• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.463-472
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• 2023

The amount of damage and the area of damage to forest fires are increasing globally, and the effectiveness analysis of the restoration method after the damage is performed insufficient. This study calculated the area of forest fire damage was calculated using Sentinel-2B satellite images and stack map and the intensity of forest fire damage is analyzed according to the forest type. In addition, the vegetation index was calculated using various wavelength bands. Based on the results, the vegetation resilience by the restoration method was quantitatively. As results, areas with a high proportion of coniferous forests suffered high intensity forest fire damage, and areas with a relatively high ratio of mixed and broad-leaved forests tended to have low forest fire damage. Also, artificial forests showed a recovery of about 92.7% compared to before forest fires and natural forests showed a recovery of about 99.6% from the result of analyzing vegetation resilience in artificial and natural forests after forest fires. Accordingly, it was confirmed that natural forests after forest fire damage had superior vegetation resilience compared to artificial forests. It can be proposed that this study is meaningful in providing important information for efficiently restoring the affected target site and the selection criteria for trees to reduce forest fire damage through the evaluation of vegetation resilience by the intensity of forest fire damage and restoration methods.

• Journal of Bio-Environment Control
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• v.22 no.4
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• pp.392-399
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• 2013

This study aimed to investigate responses of photosynthesis, plant growth, and phytochemical contents to different artificial light sources for 'Seneca RZ' and 'Gaugin RZ' two butterhead lettuce (Lactuca sativa L.). In this study, fluorescent lamps (FL), three colors LEDs (red, blue and white, 5 : 4 : 1; RBW) and metalhalide lamps (MH) were used as artificial lighting sources. Photoperiod, air temperature, relative humidity, EC, and pH in a cultivation system were maintained at 16/8 h, $25/15^{\circ}C$, 60~70%, $1.4{\pm}0.2dS{\cdot}m^{-1}$, and $6.0{\pm}0.5$, respectively. The photosynthetic rate of both two butterhead lettuce were the highest under RBW in middle growth stage. However, in late growth stage, the photosynthetic rate of both two butterhead lettuce were higher under RBW and MH than FL. The light sources showed significant results for plant growth but those effects were different to variety. Fresh and dry weight of 'Gaugin RZ' butterhead lettuce under MH were heavier than other lights in all growth stages. Growth of 'Seneca RZ' butterhead lettuce was maximized highest under MH in middle growth stage and FL in late growth stage. In the leaf tissue of 'Seneca RZ' butterhead lettuce, tipburn symptom occurred under all light sources and in the leaf tissue of 'Gaugin RZ' butterhead lettuce, it occurred under two light sources except for fluorescent lamps in late growth stage. kinds of lamp affect plant growth more than plant quality. Relative growth rate of both two butterhead lettuce was faster in middle growth stage than late stage. Growth of 'Gaugin RZ' was shown by kinds of lamp in middle growth stage and but it was not significantly affected by light sources and variety in late stage. Most of the phytochemical contents of two butterhead lettuce were significantly affected by different light sources. Contents of all vitamins showed higher than other light sources on RBW for both two lettuce, especially ${\beta}$-Carotene content of 'Gaugin RZ' was the highest. Plant growth, photosynthesis, and phytochemical contents were observed significant effects by different light sources for two butterhead lettuce but those effects were highly different between variety and kinds of phytochemicals. Therefore, the selection of optimum light source should be considered by variety and kinds of phytochemicals in the plant factory.

• Economic and Environmental Geology
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• v.18 no.4
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• pp.343-355
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• 1985

Spectral reflectivity and microhardness were measured quantitatively on polished surfaces of a selection of bireflecting minerals obtained from several well known metallic deposits. Incremental errors are much higher than decremental errors and errors were found to be lowest in the spectral region close to the green wavelength ($544m{\mu}$). The characteristics of the spectral profile are significant in their control of white light color. The covellite and graphite have reflectivity profiles similar in shape for each principal direction, showing noticeable difference in magnitude between the profiles: The spectral reflectivity of covellite parallel to the extraordinary vibration is higher (R$$\simeq_-$$10%) than that parallel to the ordinary vibration and graphite shows opposite feature. Reflectivity of the enargite and famatinite cut parallel to the cleavage plane is always higher (R$$\simeq_-$$5%) than that of the section cut normal. The optical symmetry of 5 bireflecting minerals was determined by noting the variation in reflectivity at $544m{\mu}$. The data indicate that covellite is optically uniaxial positive and graphite is optically uniaxial negative. The Rm values for enargite and famatinite are clearly closer to the minimum value for the mineral ($R_1$) than to the maximum value ($R_2$) : the minerals can be recognized as optically biaxial positive. Enargite and famatinite cut parallel to cleavage have much higher hardness values (HV=> $200kg/mm^2$) than those cut normal to cleavage. Vickers indentations exhibit characteristic features for all the bireflecting mineral species studied. Broad radicle groupings of the mineral species can be made with regard to the reflectivity microhardness numbers.

• Journal of Korean Society of Forest Science
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• v.102 no.1
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• pp.90-96
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• 2013

This study was conducted to investigate a stability trend within 6 above average and 4 blow average erosion control dams, which were selected by The Korean Association of Soil and Water Conservation and were built in 1990s in Gyeonggi and Gangwon Province. The study was aimed to measure rebound hardness of upstream face, flood way and downstream face from those dams selected by using 'Concrete Test Hammer'. The main purposes of the study are selection of compression strength prediction equation and scope of wavelength, which successfully demonstrate non-destructive test results for erosion control dams. There is an opportunity to increase disaster prevention ability when stability vulnerability of concrete erosion control dam is detected in a timely manner. Results of the compression strength investigation express that there is a consistency with visual inspection of stability that has been processed by The Korean Association of Soil and Water Conservation. We concluded that a prediction equation, which was developed by Architectural Institute of Japan (AIJ), shows highest suitability in Korean erosion control dams when stability investigation is performed. The detailed criteria for the test result are 'stable', 'detail inspection required' and 'poor' for over 300 $kgf/cm^2$, 250~300 $kgf/cm^2$ and below 250 $kgf/cm^2$ respectively. Standards for stability of Korean erosion control dam and a compression strength prediction equation (that corresponds to the standards of the stability) should be established on the basis of chronological data of erosion control dam compression strength. Systematical approach for stability inspection that carries out remodeling or repair when problem on erosion control structures are detected through visual inspection and simple stability test, is necessary for the future disaster prevention.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.