• Journal of the Korean Society of Environmental Restoration Technology
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• v.8 no.2
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• pp.33-40
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• 2005

The objective of this research was to find an indirect method to estimate spectral reflectance and NDVI(Normalized Difference Vegetation Index) efficiently, using the spectroradiometer and NOAA AVHRR satellite data. 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 paddy rice during the growing season at Chungbuk national university's farm in 2002. The feasibility of detecting the temporal variation in the spectral reflectance and NDVI in paddy rice were conducted on eight growth stages. AVHRR data were collected in eight different months over a one year period in 2002. The results were compared with those obtained by analyzing NDVI characteristics. The spectral reflectance and NDVI of paddy rice have a great effect on the growth condition. Considerably, NDVI was increased by developing muscle fiber tissue at the near infrared wavelength until the Booting stage. Then the NDVI increased until the Maturity stage and then decreased until harvest. The highest month was at July and the lower month was at March. The difference NDVI analysis using March and another months data was conducted, the results were provided information on the growth condition of crops.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.175-182
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• 2006

Because of the phenological variation of vegetation growth in temperate region, it is often difficult to accurately assess the surface conditions of agricultural croplands, grasslands, and disturbed forests by multi-spectral remote sensor data. In particular, the spectral similarity between soil and dry vegetation has been a primary problem to correctly appraise the surface conditions during the non-growing seasons in temperature region. This study analyzes the spectral characteristics of the mixture of dry vegetation and soil. The reflectance spectra were obtained from laboratory spectroradiometer measurement (GER-2600) and from EO-1 Hyperion image data. The reflectance spectra of several samples having different level of dry vegetation fractions show similar pattern from both lab measurement and hyperspectral image. Red-edge near 700nm and shortwave IR near 2,200nm are more sensitive to the fraction of dry vegetation. The use of hyperspectral data would allow us for better separation between bare soils and other surfaces covered by dry vegetation during the leaf-off season.

• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.349-356
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• 2011

This research is aim to analyze of changing landscape and according to phenological cycle from image information of coastal environment obtained by multi-media were analyzed by camera and satellite image. The digital camera and satellite image were used for tidal flat vegetation monitoring during the construction of Sihwa lake. The vegetation type and phenological cycle of Sihwa tidal flat have been changed with the Sihwa lake ecosystem. The environment changes of Sihwa tidal flat area and ecological change were analyzed by field work digital camera images and satellite images. The airborne, UAV and satellite images were classified with the changed elements of coastal ecological environment and tidal flat vegetation monitoring carried out the changed area and shape of vegetation distribution with time series images.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.175-184
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• 2009

This study attempts to analyze the difference among the variations of ecological distribution in Gobi desert and Manchuria through satellite based land cover classification. This was motivated by two well-known facts: 1) Gobi desert, which is an old source region, had been gradually expanded eastward; 2) Manchuria, which is located in east of Gobi desert, was observed as a new source region of yellow dust. An unsupervised classification called ISODATA clustering method was employed to detect the land cover change and to characterize the status of desertification and its expanding trends using NDVI (Normalized Difference Vegetation Index) derived from VEGETATION sensor onboard the SPOT satellite for 1999 and 2007. We analyzed NDVI annual variation pattern for every classes and divide into 5 level according to their vegetation's density level based on NDVI. As results, Gobi desert is showed positive variation: a decrease $78,066km^2$ in central Gobi desert and out skirts of Gobi desert (level-0) but Manchuria area is worse than previous time: an increase $25,744km^2$.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.329-338
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• 2011

The time-series normalized difference vegetation index (NDVI) product has proven to be a powerful tool to investigate the phenological information because it can monitor the change of the forests with very high time-resolution, This study described the application of the DFT analysis over the 9 year MODIS data for the identification of the two types of vegetation cover, Pinus densiflora(Pd) and Querqus mongolica(Qm) which are dominant species of evergreen and broadleaved deciduous forest, respectively, The total number of samples was 5148 reference cycles which consist of 2160 Pd and 2988 Qm. They were extracted from the pixel-based MODIS scenes over the 9 years from 2000 to 2008 of South Korea. The DFT analysis was mainly focused on the 0th and $1^{st}$ harmonic components, each of which represents the mean value and the variation amplitude of the NDVI over the years, respectively. The $0^{th}$ harmonic values of the vegetation Pd and Qm averaged over the 9 years were 0.74 and 0.65, respectively. This implies that Pd has a higher NDVI than Qm. Similarly obtained $1^{st}$ harmonic values of Pd and Qm were 0.19 and 0.27, respectively. This can be intuitively understood considering that the seasonal variation of Qm is much larger than Pd. This distinctive difference of the $1^{st}$ harmonic value has been used to identify evergreen and deciduous forests. Overall agreement between the Fourier analysis-based map and the actal vegetation map has been estimated to be as high as 75%. This study found that the DFT analysis can be a concise and repeatable method to separate and trace the changes of evergreen and deciduous forest using the annual NDVI cycles.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.39-44
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• 2019

LID facilities do not consider environmental factors, and due to inappropriate vegetation planting causing degradation in efficiency due to plant damage and difficulty in maintenance. Therefore, in this study, assessment of impact environmental factor by seasonal variation of chlorophyll and growth of vegetation planted in LID technologies and change of pollutant reduction were conducted. In the case of B-SJ and B-RI, growth rate decreased after summer (August), and B-MG showed steady growth until autumn (September). Chlorophyll was found to increase during spring season while it decreased during autumn season. The chlorophyll concentration was found to affect the plant growth pattern. TN reduction efficiency was highest with greater than 80% efficiency in summer, and it was analyzed that plants were identified as the main factor affecting the seasonal reduction efficiency of TN. Also, temperature and relative humidity were analyzed to affect plant growth, activity and pollutant removal efficiency. Plant type and growth pattern are considered as factors to be considered in selection of appropriate plant types in LID technologies.

• Journal of Forest and Environmental Science
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• v.36 no.2
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• pp.133-142
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• 2020

Soil physical and chemical properties at three layers such as top (0-10 cm), middle (10-20 cm) and bottom (20-30 cm) layers under three different vegetation types were studied. Soil samples were collected from Acacia forest, vegetable and fallow lands of Chittagong university campus, Chittagong, Bangladesh. Results showed that sand was the dominant soil particle followed by clay and silt fractions in all soil depths under different vegetation types. Soils of fallow land showed the highest values of bulk density while forest soils had the lowest values at three depths. Acacia forest soil having lowest values of dispersion ratio (DR) is less vulnerable while fallow soil with highest DR values is more vulnerable to soil erosion. The lower pH value at all soil layers in three ecosystems represented that soils under study are acidic in nature. Contents of organic matter, total nitrogen, exchangeable cations (Ca²⁺, Mg²⁺, K⁺ and Na⁺) and cation exchange capacity (CEC) were observed higher in Acacia forest soils compared to vegetable and fallow soils. Only soils of vegetable land had higher level of available phosphorus in three layers than that of other two land covers. The study also revealed that different soil properties were observed in three different vegetation types might be due to variation in vegetation and agronomic practices.

• The Korean Journal of Ecology
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• v.23 no.6
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• pp.453-460
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• 2000

The forest vegetation of Mt. seondal was classified into eight communities and one afforestation by the phytosocialogical method (Z-M method). In general, Quercus mongolica trees occupied most of the area, while afforestation forest was distributed on the lower slope, cultivated land, and at the vicinity of village. The vegetation on the top part of Mt. Seondal was comparatively well preserved, but that in the lower areas has been disturbed heavily by human activity and some had mixed forests composed of pine trees, oaks, ashes, and Rhododendron micrantum shrub. By cluster analysis method. nine groups were identified as follows : Quercus mongolica group, Q. mongolica - Pinus densiflora group, Q. mongolica - Rhododendron schlipen - bachii group, Q. mongolica - Symplocos chinensis for. pilosa group, P. densiflora group, Juglans mandshurica group, Fraxinus mandshurica group, Betula costata group and Larix leptolepis group. These groups showed differences in species composition, but Quercus mongolica, Q. mongolica - P. densiflora, Q. mongolica - R. schlippenbachii and Q. mongolica - S. chinensis for. pilosa groups among them showed very similar floristic composition to each other. In the relationship between polar ordination axes and environmental variables, altitude was the environmental factor determining variation in species composition along axis X and soil moisture was the environmental along axis Y. They were the main factors in determining forest vegetation. The result of cluster analysis and polar ordination for the forest vegetation were corresponded to those of phytosocialogical classification in classifying vegetation.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.224-227
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• 2008

Land cover and its changes, affecting multiple aspects of the environmental system such as energy balance, biogeochemical cycles, hydrological cycles and the climate system, are regarded as critical elements in global change studies. Especially in arid and semiarid regions, the observation of ecosystem that is sensitive to climate change can improve an understanding of the relationships between climate and ecosystem dynamics. The purpose of this research is analyzing the ecosystem surrounding the Gobi desert in North Asia quantitatively as well as qualitatively more concretely. We used Normalized Difference Vegetation Index (NDVI) derived from SPOT-VEGETATION (VGT) sensor during 1999${\sim}$2007. Ecosystem monitoring of this area is necessary because it is a hot spot in global environment change. This study will allow predicting areas, which are prone to the rapid environmental change. Eight classes were classified and compare with MODerate resolution Imaging Spectrometer (MODIS) global land cover. The time-series analysis was carried out for these 8 classes. Class-1 and -2 have least amplitude variation with low NDVI as barren areas, while other vegetated classes increase in May and decrease in October (maximum value occurs in July and August). Although the several classes have the similar features of NDVI time-series, we detected a slight difference of inter-annual variation among these classes.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.4
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• pp.245-252
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• 2013

Leaf area index (LAI) is important in explaining the ability of crops to intercept solar energy for biomass production, amount of plant transpiration, and in understanding the impact of crop management practices on crop growth. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of RapidEye imagery obtained from 2010 to 2012 using empirical models in a rice plain in Seosan, Chungcheongnam-do. Rice plants were sampled every two weeks to investigate LAI, fresh and dry biomass from late May to early October. RapidEye images were taken from June to September every year and corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). Linear, exponential, and expolinear models were developed to relate temporal satellite NDVIs to measured LAI. The expolinear model provided more accurate results to predict LAI than linear or exponential models based on root mean square error. The LAI distribution was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when RapidEye imagery was applied to expolinear model. The spatial trend of LAI corresponded with the variation in the vegetation growth condition.