• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.2
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• pp.81-89
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• 2006

The purpose of this study was to evaluate the applicability of small RC(radio controlled) helicopter and single lens reflect camera as SFAP(Small Format Aerial Photography) aquisition system to monitor the vegetation coverage of wetland. The system used to take pictures of small artificial wetland were a common optical camera(Nikon F80 with manual lens whose focal length was 28mm) attached to the bottom of a RC helicopter with a 50 cubic inch size glow engine. Three hundreds pictures were taken at the altitude of 50m above the ground, from 23rd June to 7th September 2005. Four from the images were selected and scanned to digital images whose dimension were 2048${\times}$1357 pixels. Those images were processed and rectified with GCP(Ground Control Poins) and digital map, and then classified by the supervised- classification module of image processing program PG-steamer Version 2.2. The major findings were as follows ; 1. The final images processed had very high spatial resolution so that the objects bigger than 30mm like lotus(Nelumbo nucifera), rock and deck were easily identified. 2. The dominant plants of the monitoring site were Monochoria ragianlis, Typha latifolia, Beckmannia syzigachne etc. Because those species have narrow and long leaves and form irregular biomass, the individuals were hardly identifiable, but the distribution of population were easily identifiable depending on the color difference. 3. The area covered by vegetation was rapidly increased during the first month of monitoring. At the beginning of the monitoring 23th June 2005, The rate of area covered by vegetation were only 34%, but after 27 and 60 days it increased to 74%, and the 86% respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.135-144
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• 2022

Since vegetation provides humans with various ecological spaces and is also very important in terms of water resources and climatic environment, many vegetation monitoring studies using vegetation indexes based on near infrared sensors have been conducted. Therefore, if the near infrared sensor is not provided, the vegetation monitoring study has a practical problem. In this study, to improve this problem, the NDVI (Normalized Difference Vegetation Index) was used as a reference to evaluate the accuracy of the vegetation index based on the optical sensor. First, the Kappa coefficient was calculated by overlapping the vegetation survey point surveyed in the field with the NDVI. As a result, the vegetation area with a threshold value of 0.6 or higher, which has the highest Kappa coefficient of 0.930, was evaluated based on optical sensor based vegetation index accuracy. It could be selected as standard data. As a result of selecting NDVI as reference data and comparing with vegetation index based on optical sensor, the Kappa coefficients at the threshold values of 0.04, 0.08, and 0.30 or higher were the highest, 0.713, 0.713, and 0.828, respectively. In particular, in the case of the RGBVI (Red Green Red Vegetation Index), the Kappa coefficient was high at 0.828. Therefore, it was found that the vegetation monitoring study using the optical sensor is possible even in environments where the near infrared sensor is not available.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.25-33
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• 2022

In this study, a monitoring method using high-resolution images acquired by unmanned aerial vehicles and deep learning algorithms was proposed for the management of the Sinduri coastal sand dunes. Class classification was done using U-net, a semantic division method. The classification target classified 3 types of sand dune vegetation into 4 classes, and the model was trained and tested with a total of 320 training images and 48 test images. Ignored label was applied to improve the performance of the model, and then evaluated by applying two loss functions, CE Loss and BCE Loss. As a result of the evaluation, when CE Loss was applied, the value of mIoU for each class was the highest, but it can be judged that the performance of BCE Loss is better considering the time efficiency consumed in learning. It is meaningful as a pilot application of unmanned aerial vehicles and deep learning as a method to monitor and manage sand dune vegetation. The possibility of using the deep learning image analysis technology to monitor sand dune vegetation has been confirmed, and it is expected that the proposed method can be used not only in sand dune vegetation but also in various fields such as forests and grasslands.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.2
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• pp.97-105
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• 2011

This study was carried out to investigate vegetation and tree vitality of Berchemia berchemiaefolia habitat to recommend basic information for synecological characteristics. Totally 9 vegetation data were collected and analyzed. And one plant community (Quercus serrata-Berchemia berchemiaefolia community) including 43 families 66genera 72 species 8 varieties and 3 forma was differentiated. Quercus serrata-Berchemia berchemiaefolia community was subdivided into Typical subunit and Quercus mongolica subunit. Species showing the higer r-NCD value in the plant community were Berchemia berchemiaefolia, Quercus serrata, Lindera obtusiloba, Fraxinus rhynchophylla, Acer pseudo-sieboldianum, Corylus heterophylla var. thunbergii. In tree vitality result, Berchemia berchemiaefolia population containing 35 individual was estimated 3 monitoring categories; 1) General 2) Principal 3) Absolute. These categories frequencies arranged by the order General Monitoring (85.7%; 30 individual), Principal Monitoring (11.4%; 4 individual) and Absolute Monitoring (2.9%; 1 individual).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.289-291
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• 2003

Selective logging is currently a widely adopted management practice throughout the tropics. Monitoring of spatial extent and intensity of such logging is, therefore, becoming an important issue for sustainable management of forest. This study explores the possibility of using vegetation indices and Landsat 7 ETM+ image for this purpose. Two dataset acquired on 2002 and 2000 of Labanan concession area East Kalimantan, Indonesia were used. Three different vegetation indices (MSAVI, SAVI and NDVI) slicing and differentiating methods were tested. The results showed that the MSAVI is superior with overall accuracy of 77% and kappa 0.64.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.598-601
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• 2007

Urban growth management is essential for sustainable urban growth. Monitoring physical urban built-up area is a task of great significance to manage urban growth. Detecting urbanized area is essential for monitoring urbanized area. Although image classifications using satellite imagery are among the conventional methods for detecting urbanized area, they requires very tedious and hard work, especially if time-series remote sensing data have to be processed. In this paper, we propose an effective urbanized area detecting method based on normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). To verify the proposed method, we extract urbanized area using two methods; one is conventional supervised classification method and the other is the proposed method. Experiments shows that two methods are consistent with 98% in 1998, 99.3% in 2000, namely the consistency of two methods is very high. Because the proposed method requires no more process without band operations, it can reduce time and effort. Compared with the supervised classification method, the proposed method using vegetation indices can serve as quick and efficient alternatives for detecting urbanized area.

• Korean Journal of Environment and Ecology
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• v.24 no.3
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• pp.302-317
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• 2010

In this study, not only to present the management plan but also to verify the effectiveness for a area of improving the landscape and the area of creating the base of bio-inhabitation in Tancheon stream concrete embankment where were practised the vegetation-mat measures for greening via monitoring i.e. restoration progress. The results of monitoring, there were a total of 41 taxa, 18 families, 38 species, 3 varieties in 2006, moreover in the 2007, there were a total of 59 taxa, 19 families, 56 species, 3 varieties and in the period 2008, 64 taxa, 29 families, 59 species, 8 varieties. Therefore, these site has increased the plant spaces year by year. The distribution of vegetation characteristics shows that Miscanthus sacchariflorus and Pennisetum alopecuroides expands their influence in the area of applying the construction method. Those area appears a diversity of native species by the stream deposition at the flood. Thus, its condition is very soundly ecological health and eco-friend. At present, native species have been dominant, however, disturbed species and invasive species can be expected to increase dramatically in the future. Therefore, it is necessary to a long-range monitoring and management for maintaining an environmentally sound aquatic ecosystem. On this area refer to mix the river vegetation of primary succession and disturbed vegetation. For that reason, the method of constructing the vegetation-mat measures for greening in embankment does not need to remove the concrete and can install a coir-mat on the top. It leads to improve the landscape, moreover, it was analysed the such dramatic changes in the vegetation species richness by providing continuous the plant growth basis have a impact on in bio-diversity.

• Spatial Information Research
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• v.17 no.1
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• pp.117-129
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• 2009

South Korea has been undergoing spring drought periodically and diverse researches using vegetation index have been carried out to monitor spring droughts. The strength of the vegetation index-based drought monitoring is that the monitoring method enables efficient spatio-temporal grasp of changes in drought events. According to the development of low resolution satellite images such as MODIS, which are characterized by outstanding temporal resolution, the use of the method is expected to increase. Drought analysis using vegetation index considered only meteorological factor as a cause that affects vitality of vegetation. But many indirect and direct factors affect vegetation stress, So many uncertainties are involved in such method of analysis. To secure objectivity of drought analysis that uses vegetation index it is therefore necessary to compare the method with most representative drought analysis tools that are used for drought management. In this study, PDSI and SPI which a meteorological drought index that quantifies drought and that is used as a basic index for drought monitoring and MODIS NDVI are compared to propose correlation among them and to show usefulness of drought assessment that uses vegetation index. This study shows changing patterns of NDVI and SPI 6-month are similar and correlation between NDVI and SPI was highest in inland vegetation cover.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.3
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• pp.9-16
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• 2003

In support of remote sensing applications for monitoring processes of the Earth system, research was conducted to analyze the basic spectral response related to background soil and vegetation cover characteristics in the visible and reflective infrared wavelengths. Surface samples of seven stations were examined. Five soils were from land-field and two soils from tideland areas. The vegetation cover experiment was conducted on seven soil samples with known natural moisture content (%) by weight. To study the effect of vegetation cover, spectral measurements were taken on five or six vegetation cover treatments of the seven soils with 3 replications in air dry conditions. For collecting RS base data, used spectro-radiometer that measures reflection characteristics between 300~1,100nm was used and measured the reflection of vegetation from bean leaves. The relationships were evaluated for both a general soil line and for the individual lines of five soils, under air-dried condition as well as different vegetation cover ratio, through the determination of the line parameters. As vegetation cover ratio in bean leaves increases, features of soil reflectance decrease and those of plant reflectance become more and more apparent. In proportion to vegetation cover rate, near-infrared reflectance increased and visible reflectance decreased. Analysis results are compared to commonly used vegetation indices(RVI and NDVI ).