• 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 Forest and Environmental Science
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• v.25 no.1
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• pp.49-55
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• 2009

The present study analyses the effect of land use on the vegetation of some desert ecosystems in Abu Dhabi, United Arab Emirates (UAE). Three sites were selected to represent different types of land use, inside Umm Al-Banadeq forest, outside the forest and along Abu Dhabi-Al Ain Trucks Road. In total, fifty-two stands were examined; including a matrix of 14 species ${\times}$ 52 stands. Based on species cover data, stands were classified using TWINSPAN and ordinated using DCA. Four vegetation groups were generated at level three of classification. Zygophyllum mandavillei was dominant in most vegetation groups; Heliotropium bacciferum dominated vegetation groups inhabited the forest. Species richness, species turnover, relative evenness and relative concentration of dominance of forest vegetation groups were 2.8, 5.7, 0.7, and 2.0, respectively. The differences were attributed to both natural variability and forestry-induced changes, including change in land use, drainage and ploughing and shading by trees. Vegetation group inhabited Abu Dhabi-Al Ain Trucks Road, that were dominated by Haloxylon salicornicum and Zygophyllum mandavillei have high total cover (8.8 m per $m^{-1}$). Most community and vegetation attributes were significantly higher inside the forest than outside. Human interventions and environmental factors affected species diversity and abundance of these communities.

• The Korean Journal of Ecology
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• v.10 no.2
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• pp.91-107
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• 1987

This study is concerned with some methods and applications, used as a basis on information and entropy analysis of vegetation data. These methods are adopted for the evaluating the effect of sampling intensity on information, which repersnets the departure of observed variable from standard component. Classes on the data matrix are caluculated by using marginal dispersion array for rank and weighting information program. Finally the information and entropy are computed by applying seven options. On the application of vegetation studies, two models for cluster analysis and analysis of concentration are explained in detail. Cluster analysis is based on use of equivocation information and Rajski's metrics. The analysis of concentration utilizes coherence coefficience being transformed values, which has been adjusted from blocks and entropy values. The relationship btween three begetation clusters and four stands of Naejangsan data is highly significant in 79% of total variance. Cluster A relatively tends to prefer north side, and cluster C south side.

• 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.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.351-360
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• 2013

Harmonic analysis enables to characterize patterns of variation in MODIS NDVI time series data and track changes in ground vegetation cover. In harmonic analysis, a periodic phenomenon of time series data is decomposed into the sum of a series of sinusoidal waves and an additive term. Each wave is defined by an amplitude and a phase angle and accounts for the portion of variance of complex curve. In this study, harmonic analysis was explored to tract ground vegetation variation through time for land-cover vegetation change detection. The process also enables to reconstruct observed time series data including various noise components. Harmonic model was tested with simulation data to validate its performance. Then, the suggested change detection method was applied to MODIS NDVI time series data over the study period (2006-2012) for a selected test area located in the northern plateau of Korean peninsula. The results show that the proposed approach is potentially an effective way to understand the pattern of NDVI variation and detect the change for long-term monitoring of land cover.

• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.496-507
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• 2006

A hybrid approach integrating both high-resolution and hyperspectral data sets was used to map vegetation cover of a coastal lowland area in the Hawaii Volcanoes National Park. Three common grass species (broomsedge, natal redtop, and pili) and other non-grass species, primarily shrubs, were focused in the study. A 3-step, hybrid approach, combining an unsupervised and a supervised classification schemes, was applied to the vegetation mapping. First, the IKONOS 1-m high-resolution data were classified to create a binary image (vegetated vs. non--vegetated) and converted to 20-meter resolution percent cover vegetation data to match AVIRIS data pixels. Second, the minimum noise fraction (MNF) transformation was used to extract a coherent dimensionality from the original AVIRIS data. Since the grasses and shubs were sparsely distributed and most image pixels were intermingled with lava surfaces, the reflectance component of lava was filtered out with a binary fractional cover analysis assuming that tile total reflectance of a pixel was a linear combination of the reflectance spectra of vegetation and the lava surface. Finally, a supervised approach was used to classify the plant species based on tile maximum likelihood algorithm.

• Spatial Information Research
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• v.18 no.5
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• pp.27-36
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• 2010

This study observed distribution of vegetation to confirm change of tundra-taiga boundary. Tundra-taiga boundary is used to observe the transfer of vegetation pattern because it is very sensitive to human activity, natural disturbances and climate change. The circumpolar tundra-taiga boundary could observe reaction about some change. Reaction and confirmation about climate change were definite than other place. This study used Leaf Area Index(LAI) 8-Day data in August from 2000 to 2009 that acquire from Terra satellite MODerate resolution Imaging Spectroradiometer(MODIS) sensor and used K$\"{o}$ppen Climate Map, Global Land Cover 2000 for reference data. This study conducted analysis of spatial distribution in low density vegetated areas and inter-annual / zonal analysis for using the long period data of LAI. Change of LAI was confirmed by analysis based on boundary value of LAI in study area. Development of vegetation could be confirmed by area of grown vegetation($730,325km^2$) than area of reduced vegetation ($22,372km^2$) in tundra climate. Also, area was increased with the latitude $64^{\circ}$ N~$66^{\circ}$ N as the center and around the latitude $62^{\circ}$ N through area analysis by latitude. Vegetation of tundra-taiga boundary was general increase from 2000 to 2009. While area of reduced vegetation was a little, area of vegetation growth and development was increased significantly.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• The Korean Journal of Ecology
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• v.16 no.1
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• pp.93-114
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• 1993

The vegetation of Mt. Mudeung was investigated from April, 1991 to September, 1992. The units of vegetation were classified 10 units by the Braun-Blanquet's phytosociological method. The forest vegetation was classified into 10 communities, Pinus densiflora, Pinus vigida, Chamaecyparis obtusa afforestation, Quercus mongolica, Q. variabilis, Q. serrata, Q. acutissima, Miscanthus sinensis var. purpurascens, Hylomecon hylomeconoides and Drosera rotundifolia community. Based on the classification, the actual vegetation map and degree of green naturality were drawn in 1:50,000 scale. The vertical distribution of the main component species was investigated based on the vegetation data of the EN slope and SW slope of Mt. Mudeung from altitude 200m to top.

• Journal of electromagnetic engineering and science
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• v.5 no.4
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• pp.183-188
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• 2005

A simple microwave backscattering model for vegetation canopies on earth surfaces is developed in this study. A natural earth surface is modeled as a two-layer structure comprising a vegetation layer and a ground layer. This scattering model includes various scattering mechanisms up to the first-order multiple scattering( double-bounce scattering). Radar backscatter from ground surface has been modeled by the polarimetric semi-empirical model (PSEM), while the backscatter from the vegetation layer modeled by the vector radiative transfer model. The vegetation layer is modeled by random distribution of mixed scattering particles, such as leaves, branches and trunks. The number of input parameters has been minimized to simplify the scattering model. The computation results are compared with the experimental measurements, which were obtained by ground-based scatterometers and NASA/JPL air-borne synthetic aperture radar(SAR) system. It was found that the scattering model agrees well with the experimental data, even though the model used only ten input parameters.