• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.1
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• pp.97-110
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• 2021

Vegetation index information is an important figure that is used in many fields such as landscape architecture, urban planning, and environment. Vegetation may vary slightly in vegetation vitality depending on photosynthesis and chlorophyll content. In this study, a range of vegetation worth preserving in the Taehwa River water system was determined, and hyperspectral images of drones were acquired (August, October), and the results were presented through DVI(Normalized Defference Vegetation Index), EVI(Enhanced Vegetation Index), PRI(Photochemical Reflectance Index), ARI (Anthocyanin Reflectance Index) index analysis. In addition, field spectral data and VRS-GPS(Virtual Reference System-GPS) surveys were performed to ensure the quality and location accuracy of the spectral band. As a result of the analysis, NDVI and EVI showed low vegetation vitality in October, -0.165 and -0.085, respectively, and PRI and ARI increased to 0.011 and 7.588 in October, respectively. For general vegetation vitality, it was suggested that NDVI and EVI analysis were effectively performed, and PRI and ARI were thought to be effective in analyzing detailed characteristics of plants by spectral band. It is expected that it can be widely used for park design and landscape information modeling by using drone image information construction and vegetation information.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.28-37
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• 2008

In this study, we perform land surface monitoring of NDVI (Normalized Difference Vegetation Index) variation by using remote sensing data during 1999-2005 over North Korea, which can't easily access to measure directly land surface characteristics due to one of the world's most closed societies. North Korea forest region has most abundant forest vegetation - so called Lungs of Korea in the Korea peninsula. NDVI represents vegetation activity used in many similar studies. In this study, we detect vegetation variation and analysis factors of the change over North Korea. By using variation of NDVI, we can infer that effect of drought over North Korea, and reduced vegetation indices by typhoon in North Korea. Land surface type except barren ground with decreased NDVI value is considered as when North Korea region was suffering from drought and typhoon effects, which show lower than mean of 7-year NDVI value. Especially, in recently, the food production of North Korea with political and economical issues can be inferred indirectly these trends by using estimated output data from this study.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.250-255
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• 2002

This paper describes the study methods of identifying forest vegetation types, based on this study, forest vegetation classification method based on vegetation index is proposed. According to reflectance data of vegetation canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun, China, many vegetation index are calculated and analyzed. The relationships between vegetation index and vegetation types are that PVI identifies broadleaf forest and conifer forest the most easily, the next is TSAVI and MSAVI, but their calculation is complex. RVI values of different conifer trees vary obviously, so RVI can classify conifer trees. In a word, combination of PVI and RVI is evaluated to classify different vegetation types.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.21-35
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• 2020

Vegetation information is a very important factor used in various fields such as urban planning, landscaping, water resources, and the environment. Vegetation varies according to canopy density or chlorophyll content, but vegetation vitality is not considered when classifying vegetation areas in previous studies. In this study, in order to satisfy various applied studies, a study was conducted to set a threshold value of vegetation index considering vegetation vitality. First, an eBee fixed-wing drone was equipped with a multi-spectral camera to construct optical and near-infrared orthomosaic images. Then, GIS calculation was performed for each orthomosaic image to calculate the NDVI, GNDVI, SAVI, and MSAVI vegetation index. In addition, the vegetation position of the target site was investigated through VRS survey, and the accuracy of each vegetation index was evaluated using vegetation vitality. As a result, the scenario in which the vegetation vitality point was selected as the vegetation area was higher in the classification accuracy of the vegetation index than the scenario in which the vegetation vitality point was slightly insufficient. In addition, the Kappa coefficient for each vegetation index calculated by overlapping with each site survey point was used to select the best threshold value of vegetation index for classifying vegetation by scenario. Therefore, the evaluation of vegetation index accuracy considering the vegetation vitality suggested in this study is expected to provide useful information for decision-making support in various business fields such as city planning in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.147-150
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• 2008

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.908-910
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• 2003

In this paper the extraction method for the best suitable green vegetation area in urban area, Daegu, Korea, was developed using satellite images (1994, 1999, Landsat TM). For this, the GIS overlay analysis of GVI (Green Vegetation Index), SBI (Soil Brightness index), NWI (None-Such wetness Index) was performed to estimate the best suitable green vegetation area. Also, the statistical documents, algorithm and Tasseled-Cap index were used to recognize the change of land cover such as cultivation area, urban area, and damaged area. Through the result of this study, it is possible to monitor the large sized reclamation of land by drainage or damaged area by forest fires. Moreover, information with the change of green vegetation and the status of cultivation by GVI, but also moisture content by percentage by NWI and surface class by SBI can be obtained.

• Journal of Environmental Science International
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• v.21 no.2
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• pp.135-144
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• 2012

This study aims at classifying and analyzing the vegetation structure of Castanopsis sieboldii forest, one of the evergreen broad-leaved forests found under the warm-temperate climate of Korea. It is also compared with the ones of the Castanopsis sieboldii forest in Japan where most similar such forest of Korea, to find unique vegetation structures of the only Korean forest. Vegetation structure of Korean Castanopsis sieboldii forest was divided into two units at the level of community units both of Ardisia japonica-Castanopsis sieboldii community and Ardisio-Castanopsietum sieboldii association. The association carries similar type with the vegetation system of Japan, but any subunits differentiated with the Japan were found vary much. Hierarchical cluster analysis brings in similar result with the analysis on the vegetation structure as well.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.99-106
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• 2014

After 1960 forest and ecosystem are rapidly destroyed by industrialization and urbanization. Accordingly, studies that produce vegetation map continue for forest and ecosystem management. Since 1986 national natural environment survey is being conducted in Korea. Also, vegetation information is managed properly through forest geospatial information service(FGIS) of the Department of Environment when NGIS project was promoted since 1995. But it provide dominant species information based on text. In particular, some vegetation information dose not provide to end-user. Therefore, we suggest construction method of vegetation information management system based on GIS to solve the problem. Also, we suggest connection method of related system for an accurate analysis, planning and decision-making support.