• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.805-809
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• 2008

Measurement of leaf area index (LAI) is useful for understanding rice growth, water use, and canopy light interception. The top nitrogen content(TNC) per unit area is an important quantitative index of the condition of nitrogen nutrition in rice production. The rapid and simple method of estimation of TNC, with the use of the existing nondestructive analyzing instruments chlorophyll meter SPAD-502 and plant canopy analyzer (PCA) LAI-2000, was scrutinized. Destructive measurement is time consuming and labor intensive. Our objective was to evaluate sampling procedures using the Li-Cor LI-1800, LAI 2000 plant canopy analyzer (PCA) for nondestructive estimation of rice LAI, and SPAD-502 on the Northern Plains of Cheongju. The LAI estimated by PCA tended to underestimate the LAI determined by actual measurement by about 20%. The estimation of LAI by PCA was judged to have a sufficient accuracy as a practical technique. A high positive correlation was obtained between the values of the SPAD reading and LAI. NDVI and LAI also showed a very high correlation. The values of the SPAD reading and LAI, and NDVI gave a high positive correlation. These results indicated that the method described in this study was effective as a simple and rapid method for the estimation of rice growth.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.679-684
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• 2002

MODIS LAI has been one of key products for analyzing the quantitative aspects ofterrestrial ecology. This study was designed to validate MODIS LAS product by using the reference LAI map that was derived from both ground measurements and ETM＋ surface reflectance. The study area, the Kwangneung Experiment Forest in Korea, covers mixed species of deciduous and conifers of temperate forest. Throughout the growing season of 2002, we have measured LAS at the 30 sample plots using an optical device. Ground measured LAS data were then correlated to the ETM＋ reflectance to produce a continuous map of LAS over the study area. Preliminary comparison between MODIS LAI and the reference LAI map showed the lower LAI values from the MODIS product.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.305-311
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• 2006

Although there have been several attempts to estimate forest LAI using optical remote sensor data, there are still not enough evidences whether the NDVI is effective to estimate forest LAI, particularly in fully closed canopy situation. In this study, we have conducted a simple correlation analysis between LAI and spectral reflectance at two different settings: 1) laboratory spectral measurements on the multiple-layers of leaf samples and 2) Landsat ETM+ reflectance in the close canopy forest stands with fieldmeasured LAI. In both cases, the correlation coefficients between LAI and spectral reflectance were higher in short-wave infrared (SWIR) and visible wavelength regions. Although the near-IR reflectance showed positive correlations with LAI, the correlations strength is weaker than in SWIR and visible region. The higher correlations were found with the spectral reflectance data measured on the simulated vegetation samples than with the ETM+ reflectance on the actual forests. In addition, there was no significant correlation between the forest.LAI and NDVI, in particular when the LAI values were larger than three. The SWIR reflectance may be important factor to improve the potential of optical remote sensor data to estimate forest LAI in close canopy situation.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1719-1729
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• 2021

Leaf area index (LAI) provides valuable information necessary for sustainable and effective management of forests. Although global high resolution LAI data are provided by European Space Agency using Sentinel-2 satellite images, they have not considered forest characteristics in model development and have not been evaluated for various forest ecosystems in South Korea. In this study, we proposed a LAI estimation model combining machine learning and the PROSAIL radiative transfer model using Sentinel-2 satellite data over a local forest area in South Korea. LAI-2200C was used to measure in situ LAI data. The proposed LAI estimation model was compared to the existing Sentinel-2 LAI product. The results showed that the proposed model outperformed the existing Sentinel-2 LAI product, yielding a difference of bias ~ 0.97 and a difference of root-mean-square-error ~ 0.81 on average, respectively, which improved the underestimation of the existing product. The proposed LAI estimation model provided promising results, implying its use for effective LAI estimation over forests in South Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.

• Journal of Korean Library and Information Science Society
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• v.45 no.4
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• pp.139-164
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• 2014

Analyzing research schools' reports on school library activities, this paper identifies the characteristics and problems of library assisted instruction (LAI), and proposes areas and ways for improvement. Twenty three reports of secondary schools in Edunet were analyzed and their content were categorized into 13 educational activities. Most frequently implemented activities were collection development, reading programs, LAI, and Digital Library System (DLS). The verified positive impact of LAI include enhanced motivation for reading and improved ability for self-directed learning. Areas for improvement include LAI's excessive dependence on DLS and reading activities, insufficient time and library materials which hindered students' information activities. In order for LAI to be more effective in enhancing self-directed learning ability, it is suggested to connect LAI to specific educational experiences and develop customized and detailed content.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.571-585
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• 2017

The number of spaceborne optical sensors including red-edge band has been increasing since red-edge band is known to be effective to enhance the information content on biophysical characteristics of vegetation. Considering that the Agriculture and Forestry Satellite is planning to carry an imaging sensor having red-edge band, we tried to analyze the current status and potential of red-edge band. As a case study, we analyzed the effect of using red-edge band and tried to find the optimum band width and wavelength region of the red-edge band to estimate leaf area index (LAI) of very dense tree canopy. Field spectral measurements were conducted from April to October over two tree species (white oak and pitch pine) having high LAI. Using the spectral measurement data, total 355 red-edge bands reflectance were simulated by varying five band width (10 nm, 20 nm, 30 nm, 40 nm, 50 nm) and 71 central wavelength. Two red-edge based spectral indices(NDRE, CIRE) were derived using the simulated red-edge band and compared with the LAI of two tree species. Both NDRE and CIRE showed higher correlation coefficients with the LAI than NDVI. This would be an alternative to overcome the limitation of the NDVI saturation problem that NDVI has not been effective to estimate LAI over very dense canopy situation. There was no significant difference among five band widths of red-edge band in relation to LAI. The highest correlation coefficients were obtained at the red-edge band of center wavelength near the 720 nm for the white oak and 710 nm for the pitch pine. To select the optimum band width and wavelength region of the red-edge band, further studies are necessary to examine the relationship with other biophysical variables, such as chlorophyll, nitrogen, water content, and biomass.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1400-1402
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• 2003

The objective of this paper is to determine the suitable spectral bands for monitoring growth status change during a long period. The long-term ground-level reflectance spectra as well as LAI and biomass were obtained in xiaotangshan area, Beijing, 2001. The narrow-band NDVI type spectral indices by all possible two bands were calculated their correlation coefficients R$^2$ with biomass and LAI. The best NDVIs must have higher R$^2$ with both biomass and LAI. The reasonable band centers and band widths were determined by a systematically increasing bandwidth centered over a wavelength. In addition, the first 19 bands of MODIS were simulated and investigated. Each developed spectral indices was then validated by the biomass and LAI time series using the generalized vector angle. It turned out that six new NDVI type indices within 750-1400nm were developed. NDVI(811_10,957_10) and NDVI(962_10,802_10) performed best. No satisfactory conventional NDVI formed by red and NIR bands were found effective. MODIS_NDVI(band19, band17) and MODIS_NDVI(band19, band2) were much better than MODIS_NDVI(band2,band1) for growth monitoring.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.815-820
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• 2015

For the establishment of effective water resources management platform for Jeju-Island, the characteristics, including surface runoff, evapotranspiration, groundwater recharge and discharge are to be properly quantified. Among these hydrologic components, interception due to vegetation is very important factor but it is hard to be quantified. After Von Hoyningen-Huene (1981) found the relationship between LAI (Leaf Area Index) and interception storage, LAI has been used for key factor to estimate interception and transpiration. In this study the equation suggested by Kozak et al. (2007) is implemented in SWAT-K (Soil and Water Assessment Tool - Korea) model and is tested at the Cheonmicheon watershed in Jeju-Island. The evaporation due to interception was estimated as 85~104mm, 8~11% of whole evaporation. Therefore it is necessary to consider the evaporation due to interception as a controlling factor to water budget of this watershed.