• Journal of Korean Society of Forest Science
• /
• v.70 no.1
• /
• pp.91-102
• /
• 1985

Growth and biomass production of natural stands of Quercus variabilis in relation to tree density were studied to obtain basic guide lines for future tending operation. Two natural stands of Quercus variabilis located at 900m (A stand: 6,600trees/ha, $15.84m^2/ha$, $\frac{19}{17-20}$) and 800m (B stand: 4,300trees/ha, $16.65m^2/ha$, $\frac{20}{17-21}$) elevation in Sancheong, Kyongnam Province were selected for the comparative study and following results were obtained through a sample plot method. After diameter of individual trees in the sample plots was measured, twelve average trees from each diameter class were cut felled to measure dry weight of $W_S$, $W_B$, $W_L$, $W_{Ba}$, and standing biomass and biomass production rates by a allometrior regressions related to $D^2H$. Vertical distribution of leaves along the stems indicated that photosynthesis was carried out 2.2m above the ground in Stand A and 1.2m in Stand B. Maximum photosynthesis was located 4.2m and 6.2m above the ground in Stand A and B, respectively. Leaf area index was 4.25ha/ha for Stand A, and 3.89ha/ha for Stand B. Above-ground standing biomass was 49.51 ton/ha for Stand A and 59.20 ton/ha and net annual production was 6.75 ton/ha/yr. for Stand A and 8.99 ton/ha/yr. for Stand B. The ratio of net annual production to standing biomass was 17.5% for Stand A and 16.7% for Stand B. Net assimilation rate was 2.75kg/kg/yr. for Stand A and 3.58kg/kg/yr. for Stand B. Stem wood production rate was 1.46kg/kg/yr. for Stand A and 2.09kg/kg/yr. for Stand B. Bark production rate was 0.60 kg/kg/yr. for Stand A and 0.34kg/kg/yr. for Stand B. Above data indicated that Stand B utilized growing spaces and sites more efficiently than Stand A. It is concluded chat productivity of natural stands of Quercus variabilis can be enhanced through optimization of basal areas and number of tree per hectare and that sound management of natural oak stands should be based on systematic sampling of the area for periodic productivity estimation.

• Korean Journal of Soil Science and Fertilizer
• /
• v.45 no.2
• /
• pp.127-134
• /
• 2012

Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage ($r{\leq}0.50$). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content ($R^2=0.92$). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.2
• /
• pp.175-182
• /
• 2018

Knowledge of the optimum cultivation period for Chinese cabbage would help growers especially in spring in Korea. Growth and yield of Chinese cabbage in a temperature gradient chamber was evaluated for the growing periods of 64 days from three set of transplanting dates including March 6, March 20, and April 3 in 2017. Air temperature in the chamber was elevated step-by-step, by $2^{\circ}C$ above the ambient temperature. This increment was divided into three phases; i.e. low (ambient+$2^{\circ}C$, A), medium (ambient+$4^{\circ}C$, B), and high temperature (ambient+$6^{\circ}C$, C). The fresh weight of Chinese cabbage was greater under B and C conditions in the first period and A in the second period, which indicated that GDDs affected the fresh weight considerably. However, leaf growth (number, area, length, and width) did not differ by GDDs. Bolting appeared under A condition in the first period, which was caused by low temperature in the early growth stage. Soft rot was developed under C condition in the second period and all temperature conditions in the third period, which resulted from high temperature in the late stage. Fresh weight increased when GDDs ranged from 587 to 729. However, it decreased when GDDs > 729. The maximum expected yield (16.3 MT/10a) was attained for the growing period of 64 days from transplanting date during which GDDs reached 601. The GDDs for optimum cultivation ranged from 478-724 under which the yield was about 95% (15.5 MT/10a) of maximum fresh weight. Such an optimum condition for GDDs was validated at five main cultivation regions including Jindo, Haenam, Naju, Seosan, and Pyeongtaek in Korea. In these regions, GDDs ranged from 619-719. This suggested that the optimum GDDs for Chinese cabbage cultivation would range from 478-724, which would give the useful information to expect the cultivation periods for ensuring maximum yield.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.3
• /
• pp.217-226
• /
• 2015

To investigate the distributions of BVOCs (Biogenic Volatile Organic Compounds) from mountain near mega city and their role in forest atmospheric, BVOCs and their oxidized species were measured at a 41 m tower in Mt. Taehwa during May, June and August 2013. A proton transfer reaction-mass spectrometer (PTR-MS) was used to quantify isoprene and monoterpenes. In conjunction with BVOCs, $O_3$, meteorological parameters, PAR (Photosynthetically Active Radiation) and LAI (Leaf Area Index) were measured. The average concentrations of isoprene and monoterpenes were 0.71 ppbv and 0.17 ppbv, respectively. BVOCs showed higher concentrations in the early summer (June) compared to the late summer (August). Isoprene started increasing at 2 PM and reached the maximum concentration around 5 PM. In contrast, monoterpenes concentrations began to increase 4 PM and stayed high at night. The $O_3$ maximum was generally found at 3 PM and remained high until 5 PM or later, which was concurrent with the enhancement of $O_3$. The concentrations of BVOCs were higher below canopy (18 m) than above canopy, which indicated these species were produced by trees. At night, monoterpenes concentrations were negatively correlated with these of $O_3$ below canopy. Using MEGAN (Model of Emissions of Gases and Aerosols from Nature), the emissions of isoprene and monoterpenes were estimated at 1.1 ton/year and 0.9 ton/year, respectively at Mt. Taehwa.

• Journal of Korea Water Resources Association
• /
• v.42 no.11
• /
• pp.911-920
• /
• 2009

Virtual water is defined as the volume of water required to produce a commodity or service. The degree of food self-sufficiency is currently about 27 % in South Korea, so that Korea is one of the largest net virtual water import countries for agricultural product, thus it is necessary to estimate suitable virtual water for South Korea. The objective of this paper is to quantify the agricultural virtual water use (AWU) and virtual water content (VWC) using the method suggested by Chapagain and Hoekstra during the period 1991-2007. To calculate the virtual water content, 44 different crop production quantity and harvested area data were collected for 17 years and FAO Penman-Monteith equation was adapted for computing crop consumptive use of water. As the results, AWU has been estimated at 15.1 billion $m^3$ in average showing a tendency to decrease. Rice has the largest share in the AWU, consuming about 10.1 billion $m^3$/yr which is about 75 % of gross AWU, and the VWC is 1600.1 $m^3$/ton for paddy rice. The largest VWCs of crops are oilseed and tuber crop, and the smallest are leaf and root vegetables. The primary crop production VWC can be used for calculating the VWC of various secondary products using the contribution ratio, therefore the results of this study are expected to be used as basic data for national agricultural water footprint.

• Korean Journal of Remote Sensing
• /
• v.25 no.1
• /
• pp.31-44
• /
• 2009

The objective of this study was to measure backscattering coefficients of paddy rice using a L-, C-, and X-band scatterometer system with full polarization and various angles during the rice growth period and to relate backscattering coefficients to rice growth parameters. Radar backscattering measurements of paddy rice field using multifrequency (L, C, and X) and full polarization were conducted at an experimental field located in National Academy of Agricultural Science (NAAS), Suwon, Korea. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector network analyzer ($20\;MHz{\sim}20\;GHz$), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying radar equation for the measured at incidence angles between $20^{\circ}$ and $60^{\circ}$ with $5^{\circ}$ interval for four polarization (HH, VV, HV, VH), respectively. We measured the temporal variations of backscattering coefficients of the rice crop at L-, C-, X-band during a rice growth period. In three bands, VV-polarized backscattering coefficients were higher than hh-polarized backscattering coefficients during rooting stage (mid-June) and HH-polarized backscattering coefficients were higher than VV-, HV/VH-polarized backscattering coefficients after panicle initiation stage (mid-July). Cross polarized backscattering coefficients in X-band increased towards the heading stage (mid-Aug) and thereafter saturated, again increased near the harvesting season. Backscattering coefficients of range at X-band were lower than that of L-, C-band. HH-, VV-polarized ${\sigma}^{\circ}$ steadily increased toward panicle initiation stage and thereafter decreased, and again increased near the harvesting season. We plotted the relationship between backscattering coefficients with L-, C-, X-band and rice growth parameters. Biomass was correlated with L-band hh-polarization at a large incident angle. LAI (Leaf Area Index) was highly correlated with C-band HH- and cross-polarizations. Grain weight was correlated with backscattering coefficients of X-band VV-polarization at a large incidence angle. X-band was sensitive to grain maturity during the post heading stage.

• Korean Journal of Soil Science and Fertilizer
• /
• v.44 no.5
• /
• pp.878-886
• /
• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.329-339
• /
• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.