• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.3
• /
• pp.51-61
• /
• 2020

Drought events are not clear when those start and end compared with other natural disasters. Because drought events have different timing and severity of damage depending on the region, various studies are being conducted using satellite images to identify regional drought occurrence differences. In this study, we investigated the applicability of drought assessment using the Evaporative Stress Index (ESI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The ESI is an indicator of agricultural drought that describes anomalies in actual and reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of Land Surface Temperature (LST) and Leaf Area Index (LAI). However, these approaches have a limited spatial resolution when mapping detailed vegetation stress caused by drought, and drought hazard in the actual crop cultivation areas due to the small crop cultivation in South Korea. For these reasons, the development of a drought index that provides detailed higher resolution ESI, a 500 m resolution image is essential to improve the country's drought monitoring capabilities. The newly calculated ESI was verified through the existing 5 km resolution ESI and historical records for drought impacts. This study evaluates the performance of the recently developed 500 m resolution ESI for severe and extreme drought events that occurred in South Korea in 2001, 2009, 2014, and 2017. As a result, the two ES Is showed high correlation and tendency using Receiver Operating Characteristics (ROC) analysis. In addition, it will provide the necessary information on the spatial resolution to evaluate regional drought hazard assessment and and the small-scale cultivation area across South Korea.

• Journal of Conservation Science
• /
• v.31 no.4
• /
• pp.395-402
• /
• 2015

This study was considered utilization of hyperspectral image analysis for monitoring. Accordingly we applied to stone cultural properties to data correction methods, image classification techniques, NDVI computation techniques using hyperspectral image. As the results, hyperspectral image analysis was possible making detailed deterioration map, accurate calculation of deterioration rate, mapping of normalized difference vegetation index on the basis of reflectance of each materials. Therefore, hyperspectral image analysis will be used for effective monitoring techniques of stone cultural heritages.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.spc4_2
• /
• pp.421-430
• /
• 2014

Aerial imagery, Satellite imaging and Hyperspectral imaging(HSI) are widely using at mapping those of agriculture, woodland, waters shoreline, and land cover, but are rarely applied at the Cadastre. There are many study cases on the overlay of aerial imagery and satellite imaging with Cadastral Map and the upgrade and registration of Cadastre' Land Category, however, reported as successful. Therefore, this study has been aimed to show the use of the Hyperspectral Imaging technology for Cadastre, especially for the land category. Also, the HSI sensor could function as a geospatial acquisition tool for error checks of the existed land categories, and as a helpful tool for acquiring the attributes and spatial data, such as the agriculture, soil, and vegetation, etc. This result indicates that HSI sensor can implement the Multipurpse Cadastre(MPC) by fusing with the cadastral information.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.1
• /
• pp.15-22
• /
• 2015

To create a wind resource map, we need a contour map, a roughness map and wind data. We need a land cover map for the roughness map of these data. A land cover map represents the area showing similar characteristics after color indexing based on the scientific method. The features of land cover is classified by Remote sensing technique. In this study, we verified the application of the NDVI technique is reasonable after we created the wind resource map using roughness maps by unsupervised classification and NDVI technique. As a result, the wind resource map using the NDVI technique showed a 60% accordance rate and difference in class less than one. From the results, The NDVI technique is found alternative to create roughness maps by the unsupervised classification.

• Korean Journal of Soil Science and Fertilizer
• /
• v.49 no.5
• /
• pp.495-502
• /
• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.4
• /
• pp.471-476
• /
• 2010

This study aimed at monitoring, mapping, and assessing the land degradation in the desert area. In this research, the Landsat TM and ETM+ imageries to assess the extent of land degradation for study area during the period from 1991 to 2007. Were used to study supervized, unsupervized classfication and NDVI land cover changes in the desert area in Mongolia. The classified map consists of five classes of water, vegetation, slight desertification, middle desertification and sever desertification. It shows that for determination classfication methods and NDVI, desertification map of the study area are prepared. The result showed accounting for a clear deterioration in vegetative cover, an increase of sever desertification and a decrease in middle desertification and slight desertification respectively of the total study area.

• The Journal of Engineering Geology
• /
• v.24 no.1
• /
• pp.123-135
• /
• 2014

Earthquakes can cause serious loss of life and significant property damage. Thus, the study of active faults is important in evaluating future fault activity and hazards caused by future earthquake events. Structural mapping and the tracing of active faults are the primary steps in studies of active faults. Until now, active faults in South Korea have been mapped using aerial photography, satellite images, and low-quality DEMs. Lineament analysis as a means of identifying active faults is relatively difficult in Korea due to geological characteristics (weak tectonic activity) and dense vegetation cover. In this paper, we introduce the basic concept of the LiDAR technique (a new prospective remote sensing method) and a data analysis method that can overcome these problems. This paper will contribute to a better understanding of the airborne LiDAR technique and its application to South Korea. Some preliminary results from Korean and USA LiDAR data show the usefulness of this technique for tracing lineaments, active faults, and terraces in South Korea.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_3
• /
• pp.1109-1123
• /
• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Korean Journal of Environment and Ecology
• /
• v.26 no.4
• /
• pp.559-575
• /
• 2012

This study, targeting Namhan Mountain Fortress which was designated as a No. 57 national historic site and placed on the World Heritage Tentative List in 2010, was intended to identify the change of vegetation structures by reviewing past references, pictures, research data and additionally conducting a site survey. Also, it was designed to draw up measures for restoring vegetation suitable for historically and culturally valuable Namhan Mountain Fortress. According to the biotope mapping of study site, Quercus spp. forest distributed a greatest part of area with 40.8% of $2,611,823m^2$. Pinus densiflora forest, highly likely to go through ecological succession, was dispersed in the whole region of Cheongryangsan, the area from West Gate to North Gate and the ranges between South Gate to Cheongryangsan with taking 16.5%. Pinus densiflora forest with a low probability of succession amounted to 4.7% and was dispersed mainly in the forest behind Namhansan elementary school. Pinus densiflora going on the ecological succession is distributed a portion of 2.9%. And the currently dying out Pinus densiflora forest amounted to 2.1%. As a result of analysis of the vegetation structure for 19 years, the succession from Pinus densiflora forest to Pinus densiflora and succession from Quercus spp. mixed forest to Quercus spp. forest to Carpinus laxiflora forest were predicted. Additionally, Quercus spp. expanded its dominance over time. According to the characteristics of each classified zone, the site was categorized into $553,508m^2$ area of Pinus densiflora forest area for the landscape maintenance, $114,293m^2$ area of Pinus densiflora forest area for the landscape restoration, $205,306m^2$ area of Pinus densiflora forest area for the disclimax, and $1,169,973m^2$ area of Pinus densiflora forest area for inducing ecological succession.

• Korean Journal of Environment and Ecology
• /
• v.27 no.6
• /
• pp.704-717
• /
• 2013

This study aims to provide basic data for management and prevention of infection damage by Oak wilt disease through mapping method of status with infected level in damaged area of Bukhansan National Park. Survey was carried out in the distributed area of oak trees with mapping unit of polygon of actual vegetation and mapped of infection ratio and infection index applying weight according to infected level. Infection ratio of oak trees in Bukhansan National Park was 58.5%, and lightly damaged ratio was 29.6%, half of the damaged ratio was 16.1%, seriously damaged ratio was 8.8% and withered ratio was 4.1%. It was serious to be infected from Beomgol ridge in Wondobong district to Hyeongjaebong in Jeongrung district. Although the infected ratio of the western part of Songchu district, Sanseong district and Gugi district centering main ridge of Bukhansan National Park was low, it of ridge and main valley was high. Infection index of hardly damaged area was 39.1% of whole area, and slightly damaged area was 41.0%, half of the damaged area was 16.1%, seriously damaged area was 3.3% and alarmed withering area was 0.4%. Infection index was high around Musugol valley in Dobong district and Jaunbong, and it of Bohyunbong of Jeongrung district and the part of Hyojari valley of Sanseong district was serious. Predicted numbers of the trees affected Oak wilt disease compared to the distributed area of oak trees was 1,585,937 trees among 2,709,147 trees of Quercus spp. 352,931 trees among the 306,161 trees of oak were infected in Woi district, the most seriously infected area and 53,141 trees among the 145,747 trees of oak was infected in Gugi district, the most slightly infected area.