• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.82-95
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• 2011

The objective of this paper is to analyze the GIS-based water cycle system: rainfall, evapotranspiration, surface run-off of Gyeongsanam-do for the effective rainwater management. The rainfall(1999~2008) analyzed by a spatial interpolation method, showed relatively higher amount in Hadong-gun, Sanchung-gun, and Sacheon-gun on the southwest coast than in Changnyeong-gun, Miryang-si, and Changwon-si in the mideast inland. The evapotranspiration was calculated by the three independent variables: air temperature, landuse, and NDVI(normalized difference vegetation index). The analysis showed that Namhae-gun had the highest evapotranspiration of 93.71mm, and Jinhae-si and Changwon-si had the lowest values of 81.78mm and 84.37mm. The surface run-off was analysed by a run-off equation based on the SCS hydrologic soil classification and landuse. The amount of surface run-off showed that Hadong-gun had the highest value, of 90.40mm, and Geochang-gun had the lowest, of 46.69mm. The analysis results of the GIS-based water cycle system will be used to support the establishment of the effective rainwater management plan in Gyeongasngnam-do.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.100-116
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• 2019

Urban green spaces, as a means to mitigate social problems and environmental risks, are getting more attention in evaluating urban environment. The inequity of green space distribution is becoming a major issue in urban planning and management. This study investigated the characteristics of green space in 3 districts (Jung-gu, Dongdaemun-gu, Seongdong-gu), that are composed of 46 administrative divisions in central Seoul, to analyze the environmental equity of urban green spaces. The correlations between the amount of green space, including the coverage of street trees, and the socioeconomic status of each administrative division were analyzed. To deduce the effects of plant coverage on the urban temperature regime, the relationship between the normalized difference of vegetation index (NDVI) and land surface temperature (LST) was analyzed. The research revealed that the mean NDVI of an administrative division was negatively correlated with the percentage of basic living recipients and disabled people. The LST of a division with low NDVI was higher due to the lack of green coverage. Such environmental inequities were closely related to residential building type, which was strongly affected by the economic status of residents. The LST of an apartment area was $2.0^{\circ}C$ lower than that of single-family houses and multi-housing areas. This is expected as the average NDVI of the apartment area was more than twice as high as the other environments considered in this study. The inequity can be exacerbated without urban planning which is deliberately designed to reduce it.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.295-301
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• 2021

In this study we developed the ground-based multispectral camera system to determine proper period to build and apply the calibration equation for dry matter of winter forage corps monitoring by unmanned aerial vehicle (UAV). Normalized difference vegetation index (NDVI) of rye, whole barley and Italian ryegrass (IRG) were measured and the growth period was divide by NDVI increasing period and decreasing period. Day of the maximum NDVI value of rye, whole barley and IRG were 8th, 9th and 5th April 2020. Regression analysis showed that the correlation coefficients (R²) between dry matter and NDVI were 0.84, 0.84, 0.78 during NDVI increasing period and 0.00, 0.02, 0.27 during NDVI decreasing period. Therefore, detailed NDVI monitoring is required to determine the proper period to build and apply the calibration equation and the ground-based multispectral camera system was effective tool for detailed NDVI monitoring.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.145-160
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• 2023

The purpose of this study was to compare and analyze diurnal thermal environments using Unmanned Aerial Vehicles(UAV)-derived physical parameters(NDVI, SVF) and ENVI-met modeling. The research findings revealed significant correlations, with a significance level of 1%, between UAV-derived NDVI, SVF, and thermal environment elements such as S↑, S↓, L↓, L↑, Land Surface Temperature(LST), and Tmrt. In particular, NDVI showed a strong negative correlation with S↑, reaching a minimum of -0.52^** at 12:00, and exhibited a positive correlation of 0.53^** or higher with L↓ at all times. A significant negative correlation of -0.61^** with LST was observed at 13:00, suggesting the high relevance of NDVI to long-wavelength radiation. Regarding SVF, the results showed a strong relationship with long-wave radiative flux, depending on the SVF range. These research findings offer an integrated approach to evaluating thermal comfort and microclimates in urban areas. Furthermore, they can be applied to understand the impact of urban design and landscape characteristics on pedestrian thermal comfort.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.2
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• pp.79-87
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• 2009

Pot experiments using sand culture were conducted in 2004 under greenhouse conditions to evaluate the effect of nitrogen deficiency on red pepper biomass. Nitrogen stress was imposed by implementing 6 levels (40% to 140%) of N in Hoagland's nutrient solution for red pepper. Canopy reflectance measurements were made with hand held spectral sensors including $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$, and $Field\;Scout^{TM}$ Chlorophyll meter, and a spectroradiometer as well as Minolta SPAD-502 chlorophyll meter. Canopy reflectance and dry weight of red pepper were measured at five growth stages, the 30th, 40th, 50th, 80th and 120th day after planting(DAT). Dry weight of red pepper affected by nitrogen stress showed large differences between maximum and minimum values at the 120th DAT ranged from 48.2 to $196.6g\;plant^{-1}$, respectively. Several reflectance indices obtained from $GreenSeeker^{TM}$, $Crop\;Circle^{TM}$ and Spectroradiometer including chlorophyll readings were compared for evaluation of red pepper biomass. The reflectance indices such as rNDVI, aNDVI and gNDVI by the $Crop\;Circle^{TM}$ sensor showed the highest correlation coefficient with dry weight of red pepper at the 40th, 50th, and 80th DAT, respectively. Also these reflectance indices at the same growth station was closely correlated with dry weight, yield, and nitrogen uptake of red pepper at the 120th DAT, especially showing the best correlation coefficient at the 80th DAT. From these result, the aNDVI at the 80th DAT can significantly explain for dry weight of red pepper at the 120th DAT as well as for application level of nitrogen fertilizer. Consequently ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season nitrogen management for red pepper providing both spatial and temporal information.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.2
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• pp.126-136
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• 2008

Tobacco plants grown in pots by sand culture for 70 days after transplanting were used to evaluate the sensing distance and measurement efficiency of ground-based remote sensors. The leaf distribution of tobacco plant and sensing distance from the sensors to the target leaves were controlled by two removal methods of leaves, top-down and bottom-up removal. In the case of top-down removal, the canopy reflectance was measured by the sensor located at a fixed position having an optimum distance from the detector to the uppermost leaf of tobacco every time that the higher leaves were one at a time. The measurement of bottom-up removal, a the other hand, was conducted in the same manner as that of the top-down removal except that the lower leaves were removed one by one. Canopy reflectance measurements were made with hand held spectral sensors including the active sensors such as $GreenSeeker^{TM}$ red and green, $Crop\;Circle\;ACS-210^{TM}$ red and amber, the passive sensors of $Crop\:Circle^{TM}$, and spectroradiometer $SD2000^{TM}$. The reflectance indices by all sensors were generally affected by the upper canopy condition rather than lower canopy condition of tobacco regardless of sensor type, passive or active. The reflectance measurement by $GreenSeeker^{TM}$ was affected sensitively at measurement distance longer than 120 cm, the upper limit of effective sensing distance, beyond which measurement errors are appreciable. In case of the passive sensors that has no upper limit of effective distance and $Crop\;Circle^{TM}(ACS210)$ that has the upper limit of effective sensing distance specified with 213 cm, longer than that of estimated distance, the measurement efficiency affected by the sensing distance showed no difference. This result suggests that it is necessary to use the sensor specified optimum distance. The result revealed that active sensors are more superior than their passive counterparts in establishing between the relative ratio of reflectance index and the dry weight of tobacco treated by top-down removal, and in the evaluation of biomass. $The\;Crop\;Circle\;ACS-210^{TM}$ red was proved to have the highest efficiency of measurement, followed by $Crop\;Circle^{TM}(ACS210)$ amber and $GreenSeeker^{TM}$ red, $Crop\;Circle^{TM}$ passive, $GreenSeeker^{TM}$ green, and spectroradiometer, in descending order.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1321-1330
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• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.