of upstream watershed of Pyeongtaek gauging station of Anseong-cheon. WMS HEC-1 was adopted, and OEM with 200 m resolution and hydrologic soil group from 1:50,000 scale soil map were prepared. Land covers of 1986, 1990, 1994 and 1999 Landsat TM images were classified by maximum likelihood method. The watershed showed a trend that forest & paddy areas decreased and urban/residential area gradually increased during the four selected years. The model was calibrated at 2 locations (Pyeonglaek and Gongdo) by comparing observed with simulated discharge results for 5 summer storm events from 1998 to 2001. The watershed average CN values varied from 61.7 to 62.3 for the 4 selected years. To identify the impact of streamflow by temporal area change of a target land use, a simple evaluation method that the CN values of areas except the target land use are unified as one representative CN value was suggested. By applying the method, watershed average CN value was affected in the order of paddy, forest and urban/residential, respectively.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2000.04b
• /
• pp.176-179
• /
• 2000

In the recognition of the gases using the quartz crystal microbalance (QCM) coated with the film materials, it is important to obtain the recognition ability of gases, and the stability of film coated above the QCM. Especially, the thickness of film coated above the QCM is decreased according with the using circumstance and time of QCM gas sensor. Therefore, the sensing chararcteristics of film is changed with these. In this paper, we coated the lipid PC (Phosphatidyl Choline) materials varing with the blended amount of PVC(Poly Vinyl Chloride) and solution (Tetra Hydrofan:THF) above QCM to obtain the stability of lipid PC film. QCM gas sensors coated with film materials were measured the frequency change in the chamber of stationary gas sensing system injected 1-hexane, ethyl acetate, ethanol and benzene of $20{\mu}{\ell}$, respectively. We obtained the principal component analysis (PCA) from the frequency change due to the absorption of gas. Also, we measured the degradation characteristics of QCM gas sensor to show the properties of stability.

• Textile Coloration and Finishing
• /
• v.27 no.2
• /
• pp.105-112
• /
• 2015

In order to detect gas phase strong acid on fabrics, a hexyl-substituted monoazo yellow dye, which was the modified form of a conventional pH-indicating dye, Methyl Yellow, was studied in view of acid-gas sensing properties and its fastness. The dye was printed on polypropylene non-wovens for protective coveralls and examined under various conditions of strong acid such as hydrochloric acid. The dye showed color change from yellow to red on exposure to gas phase hydrochloric acid as low concentration as 1~3 ppm very instantly. Considering reuse of the dye-printed non-wovens, the repeatability of color change was tested on the same sample for 50 repeats and 100 days. The acid-gas sensing function was maintained almost the same level of initial performance. The color fastness of the dye on polypropylene non-wovens was very good showing higher than ratings 4 except for 3~4 to rubbing under wet condition.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.102-105
• /
• 2006

Forest canopy density is an essentially important for maintaining the diversify flora and fauna in the tropic. But, the natural and human disturbances have an influence over the inconsistency of forest canopy density. So, forest canopy density (FCD) has been threatened in the tropic since a decade. The objective of this study was to examine the dynamics change of the forest canopy density in tropical forest Chitwan, Nepal combine with field survey and remote sensing data. The field survey data of 2001 such as canopy cover percentage, dbh so on and some human disturbances were used. Similarly, Landsat TM 1988 and ETM+ 2001 have also used to predict the dynamic changes of the FCD over the period. Moreover, nonparametric Kruskal- Wallis test has performed for the validation of the results. Data analysis revealed that very few factors i.e. the number of trees, path, and fire had realized statistically significance at P=<0.05. Therefore we concluded that detail analysis could be needed incorporate with additional socioeconomic, climatic, biophysical and institutional factors for the better understanding of the forest canopy dynamic in particular location.

• The Journal of Korea Robotics Society
• /
• v.12 no.1
• /
• pp.26-32
• /
• 2017

Previous shape sensors including bend sensors and optic fiber based sensors are widely used in various applications including goniometer and surgical robots. But theses sensors have large nonlinearity, limited in the range of sensing curvature, and sometimes are expensive. This study suggests a new concept of bend sensor using cable-conduit which consists of the outer sheath and the inner wire. The outer sheath is made of helical coil whose length of the central line changes as the sheath bends. This length change of the central line can be measured with the length change of the inner cable. The modeling and the experimental results show that the output signal of the proposed sensor is linearly related with the bend angle of the sheath with root mean square error of 5.3% of $450^{\circ}$ sensing range. Also the polynomial calibration of the sensor can decrease the root mean square error to 2.1% of the full sensing range.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.965-967
• /
• 2003

Information on forest volume, forest coverage and biomass are important for developing global perspectives about CO$_{2}$ concentration changes. Forest biomass cannot be directly measured from space yet, but remotely sensed greenness can be used to estimate biomass on decadal and longer time scales in regions of distinct seasonality, as in the north. Hence, in this research, numerical methods were used to estimate forest biomass in higher northern regions. A regression model linking Normalized Difference Vegetation Index(NDVI), to forest biomass extracted from SPOT/4 VEGETATION data and PAL 8km data in regional and continental area (N40-N70) respectively. Statistical tests indicated that the regression model can be used to represent the changes of forest biomass carbon pools and sinks at high latitude regions over years 1982-2000. This study suggests that the implementation of estimation of biomass based on 8-km resolution NOAA/AVHRR PAL and SPOT-4/VEGETATION data could be detected over a range of land cover change processes of interest for global biomass change studies.