• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.115-123
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• 2008

Evapotranspiration mapping using both meteorological ground-based measurements and satellite-derived information has been widely studied during the last few decades and various methods have been developed for this purpose. It is significant and necessary to estimate regional evapotranspiration (ET) distribution in the hydrology and water resource research. The study focused on analyzing the surface ET of Chungbuk region using Landsat 7 ETM imagery. For this process, we estimated the regional daily evapotranspiration on May 8, 2000. The estimation of surface evapotranspiration is based on the relationship between Temperature Vegetation Dryness Index (TVDI) and Morton's actual ET. TVDI is the relational expression between Normalized Difference of Vegetation Index (NDVI) and Land Surface Temperature (LST). The distribution of NDVI corresponds well with that of land-use/land cover in Chungbuk. The LST of several part of city in Chungbuk region is higher in comparison with the averaged LST. And TVDI corresponds too well with that of land cover/land use in Chungbuk region. The low evapotranspiration availability is distinguished over the large city like Cheongju-si, Chungju-si and the difference of evapotranspiration availability on forest and paddy is high.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.375-381
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• 2014

Soil moisture is an essential satellite-driven variable for understanding hydrologic, pedologic and geomorphic processes. The European Space Agency (ESA) has endorsed soil moisture as one of Climate Change Initiates (CCI) and had merged multi-satellites over 30 years. The $0.25^{\circ}$ coarse resolution soil moisture satellite data showed correlations with variables of a water stress index, Temperature-Vegetation Dryness Index (TVDI), from a stepwise regression analysis. The ancillary data from TVDI, Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS were inputted to a multi-regression analysis for estimating the surface soil moisture. The estimated soil moisture was validated with in-situ soil moisture data from April, 2012 to March, 2013 at Andong observation sites in South Korea. The soil moisture estimated using satellite-based LST and NDVI showed a good agreement with the observed ground data that this approach is plausible to define spatial distribution of surface soil moisture.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1197-1208
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• 2019

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation.

• Journal of the Korean earth science society
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• v.27 no.7
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• pp.787-803
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• 2006

The drought index has been developed, based on a $8.6{\mu}m$ surface emissivity in the $8-12{\mu}m$ MODIS channels over the African Sahel region (10-20 N, 13 W-35 W) and the Seoul Metropolitan Area (SMA: 37.2-37.7 N, 126.6-127.2 E). The emissivity indicates the $SiO_2$ strength and can vary interannually by vegetation, water vapor, and soil moisture, as a potential indicator of drought conditions. In a well-vegetated region close to 10 N of the Sahel, the Normalized Difference Vegetation Index (NDVI) showed high sensitivity, while the emissivity did not. On the other hand, the NDVI experienced negligible variability in a poorly vegetated region near 20 N, while the emissivity reflected sensitively the effects of atmospheric water vapor and soil moisture conditions. Seasonal variations of the emissivity (0.94-0.97) have been examined over the SMA during the 2003-2004 period compared to NDVI (or Enhanced Vegetation Index; EVI). Here, the dryness was more severe in urban area with less vegetation than in suburban area; the two areas corresponded to the north and south of the Han river, respectively. The emissivity exhibiting a significant spatial correlation of ${\sim}0.8$ with the two indices can supplement their information.

• Journal of East-West Nursing Research
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• v.26 no.1
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• pp.17-27
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• 2020

Purpose: This study aimed to examine the effect of auricular acupressure therapy on reducing the ocular symptoms and signs for dry eye syndrome. Methods: The participants who were aged ≥ 40 years old and met the inclusion criteria of the ocular surface disease index score ≥ 13 and a tear film break-up time ≤ 10 seconds were enrolled into the two groups: experimental group (n=29) and control group (n=27). Experimental group received auricular acupressure therapy for 8 weeks. Seed stickers were applied to the eye, liver and tubercle point of each ear once a week. Data were collected at pre and 4 and 8 weeks after the treatment and analysed the efficacy of intervention by repeated measures ANOVA. Results: There were significant differences in the ocular surface disease index, standard patient evaluation of eye dryness and a tear film break-up time in both eyes at 8 weeks after the treatment between the two groups. Conclusion: The findings indicate that the auricular acupressure therapy may be helpful for relieving symptoms of dry eye as a nursing intervention. In addition, it could also be utilized as a self-care practice using proper education and training.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Atmosphere
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• v.33 no.3
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• pp.307-317
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• 2023

This study investigates the physical mechanisms that contributed to the 2022 European record-breaking heatwave throughout May-August (MJJA). The European climate has experienced surface warming and drying in the recent decade (1979~2022) which influences the development of the 2022 European heatwave. Since its spatial pattern resembles the 2003 European heatwave which is a well-known case developed by the strong coupling of near-surface conditions to land surface processes, the 2022 heatwave is compared with the 2003 case. Understanding heatwave development is carried out by the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and daily maximum surface temperature released by NCEP (National Centers for Environmental Prediction) CPC (Climate Prediction Center). The results suggest that the persistent high pressure along with clear sky tends to increase the downward shortwave radiation which leads to enhanced sensible heat flux with the land surface dryness. Terrestrial Coupling Index (TCI), a process-based multivariate metric, is employed to quantitatively measure segmented feedback processes, separately for the land, atmosphere, and two-legged couplings, which appears to the development of the 2022 heatwave, can be viewed as an expression of the recent trends, amplified by internal land-atmosphere interactions.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.7-9
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• 2004

The purpose of this study was to analyze the climatic water balance of the Korean peninsula using meteorological data and the evapotranspiration (ET) derived from NOAA/AVHRR. Quantifying water balance components is important to understand the basic hydrology. In this study, a simple method to estimate the ET was proposed based on a regression approach between NDVI and Morton's actual ET using NOAA/AVHRR data. The Morton's actual ET for land surface conditions was evaluated using a daily meteorological data from 77 weather stations, and the monthly averaged Morton's ETs for each land cover was compared with the monthly NDVIs during the year 2001. According to the climatic water balance analysis, water deficit and surplus distributed maps were created from spatial rainfall, soil moisture, and actual and potential ETs map. The results clearly showed that the temporal and spatial characteristics of dryness and wetness may be detected and mapped based on the wetness index.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.1
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• pp.3-9
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• 2005

The purpose of this study was to analyze the climatic water balance of the Korean peninsula using meteorological data and the evapotranspiration (ET) derived from NOAA/AVHRR, Quantifying water balance components is important to understand the basic hydrology, In this study, a simple method to estimate actual ET was proposed based on a regression approach between NDVI and Morton's actual ET using NOAA/AVHRR data, The Mortons actual ET for land surface conditions was evaluated using a daily meteorological data from 77 weather stations, and the monthly averaged Morton's ETs for each land cover was compared with the monthly NDVIs during the year 2001. According to the climatic water balance analysis, water deficit and surplus distributed maps were created from spatial rainfall, soil moisture, and actual and potential ETs map, The results clearly showed that the temporal and spatial characteristics of dryness and wetness may be detected and mapped based on the wetness index.