Journal of the Korean Society of Environmental Restoration Technology
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v.13
no.3
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pp.73-83
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2010
A technology using continuous fiber soil reinforcement system for the creation of ecological restoration in a damaged area has been developed and introduced. The continuous fiber soil reinforcement system (Geofiber system) is an environmentally friendly slope protection technique that continuous fiber soil reinforced layers are constructed with green plantation on cut slope. The characteristics of this system in terms of the strength and hydraulic performance, and the vegetation were investigated in this study. The main objectives of this comparative study was to quantify the potential contribution of geofiber system for the revegetation on the cut slope in a damaged area. A Geofiber system was constructed to reinforce the lower layer of slopes and revegetation methods including wood chips were carried out on the upper layer by machineries. The results of monitoring during 3 years on cut slopes were as follows : 1) All the quadrat existed in the proper range for vegetation. 2) Species richness was 4.4 (site-1) and 18.5 (site-2) respectively. 3) The averaged coverage rates of quadrats was 90%. It is remarkable that the continuous fiber soil reinforcement system would be capable of applying to a damaged area and also would serve maintaining a healthier environment for floras. However, it behooves to continue monitoring on succession of vegetation for ecological restoration.
Journal of the Korean Society of Environmental Restoration Technology
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v.13
no.1
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pp.47-56
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2010
The main objectives of this comparative study were 1) to quantify the potential contribution of wood chips to revegetation on the cut slope in a constructed area, 2) to compare the floristic similarity of species composition whether existing of wood chips in the soil media or not. Wood chips were combined with soil media in the ratio of 30%. The thin layer (1 cm, 3 cm) soil media revegetation methods and the thick layer (10 cm) soil media revegetation method were constructed on the cut slopes by machineries respectively. Also, comparative experiments the existence of wood chips in the soil media were conducted to evaluate the effects of wood chips on revegetation works. The total size of quadrat was $300m^2$ ($100m^2{\times}3$). The results of monitoring for 3 years on cut slopes were as follows: 1) All the quadrat existed in the proper range for vegetation. 2) Species richness of quadrat including wood chips was 10% more than those of commercial soil medias. 3) The coverage rates of quadrat including wood chips were similar or superior to those of conventional methods. It can be concluded that the use of wood chips would be effective to promote establishment of diverse landscape and vegetation. However, it behooves to continue monitoring on succession of vegetation for ecological restoration. Finally, adequate wood chips deposit and gathering methods should be studied properly.
Journal of The Korean Society of Agricultural Engineers
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v.63
no.6
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pp.101-115
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2021
The purpose of this study is to evaluate the compatibility of the vegetation index between the two satellites and the applicability of agricultural monitoring by comparing and verifying NDVI (Normalized Difference Vegetation Index) based on Sentinel-2 and Terra MODIS (Moderate Resolution Imaging Spectroradiometer). Terra MODIS NDVI utilized 16-day MOD13Q1 data with 250 m spatial resolution, and Sentinel-2 NDVI utilized 10-day Level-2A BOA (Bottom Of Atmosphere) data with 10 m spatial resolution. To compare both NDVI, Sentinel-2 NDVIs were reproduced at 16-day intervals using the MVC (Maximum Value Composite) technique. As a result of time series NDVIs based on two satellites for 2019 and compare by land cover, the average R2 (Coefficient of determination) and RMSE (Root Mean Square Error) of the entire land cover were 0.86 and 0.11, which indicates that Sentinel-2 NDVI and MODIS NDVI had a high correlation. MODIS NDVI is overestimated than Sentinel-2 NDVI for all land cover due to coarse spatial resolution. The high-resolution Sentinel-2 NDVI was found to reflect the characteristics of each land cover better than the MODIS NDVI because it has a higher discrimination ability for subdivided land cover and land cover with a small area range.
UAV in the agricultural application are capable of collecting ultra-high resolution image. It is possible to obtain timeliness images for phenological phases of the crop. However, the UAV uses a variety of sensors and multi-temporal images according to the environment. Therefore, it is essential to use normalized image data for time series image application for crop monitoring. This study analyzed the variability of UAV reflectance and vegetation index according to Aviation Image Making Environment to utilize the UAV multispectral image for agricultural monitoring time series. The variability of the reflectance according to environmental factors such as altitude, direction, time, and cloud was very large, ranging from 8% to 11%, but the vegetation index variability was stable, ranging from 1% to 5%. This phenomenon is believed to have various causes such as the characteristics of the UAV multispectral sensor and the normalization of the post-processing program. In order to utilize the time series of unmanned aerial vehicles, it is recommended to use the same ratio function as the vegetation index, and it is recommended to minimize the variability of time series images by setting the same time, altitude and direction as possible.
Kim, Dongyeob;Im, Sangjun;Kweon, Hyuck-Min;Yim, Jaehong
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.5B
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pp.519-524
/
2010
This study was carried out to select suitable plants for beach revegetation as a preliminary study for quantifying the effect of decreasing sand movement. After planting some herbal plants in field, monitoring of temporal change of vegetation coverage which was index of the growth rate was conducted. Through literature reviews, 24 candidate plants for beach revegetation were selected, then seven species of them, Peucedanum japonicum Thunb., Dianthus japonicus Thunb. ex Murray, Sedum oryzifolium Makino, Sedum takesimense Nakai, Sedum spectabile Boreau, Farfugium japonicum (L.) Kitam., Aster sphathulifolius Maxim. were picked through salinity tolerance experiments in laboratory. Seven species selected by salinity tolerance experiments and two additional herbal plants, Prunella vulgaris var. lilacina Nakai and Linaria vulgaris Mill., not the candidates, were nine final species which were planted in the beach around Osan port, Uljin, Korea. The changes of vegetation coverage of each species were investigated from photos periodically taken for about a year using image processing methods. As a result of the monitoring, Sedum takesimensei, Dianthus japonicus and Aster sphathulifolius were observed with high coverages during the whole monitoring while Prunella vulgaris var. lilacina and Linaria vulgaris were observed with low coverage during the same period. Consequently, Sedum takesimensei, Dianthus japonicus and Aster sphathulifolius were concluded as the most suitable plants for beach revegetation. Furthur study to quantify the effects of decreasing sand movement by the selected species is needed.
Kim, Chang-Hwan;Oh, Jang-Geun;Lee, Nam-Sook;Choi, Young-Eun;Song, Myoung-Jun
Korean Journal of Ecology and Environment
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v.48
no.1
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pp.61-67
/
2015
This study, which was conducted from Apr. 2013 to Jan. 2014, was carried out as part of a project of making a more detailed ecological zoning map with 1/5,000 scale. The necessity of electronic vegetation map with large scale has arisen in order to make the best use of basic research findings on resource monitoring of National Parks and to enhance efficiency in National Park management. In order to improve accuracy and speed of vegetation research process, the data base for vegetation research was categorized into five groups, namely broad-leaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. And then a vegetation map for vegetation research was created for the research on the site. What is in the database for vegetation research and the vegetation map reflecting findings from vegetation research showed similar distribution rate for broad-leaved forest with 71.965% and 71.184%, respectively. The distribution rate of coniferous forest (16.010%, 15.747%), mixed forest (10.619%, 12.085%), and rock vegetation (0.015%, 0.002%) did not have much difference. In a detailed vegetation map reflecting vegetation research findings, the broad-leaved mountain forest was the most widely distributed with 60.096% based on the physiognomy classification. It was followed by mountain coniferous forest (16.332%), mountain valley forest (15.887%), and plantation forest (3.558%) As for vegetation conservation classification evaluated in the national park, grade I and grade II areas took up 200.44 km2, 61.80% and 108.80 km2, 33.55% respectively. The combined area of these two amounts to 95.35%, making this area the first grade area in ecological nature status. This means that this area is highly worth preserving its vegetation. The high rate of grade I area such as climax forests, unique vegetation, and subalpine vegetation seems to be attributable to diverse innate characteristics of Odaesan National Park, high altitude, low level of artificial disturbance, the subalpine zone formed on the ridge of the mountain top, and their vegetation formation, which reflects climatic and geological characteristics, despite continuous disturbance by mountain climbing.
In this study, a quantitative assessment was carried out in order to identify the agricultural drought in time and space using the Terra MODIS remote sensing data for the agricultural drought. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were selected by MOD13A3 image which shows the changes in vegetation conditions. The land cover classification was made to show only vegetation excluding water and urbanized areas in order to collect the land information efficiently by Type1 of MCD12Q1 images. NDVI and EVI index calculated using land cover classification indicates the strong seasonal tendency. Therefore, standardized Vegetation Stress Index Anomaly (VSIA) of EVI were used to estimated the medium-scale regions in Korea during the extreme drought year 2001. In addition, the agricultural drought damages were investigated in the country's past, and it was calculated based on the Standardized Precipitation Index (SPI) using the data of the ground stations. The VSIA were compared with SPI based on historical drought in Korea and application for drought assessment was made by temporal and spatial correlation analysis to diagnose the properties of agricultural droughts in Korea.
In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.
Nam, Won-Ho;Tadesse, Tsegaye;Wardlow, Brian D.;Jang, Min-Won;Hong, Suk-Young
Journal of The Korean Society of Agricultural Engineers
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v.57
no.4
/
pp.1-9
/
2015
The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.
This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.
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