• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.16-28
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• 2013

Recently the various applications and spectral indices development of airborne hyperspectral imagery(A-HSI) has been increased. Especially the vegetation indices (VIs) were used to verify stress and vigor of vegetation. The VIs needs two or more spectral bands selectively to calculate as NIR(near infrared) and red wavelength. The A-HIS has specific band characteristics as narrow, continues and many. The A-HIS has narrow, continues and many specific band characteristics. That could be make it confuse which of bands could be explained for appropriate vegetation characteristics. If the A-HIS bands is not the same the wavelength with VIs' development band setting, then it need a selection adequate for spectral characteristics of target vegetation. Therefore we set 4 substitute bands for NIR and red wavelength respectively and calculated two VIs combined with substitute bands such as NDVI(normalized difference vegetation index) and MSRI(modified simple ratio index). To consider the variation of each VIs, we adapted the image differencing method of change detection technique. Also, we used spectral derivative to identify appropriate bands for spectral characteristics of digital forest cover type map. The result of adequate bands for two VIs selected red #3 as 680.2nm and NIR #2 as 801.7nm. This wavelength was good for any forest type in low variations.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.687-690
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• 2005

Recently there have been a lot of kinds of damages in forest area such as forest fires, forest pest, landslide so that the efficient methods to mange those information and the way to face them are deadly needed. In this study, there were preparing the various vegetation index map and comparing them with the field surveying the tried to figure out which vegetation index algorism is the best proper to present forest fire damaged area. These all were based on Landsat ETM+ satellite image (2000.10.16). The result of this study is to select the high correlation algorism among the various vegetation indexes and then construct the forest fire disaster map, the case of forest fires damaged area.

• The Korean Journal of Quaternary Research
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• v.22 no.2
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• pp.6-11
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• 2008

Vegetation change reconstructed by pollen analysis is effective to clarify natural conditions such as climate and soil as well as intensity of human activity. Pollen analysis in Korea is difficult to obtain peaty soil sedimented by low relief geomorphollogically and formation age is usually confined to obtain information during young Holocene as well as little absolute age data. Isopollen map was constructed in order to analyze the change of vegetation environment time-spatially during Holocene based on the 30 data with age dated from 78 results from pollen analysis in Korea. The indicatives for vegetation environment were the main trees in Korea such as Alnus, Pinus, Quercus and AP/NAP during the periods of 6,000 y.BP, 4,000 y.BP, 3,000 y.BP, 2,000 y.BP, 1,000 y.BP. As a result, the regional time-spatial patterns of vegetation distribution appeared clearly on the isopollen map. The dominant vegetation stage was repeated in the different pattern e.g. the dominance between Alnus and Quercus at West Coast and between Pinus and Quercus at East Coast competitively.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.403-409
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• 2003

Since SPOT4 satellite contained VEGETATION 1 sensor launched, the noise in VEGETATION data was occasionally arisen a difficulty for the data traitement. Blind line noise types were studied in VEGETATION-l short wave infrared channel(SWIR). In order to provide a precis product, the procedure for removing this noise is strongly recommended. In the case that the blind values are clearly distinguished from contamination-free values a simple threshold method was applied, while a changeable threshold method was used for the blind value mixed with contamination-free values. New algorithm presented in this study is consists of two method for each type of SWIR blind. After removing blind line, there were again some residual pixels of blind, because the threshold is not determinated sufficiently low. Lower threshold could remove the blind line as well as the contamination-free pixels. Nevertheless, the results showed a good qualitative improvement as compared with other algorithm.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.94-100
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• 2008

Recently, global warming for climate system is a crucial issue over the world and it brings about severe climate change, abnormal temperature, a downpour, a drought, and so on. Especially, a drought over the earth surface accelerates desertification which has been advanced over the several years mainly originated from a climatic change. The objective of this study is to detect variation of vegetation water condition around China and Mongolia desert by using satellite data having advantage in observing surface biological system. In this study, we use SPOT/VEGETATION satellite image to calculate NDWI (Normalized Difference Water Index) around study area desert for monitoring of status of vegetation characteristics. The vegetation water status index from remotely sensing data is related to desertification since dry vegetation is apt to desertify. We can infer vegetation water status using NDWI acquired by NIR (Near infrared) and SWIR (Short wave infrared) bands from SPOT/VGT. The consequence is that NDWI decreased around desert from 1999 to 2006. The areas that NDWI was decreased are located in the northeast of Mongolian Gobi desert and the southeast of China Taklamakan desert.

• Journal of Ecology and Environment
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• v.41 no.4
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• Journal of Ecology and Environment
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• v.36 no.4
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• pp.235-243
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• 2013

In Korea, where the plain land is greatly deficient as a mountainous nation, most of riparian zones were transformed into agricultural fields and urban areas. Excessive use of the land, which is close to river, makes the rivers enduring severe pollution stresses. Disappearance of riparian buffer, which plays a function of filter in the riverside, appears as a main factor aggravating water pollution of rivers. In this respect, it is imperative to restore the lost riparian vegetation. This study found out restoration models of riparian vegetation from the Bongseonsa stream, which has remnant riparian vegetation patches as a conservation reserve. Feasible reference information applicable for restoration of riparian vegetation was shown in the species level in the order of herb, shrub, and tree and sub-tree zones as far away from the waterway. Those information could contribute to restoring integrate and healthy rivers and streams beyond simple landscaping differently from the other restoration projects when they will be applied to the restoration project to be carried out in the future. In addition, the spatial range of river and stream, background that riparian zone disappeared in Korea, and application plan of the obtained reference information were discussed.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.47-54
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• 2005

The goal of this study is to generate a landslide potential map using GIS(Geographic Information System) based method. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM(Digital Elevation Model) and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight value for landslide potentialities is calculated from AHP(Analytic Hierarchy Process) method. Slope and Slope-direction is extracted from DEM, and soil information is extracted from digital soil map. Also, vegetation information is extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is compared with landslide place.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.21-27
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• 2000

This paper is keeping with the general pattern of automatic acquisition and interpretation of geographical digital data. Maps of the Institut Geographique National of France are built up with four so-called "mother" maps represented by four colors. The green one deals with the vegetation. In a green layer, woods, bushes, vines. fields and boundaries of domanial forests or nature reserves are represented by different synthetic textures We present here an original method of texture analysis applied to the automatic interpretation of vegetation belts.