• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.593-601
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• 2015

The NDVI (Normalized difference vegetation index) is used as indicators of crop growth situation in remote sensing. To measure or validate the NDVI, reliable NDVI sensors have been needed. We tested new fixed-field NDVI sensor, "SRS (Spectral Reflectance Sensor)" developed by Decagon Devices, during Kimchi cabbage growing season at the cultivation area located in Gochang, Gangneung and Taebaek in Korea from 2014 to 2015. The diurnal variation of NDVI measured by SRS (SRS NDVI) showed a slight ${\cap}$-profile shape and was affected by water on the sensor surface. This means that SRS NDVI around noontime is resonable, except rainy day. Comparisons were made between the SRS NDVI and NDVI of used widely mobile sensor (Cropcircle NDVI). The comparisons indicate that SRS NDVI are close to Cropcircle NDVI (R=0.99). SRS NDVI time series displayed change of the plant height and leaf width of Kimchi cabbage. An obvious exponential relationship is found between SRS NDVI and the plant height ($R^2{\geq}0.92$) and leaf width ($R^2{\geq}0.92$) of Kimchi cabbage. Thus, SRS NDVI will be used as indicator of crop growth situation and a very powerful tool for evaluation of remote sensing NDVI estimates and associated corrections.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.92-100
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• 2003

Analysis and results of the relationship between the NDVI and terrain element such as elevation, slope, aspect in Chunahn city area are as follows. It does not show the linear relationship between NDVI and analyzed terrain element such as elevation, slope, aspect, etc. and there is a trend such that the deviation of NDVI is decreased as the elevation and slope is increased. It appears that there is trends such that the distribution range of NDVI is discontinuously changed as the elevation and slope is increased. The distribution range of NDVI is discontinuously decreased based on about 50m and 100m borderline in elevation case, and slope $10{\sim}20^{\circ}$ borderline in slope case, respectively. Any special trend is discovered in the relationship between aspect and NDVI.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.162-165
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• 2004

The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.257-259
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• 2003

Landuse maps are prepared from satellite imagery and field observations were conducted at various locations in the study area. Compared to the field data and NDVI and RVI thematic maps, NDVI is better than RVI, because it compensates for changing illumination conditions, surface slope, aspect and other factors. Clouds, water and snow have negative values for RVI and NDVI. Rock and bare soils have similar reflectance in both NIR and visible band, so RVI and NDVI are near zero. In forest areas with good vegetation cover, NDVI is high and landslide occurrence is less. But if annual and biennial vegetations are present and if cultivation practices are changed frequently, NDVI is medium and landslide occurrence is moderate. In areas where deforestation and settlement is in progress, NDVI is less and landslide occurrence is more. The NDVI FCC thematic map may be used as an important layer in GIS application for landslide studies. Analyzing other layers such as slope, rainfall, soil, geology, drainage, lineament, etc with NDVI FCC layer will give a better idea about the identity of landslide prone areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.23-30
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• 2017

NDVI (Normalized Difference Vegetation Index) plays an important role in surface land cover classification and LST (Land Surface Temperature Extraction). Its characteristics do not full carry the information of the surface cover typically in urban areas even though it is widely used in analyses in urban areas as well as in vegetation. However, abnormal NDVI values are frequently found in urban areas. We, therefore, examined NDVI values on whether NDVI is appropriate for LST and whether there are considerations in NDVI analysis typically in urban areas because NDVI is strongly related to the surface emissivity calculation. For the study, we observed the influence of the surface settings (i.e., geometric shape and color) on NDVI values in urban area and transition features between three land cover types, vegetation, urban materials, and water. Interestingly, there were many abnormal NDVI values systematically derived by the surface settings and they might influence on NDVI and eventually LST. Also, there were distinguishable transitions based on the mixture of three surface materials. A transition scenario was described that there are three transition types of mixture (urban material-vegetation, urban material-water, and vegetation-water) based on the relationship of NDVI and LST even though they are widely distributed.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.111-119
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• 2001

This study analyzes time variability of the normalized difference vegetation index (NDVI), the leaf area index (LAI) and surface temperature (Ts) estimated from AVHRR data collected from across the Korean peninsula from 1981 to 1994. In the present study, LAI defined as vegetation density, as a function of NDVI applied for the vegetation types and Ts defined by the split-window formulation of Becker and Li (1990) with emissivity of a function of NDVI, are used. Results of the inter-annual, intra-annual and intra-seasonal variabilities in Korea show: (1) Inter-annual variability of NDVI is generally larger in the southem and eastern parts of the peninsula than in the western part. This large variability results from the significant mean variation. (2) Inter-annual variability of Ts is larger in the areas of smaller NDVI. This result shows that the NDVI play a small role in emissivity. (3) Inter-annual variability of LAI is larger in the regions of higher elevation and urban areas. Changes in LAI are unlikely to be associated with NDVI changes. (4) Changes in NDVI and Ts are likely dominant in July and are relatively small in spring and fall. (5) Urban effect would be obvious on the time-varying properties of NDVI and Ts in Seoul and the northern part of Taejon, where NDVI decreases and Ts increases with a significant magnitude.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.151-160
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• 2017

This study was conducted by using a Nikon Coolpix S800c camera equipped with a NIR filter to measure the NDVI(Normalized Difference Vegetation Index). It was used for the measurement of the three trees of Pinus densiflora, Taxus cuspidata, Zelkova serrata and Acer palmatum in Kangwon National University. The NDVI value of the surface of the building was compared and analyzed. The average value of NDVI in August and September was high in all species. The NDVI distribution of Taxus cuspidata was higher than the other trees. The NDVI distribution of Pinus densiflora and Taxus cuspidata did not show any significant seasonal differences, but The NDVI distribution of Zelkova serrata and Acer palmatum were relatively low in May and June, which are leafless periods. Previous studies related to NDVI value were generally analyzed using satellite imagery. However, it was scarce related to study the NDVI value of each tree or study the changing process of NDVI by time series. Previous studies have used NDVI values on the ground but this study used NDVI values in the ground section. Future studies will be necessary to measure the NDVI value at different times for various species and also to make efforts to generalize the measurement method. In addition, research related to various fields such as the relationship between NDVI and carbon stocks and the relationship with LAI needs to be conducted.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.649-654
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• 2005

This study proposes a particular approach to assess information about NDVI(Normalized Difference Vegetation Index) and LAI(Leaf Area Index) from the spectroradiometer and NOAA/AVHRR satellite data. AVHRR data were collected in twelves months over a one year period in 2004. We calculated 10-day composite NDVI using daily composite AVHRR surface reflectance products(1km spatial resolution). The 10-day composite NDVI have a great effect on the plant growth conditions. Considerably, NDVI was increased by developing muscle fiber tissue from April to May. Then the NDVI increased until the August and then decreased until February. The highest month was at August and the lower month was at December. The difference NDVI analysis using December and another months data was conducted, the results were provided information on the variation of vegetation coverage. The result suggest that a relationship established between the LAI and NDVI in 2004.