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

• Spatial Information Research
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• v.3 no.2
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• pp.91-102
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• 1995

The purposes of this paper are to find ways to detect ecotone between two eco'||'&'||'not;systems, measure the width and size of ecotone around the Mt. Pukhansan National Park, and investigate environmental impacts, if any, on the forest ecosystem of the park by human activities. Normalized Difference Vegetation Index(NDVI) derived from TM data and the ana'||'&'||'not;lytical capabilities of GIS are used to investigate characteristics of the ecotone, or the impact zone, of the park. Major findings of the study can be summarized as follows: First, it was found that ecotone of the park could be identified from NDVI -distance curves deri"ed by a series of buffering op'||'&'||'not;erations. Second, NDVIs of all three years of the national park are about 14 percent higher than surrounding areas. Third, width of ecotone were found to be closely related to phenology, adjacent land use, environmental degradation, etc. Third, ecotone of the study area was nearly douvled during 1985-1993 period, which might be caused by heavy trampling of visitors. Thus it can be concluded that further studies are needed to find exact causes of the deterioration of plant communities of the ecotone of the park.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.78-84
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• 2003

The purpose of this study is to evaluate the ecosystem soundness in landscape scale using landscape indices, and to extract regional information that can be used for sustainable landuse planning. About BongWha-gun, the landcover classification using Landsat TM images and patch analysis ware carried out, and some landscape indices were calculated using geographic information system(GIS) and patch analyst program. As the results of this study, Seokpo, Jaesan and Sochun got higher scores in landscape indices related to the ecosystem soundness. But, Bonghwa-eup got lowest scores in the 10 regions. When compared with normalized difference vegetation index(NDVI), this result showed consistency to some degree. Although, there needs more supplementary studies, it is anticipated that landscape scale ecosystem evaluation using landscape indices can gives us some informations related to sustainable landuse planning.

• Ecology and Resilient Infrastructure
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• v.4 no.4
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• pp.237-244
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• 2017

The Impact Mitigation Regulation was first introduced in Germany with an intention to avoid or reduce the natural ecology and landscape infringement as much as possible according to the development project. The system has is an advantage of being able to efficiently operate the linkage policy of land planning and environment planning to prevent the excessive development of the national land and to continue to manage it. This study applied the German natural impact mitigation system by revising and supplementing it according to the domestic situation with a biotope map of Juam-dong, Gwacheon City, as a case study area. Spatial analysis was conducted of biotope maps, landscape maps, and NDVI maps to suggest a plan to derive and preserve the areas excellent in an ecological and environmental value. It was confirmed the Impact Mitigation Regulation could be used as a policy link of the land-environment policy that minimizes the degree of the damage that cannot help occurring necessarily in the development of the national land and to manage that damage from the planning stage.

• Atmosphere
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• v.19 no.2
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.315-328
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• 2011

Landsat data incorporated with additional bands-normalized difference vegetation index (NDVI) and band ratios were used to assess the extent and rate of deforestation in the Gunung Mutis Nature Reserve (GMNR), a mountainous tropical forest in Eastern of Indonesia. Hybrid classification was chosen as the classification approach. In this approach, the unsupervised classification-iterative self-organizing data analysis (ISODATA) was used to create signature files and training data set. A statistical separability measurement-transformed divergence (TD) was used to identify the combination of bands that showed the highest distinction between the land cover classes in training data set. Supervised classification-maximum likelihood classification (MLC) was performed using selected bands and the training data set. Post-classification smoothing and accuracy assessment were applied to classified image. Post-classification comparison was used to assess the extent of deforestation, of which the rate of deforestation was calculated by the formula suggested by Food Agriculture Organization (FAO). The results of two periods of deforestation assessment showed that the extent of deforestation during 1989-1999 was 720.72 ha, 0.80% of annual rate of deforestation, and its extent of deforestation during 1999-2009 was 1,059.12 ha, 1.31% of annual rate of deforestation. Such results are important for the GMNR authority to establish strategies, plans and actions for combating deforestation.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.55-61
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• 2011

The land use has been changed artificially and caused the result of temperature increase of city compared with the outside of city or region of park and forest. The purpose of this research is to analyze the change of the urban surface temperature with land use zoning in Jinju using Landsat TM/$ETM^+$ imagery and to provide the correlation between NDVI(Normalized Difference Vegetation Index) and urban surface temperature change. The results presented that the spatial distribution of urban surface temperature was depending on the change of NDVI values on land use zoning. Considering to the average temperature by land use zoning, industrial area was the highest temperature but green area was the lowest temperature. Also as a result of comparing the correlation between surface temperature and NDVI, the green and residential area had higher correlation values than the commercial and industrial area. These results will be played a part as one of the major factors for implementing the sustainable urban planning considering the urban heat island effect problem.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.39-44
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• 2009

To analysis the LST distribution of Jeju island, remote sensing techniques using Landsat TM band 6 data were used. In this study, we made the LST distribution map based on the NASA. The study areas are the Jeju and Seogwipo cities of the Jeju Island. And we analyzed the correlation between the LST and NDVI which was calculated from the Landsat TM band 3 and ban 4. From the result, we found that the coefficients of the correlation were -0.77 and -0.74 on the Jeju and the Seogwipo cities, respectively. Finally, from the correlation between the land cover and LST, we also found that an inverse relationship between the LST and NDVI was exist.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.25-43
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• 2018

The effects of hydro-meteorological and surface variables on the frequency of Asian dust events (FAE) were investigated using ground station and satellite-based data. Present weather codes 7, 8, and 9 derived from surface synoptic observations (SYNOP)were used for counting FAE. Surface wind speed (SWS), air temperature (Ta), relative humidity (RH), and precipitation were analyzed as hydro-meteorological variables for FAE. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and snow cover fraction (SCF) were used to consider the effects of surface variables on FAE. The relationships between FAE and hydro-meteorological variables were analyzed using Z-score and empirical orthogonal function (EOF) analysis. Although all variables expressed the change of FAE, the degrees of expression were different. SWS, LST, and Ta (indices applicable when Z-score was < 0) explained about 63.01, 58.00, and 56.17% of the FAE,respectively. For NDVI, precipitation, and RH, Asian dust events occurred with a frequency of about 55.38, 67.37, and 62.87% when the Z-scores were > 0. EOF analysis for the FAE showed the seasonal cycle, change pattern, and surface influences related to dryness condition for the FAE. The intensity of SWS was the main cause for change of FAE, but surface variables such as LST, SCF, and NDVI also were expressed because wet surface conditions suppress FAE. These results demonstrate that not only SWS and precipitation, but also surface variables, are important and useful precursors for monitoring Asian dust events.

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