• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1353-1357
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• 2018

This paper compares and analyzes Fusarium wilt of radish by using an unmanned aerial vehicle(UAV) with the NDVI-7 camera. The UAV have taken near-infrared images of the Radish field in Gangwon area, which is affected by Fusarium wilt. Based on those images, we analyzed NDVI(Normalized difference vegetation index) and compared conditions of radish by using the Blue value among Regular Vegetation Index in NDVI. First, the radish field is divided into three fields for radish, soil and vinyl. Each field has separate Blue values that are radish 0.4890, soil 0.2959, vinyl -0.0605 respectively. Second, radish condition levels are divided into four stages which are normal, early, middle, and late stage of Fusarium wilt. The average values of each stage are normal 0.5165(100%), early 0.4565(88%), middle 0.3444(66%), and late 0.1772(34%) respectively. This result shows that this NDVI value is validated by measuring conditions of Radish and soil.

• KCID journal
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• v.21 no.1
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• pp.78-88
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• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.21-33
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• 2007

Different vegetation indices from satellite images have been used for monitoring drought damages, and this study aimed to develop a drought index using NOAA/AVHRR NDVI(Normalized Difference Vegetation Index) and to analyze the temporal and spatial distribution of spring drought severity in North Korea from 1998 to 2001. A new drought index, DevNDVI(Deviation of NDVI), was defined as the difference between a monthly NDVI and average monthly NDVI at the same cover area, and the DevNDVI images at all years except for 2001 demonstrated the drought-damaged areas referred from various domestic and foreign publications. The vegetation of 2001 showed high vitality despite the least amount of rainfall among the target years, and the reason was investigated that higher temperature above normal average would shift the growing stages of plants ahead. Therefore, complementary methods like plant growth models or ground survey data should be adopted in order to evaluate drought-induced plant stress using satellite-based NDVI and to make up far the distortion induced by other environments than lack of precipitation.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.27-41
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• 2017

The purpose of this study is to diagnose the possibility of future drought expression by late March dryness in rice paddy areas using Terra MODIS NDVI (Normalized Difference Vegetation Index). We tested the degree of dryness by comparing the 2000-2015 average NDVI with yearly NDVI, which we name DCI (Dry Condition Index). The 16-day interval DCIs from March 6 to May 25 were evaluated with spatio-temporal expression of South Korea. In particular, we find that the DCI for April 7 (March 23 to April 7) offered reasonable prediction of paddy dryness during drought years. The April 7 DCI value for dry conditions ranged from 0.04 to 0.08 while the DCI for normal conditions ranged from -0.04 to 0.01. The DCI can be one of the indicators used to evaluate the dryness of rice paddy areas at the beginning of the spring season.

• 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.

• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.105-117
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• 2018

This study conducted health assessment and multivariate vegetation analysis using the riparian vegetation index in 30 sites of the Geumgang mainstream and Mihocheon to obtain practical data on the river management of the Geumgang. The result showed that the number of plant communities was 54. The flora was 75 families, 185 genera, 243 species, 2 subspecies, 21 varieties, 2 varieties, and 268 taxa. The riparian vegetation index was 38.3 (3.3; G-D1 ~ 66.7; G-U2, G-U4, and G-M3), and the health of the rivers in this area was evaluated as normal (grade C). The health of rivers was the highest in the upper stream of Geumgang mainstream and lowest in the downstream of Geumgang mainstream. The relationship between riparian vegetation index and chlorophyll-a content was low. The riparian vegetation was divided into five groups of Digitaria ciliaris colony group, Salix gracilistyla colony group, Erigeron annuus colony group, the group dominated by Humulus japonicus, Salix koreensis, Miscanthus sacchariflorus, and Phragmites japonica colonies, and the group dominated by Conyza canadensis and Echinochloa crusgalli var. echinata colonies. They had the similar health conditions. The CCA analysis showed that the environmental factors affecting the distribution of vegetation were physical factors such as vegetation area, artificial structure area, waterway area, branch width, channel width, and bank height and the biological factors such as the number of species. As such, it is necessary to maintain the health condition through continuous monitoring where the health condition is high and to apply active measures such as ecological restoration where the health condition is low.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.399-409
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• 2009

Many researches have shown that NDVI provides a potential methods to derive meaningful metrics that describe ecosystem functions. In this paper we investigated the use of the MODIS NDVI (Normalized Difference Vegetation Index) to monitor vegetation phenology dynamics of Northern plateau region, North Korea, during last 9-years (2000~2008). The findings of this paper can be summarized as follows. First, the length of growing season ranged from a low of 128 days in 2003 to a high of 176 days in 2000 and 2005. On the average of the last 9 years, the highest NDVI of 0.86 was marked on 28 July. Greenup onset occurs at the start of May, while the senescence begins between late September and October. Second, these annual vegetation cycles were compared with Seorak and Jiri Mountain regions of South Korea which have similar vegetation condition. Greenup onsets in South Korea were observed earlier than those of North Korea and the average time lag between the South and North Korea in Greenup was about 16 days which is a time-resolution of remotely sensed data. Sub-alpine conifers of such areas may be severely affected by the large of phenological characteristics due to the global warming trend.

• The Korean Journal of Ecology
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• v.27 no.2
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• pp.99-106
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• 2004

We developed the estimation model for the vegetation developmental processes on the severely burned slope areas after forest fire in the east coastal region, Korea. And we calculated the vegetation indices as a useful parameter for the development of land management technique in the burned area and suggested the changes of the vegetation indices after forest fire. In order to estimate the woody standing biomass in the burned area, allometric equations of the 17 woody species regenerated by sprouter were investigated. According to the our results, twenty year after forest fire need for the development to the normal forest formed by 4 stratum structure, tree, sub-tree, shrub and herb layer. The height of top vegetation layer, basal area and standing biomass of woody species show a tendency to increase linearly, and the ground vegetation coverage and litter layer show a tendency to increase logarithmically after forest fire. Among vegetation indices, Ive and Ivcd show a tendency to increase logarithmically, and Hcl and Hcdl show a tendency to increase linearly after forest fire. The spatial variation of the most vegetation factors was observed in the developmental stages less than the first 5 years which were estimated secondary disaster by soil erosion after forest fire. Among vegetation indices, Ivc and Ivcd were the good indices for the representation of the spatial heterogeneity in the earlier developmental stages, and Hcl and Hcdl were the useful indices for the long-term estimation of the vegetation development after forest fire.