• Journal of Wetlands Research
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• v.22 no.4
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• pp.275-285
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• 2020

In this study, after estimating VCI (Vegation Condition Index), TCI (Thermal Condition Index) and VHI (Vegetation Health Index) from the NDVI (Normalized Differentiation Vegetation Index) and LST (Land Surface Temperature) remotely sensed at major sites in Korea during the 2001-1919 period, the correlation between these indices and various drought indices is analyzed for the purpose of assessing the effects of ecological drought. The relative impact of VCI and TCI on vegetation health was found to vary by region. The effects of drought on vegetation in Korea's forest areas could be more clearly identified in TCI than in VCI. It is suggested that the revised VHI, reflecting the relative influence of VCI and TCI, can better explain the effects of drought on vegetation.

• Journal of Forest and Environmental Science
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• v.37 no.4
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• pp.280-291
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• 2021

The study examined the influence of climate and soil dynamics on vegetation health across the ecological zones in Rivers State, Nigeria. MODIS imagery was used to assess the vegetation health through NDVI and point grid pattern of meteorological data for total precipitation (TP), air temperature (AT), soil moisture (SM) and soil temperature (ST) of 2000, 2003, 2006, 2009, 2012 and 2015 were used for the study. Descriptive and inferential statistics were used for data analysis. Findings showed that NDVI ranged between 0.420 and 0.612 in the freshwater swamp (FWS) while between 0.465 and 0.611 in the rainforest and the NDVI in the mangrove was generally low. The highest mean AT was experienced in the mangrove ecological zone and the least was experienced in the rainforest. The mean SM was generally highest in the rainforest with highest value in 2000 (774.44 m³/m³). The ST was highest in the mangrove and the least was experienced in the rainforest while the TP was highest in the mangrove. NDVI correlated significantly with SM (r=0.720; p<0.05) and ST (r= -0.493; p<0.05). NDVI, SM, TP and ST significantly varied among the ecological zones. Regression analysis showed that vegetation health was significantly related to the combination of soil temperature and soil moisture (R²=0.641; p=0.000). Thus, monitoring the factors that affect vegetation health in a changing climate and soil environments is highly required.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.111-121
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• 2016

This study was carried out to assess the riparian vegetation health in the fluctuation area and vicinity of reservoirs. The results of this study could be a basic data to improve the ecological function and establish green-network of waterside ecosystem. The study site is Daecheong lake reservoirs which the representative landscape of Geum river and with great number of visitors near metropolitan city. The 6 survey plots of 2 survey area were selected, survey area 1 had 4 survey plots and survey area 2 had 2 survey plots, and to compare the study results 4 control plots were selected in Gyeongcheon reservoir. The main dominant specie of survey sites was Salix koreensis in tree and subtree layer, were Salix koreensis and Salix glandulosa. in shrub layer. 2 survey plots of Samjeongdong and Kyeongcheon reservoir were assessed as 'Good', 2 survey plots of chudong were assessed as 'Fair' in vegetation health assessment. In the fluctuation area from flood water level to low water level, 58 populations of Salix koreensis were found in survey sites and Salix koreensis, Salix glandulosa and Acer tataricum subsp. ginale were found in control sites. The most adequate species at the condition affected by inundation impacts would be Salix koreensis and Salix glandulosa was more healthy at the area less affected by inundation. This study was carried out the vegetation health assessment on Daecheong reservoir which has been advanced natural succession for more than 30 years after the construction. Further, it should carry continuously out the research on the planting model of the waterside ecosystem for ecological restoration.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.1-14
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• 2019

The 1st Forest Health Management survey was conducted to examine the health of the forests in Korea. However, in order to understand the health of the forests, which account for 63.7% of the total land area in South Korea, it is necessary to comprehensively spatialize the results of the survey beyond the sampling points. In this regard, out of the sample points of the 1st Forest Health Management survey in Gyeongbuk area, 78 spots were selected. For these spots, the species diversity index was selected from the survey sections, and the spatial interpolation method was applied. Inverse distance weighted (IDW), Ordinary Kriging and Ordinary Cokriging were applied as spatial interpolation methods. Ordinary Cokriging was performed by selecting vegetation indices which are highly correlated with species diversity index as a secondary variable. The vegetation indices - Normalized Differential Vegetation Index(NDVI), Leaf Area Index(LAI), Sample Ratio(SR) and Soil Adjusted Vegetation Index(SAVI) - were extracted from Landsat 8 OLI. Verification was performed by the spatial interpolation method with Mean Error(ME) and Root Mean Square Error(RMSE). As a result, Ordinary Cokriging using SR showed the most accurate result with ME value of 0.0000218 and RMSE value of 0.63983. Ordinary Cokriging using SR was proven to be more accurate than Ordinary Kriging, IDW, using one variable. This indicates that the spatial interpolation method using the vegetation indices is more suitable for spatialization of the biodiversity index sample points of 1st Forest Health Management survey.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• 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.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.47-54
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• 1997

Vegetation Index(VI) derived from remote sensing data is used to assess ecosystem factor in Environmental Impact Assessment(EIA) process. Ecosystem factor has been prepared by Degree of Green Naturality(DGN) mainly in Environmental Impact Statements. But DGN has room for improvement of assessing actual ecosystem situation. The objectives of this study are to define the relationship between field measure DGN and VI, and to develop methodologies to use VI for assessing the status and conditions of natural ecosystem. For verification of DGN and VI, 35 sites using global positioning system are selected and reviewed. Correlation coefficients of DGN and VI shows highly as 0.69. Also VI in EIA found it can be applied to assess ecosystem. It concluded that VI as well as DGN can be applied to assess ecosystem newly and largescale.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.384-401
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• 2016

The vegetation assessment indicator has been developed recently as a biological part of the integrated assessment system for river environment to improve the efficiency of river restoration projects. This study carried out to test the vegetation assessment indicator and to reset its grade criteria on experimental streams. We classified and mapped vegetation communities at the level of physiognomic-floristic composition by each assessment unit. A total of 204 sampling quadrats were set up on the 68 assessment units at 5 experimental streams. By analyzing the vegetation data collected, we examined the appropriate numbers of sampling quadrats, the criteria of vegetation index score, classification of vegetation community, and grade criteria for vegetation assessment. The developed vegetation assessment indicator composed with the vegetation complexity index (VCI), the vegetation diversity index (VDI), and the vegetation naturalness index (VNI) was proved to reflect the current conditions of the streams sufficiently. The contribution of vegetation naturalness index to grading by vegetation assessment indicator was larger, but three indexes were closely correlated to each other. Also there was more clearer discrimination of grading with the application of adjusted criteria of vegetation assessment indicator and the standardized classification of vegetation community, but the stream segment type did not influence the vegetation assessment grade significantly.

• Atmosphere
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• v.29 no.2
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• pp.131-147
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• 2019

On the urban scale, Micro-climate analysis models for urban scale have been developed to investigate the atmospheric characteristics in urban surface in detail and to predict the micro-climate change due to the changes in urban structure. BioCAS (Biometeorological Climate Impact Assessment System) is a system that combines such analysis models and has been implemented internally in the Korea Meteorological Administration. One of role in this system is the analysis of the health impact by heat waves in urban area. In this study, the vegetation cooling models A and B were developed and linked with BioCAS and evaluated by the temperature drop at the vegetation areas during ten selected heat-wave days. Smaller prediction errors were found as a result of applying the vegetation cooling models to the heat-wave days. In addition, it was found that the effects of the vegetation cooling models produced different results according to the distribution of vegetation area in land cover near each observation site - the improvement of the model performance on temperature analysis was different according to land use at each location. The model A was better fitted where the surrounding vegetation ratio was 50% or more, whereas the model B was better where the vegetation ratio was less than 50% (higher building and impervious areas). Through this study, it should be possible to select an appropriate vegetation cooling model according to its fraction coverage so that the temperature analysis around built-up areas would be improved.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.55-63
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• 2018

This paper aimed to characterize the spatial and temporal pattern of agricultural drought in Pre-Kharif season using Vegetation Health Index (VHI) and illustrated drought characteristics in Bangladesh during 2001-2015. VHI was calculated from TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS Terra satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The finding showed that all drought-affected areas were experienced by mild, moderate, severe and extreme droughts in several years of Pre-Kharif seasons. Significant drought events were found in the year of 2002 and 2013. On average, Chittagong district covered the largest drought area in all drought stages, and the fraction of drought area was the highest in Sylhet and Rangpur for Pre-Kharif season. Finally, overlaying annual VHI raster maps resulted in that the most vulnerable district to agricultural drought were Sylhet, Rangpur, and Mymensingh in the northern and eastern regions of Bangladesh.