Background: Tropical montane forests played an important role in the provision of ecosystem services. The intense degradation and deforestation for the need of agricultural land expansion result in a significant decline of forest cover. However, the expansion of agricultural land did not completely destruct natural forests. There remain forests inaccessible for agricultural and grazing purpose. Studies on these forests remained scant, motivating to investigate biomass and soil carbon stocks. Data of biomass and soils were collected in 80 quadrats ($400m^2$) systematically in 5 forests. Biomass and disturbance gradients were determined using allometric equation and disturbance index, respectively. The regression modeling is employed to explore the spatial distribution of carbon stock along disturbance and environmental gradients. Correlation analysis is also employed to identify the relation between site factors and carbon stocks. Results: The result revealed that a total of 1655 individuals with a diameter of ${\geq}5cm$, representing 38 species, were measured in 5 forests. The mean aboveground biomass carbon stocks (AGB CS) and soil organic carbon (SOC) stocks at 5 forests were $191.6{\pm}19.7$ and $149.32{\pm}6.8Mg\;C\;ha^{-1}$, respectively. The AGB CS exhibited significant (P < 0.05) positive correlation with SOC and total nitrogen (TN) stocks, reflecting that biomass seems to be a general predictor of SOCs. AGB CS between highly and least-disturbed forests was significantly different (P < 0.05). This disturbance level equates to a decrease in AGB CS of 36.8% in the highly disturbed compared with the least-disturbed forest. In all forests, dominant species sequestrated more than 58% of carbon. The AGB CS in response to elevation and disturbance index and SOC stocks in response to soil pH attained unimodal pattern. The stand structures, such as canopy cover and basal area, had significant positive relation with AGB CS. Conclusions: Study results confirmed that carbon stocks of studied forests were comparable to carbon stocks of protected forests. The biotic, edaphic, topographic, and disturbance factors played a significant variation in carbon stocks of forests. Further study should be conducted to quantify carbon stocks of herbaceous, litter, and soil microbes to account the role of the whole forest ecosystem.
Cho, Yong Chan;Kim, Jun Soo;Lee, Chang Seok;Cho, Hyun Je;Lee, Ho Yeong;Bae, Kwan Ho
Journal of Korean Society of Forest Science
/
v.100
no.2
/
pp.240-245
/
2011
Vegetation changes were studied for 16 yr in clearcut logged Pinus densiflora forests in the southern Gangwon-do province in Korea by applying chronosequence approach. Ambient temperature and relative humidity, Detrended Correspondence Analysis (DCA), Multiple Responses Permutation Procedure (MRPP), Indicator Species Analysis (ISPAN) were used to examine successional trajectory and compositional changes. After clearcutting, canopy openness was increased abruptly at three folds (1yr 68.3% and R1 23.0%) and then decreased, but relative moisture was slightly decreased (6%) compare to control site. In the result of DCA, right after clear cutting, vegetation composition was developed heterogeneously compared to control sites, and then approached to control sites within 16 years. Based on MRPP, species composition of each developmental stages (1yr, 3yr, 10yr and 16yr) revealed signigicant differences to that of control vegetation (R1, R3, R10 and R16). Indicator species in 1yr and 3yr samples included various woody species rather than herbaceous species, but in 10yr and 16yr, herbaceous were more abundant. Earlier succession of pine forests likely can explain to Initial Floristic Composition (IFC) Model.
In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.
This study was carried out to predict fruit surface temperature (FST) causing sunburn symptoms and assess the correlation between solar radiation and FST in satusma mandarin (Citrus unshiu Marc. 'Iwasaki'). And to reduce sunburn when ambient temperature was at 31℃, sprinkler system was repeated spraying every at 5 minutes of 30 minutes intervals and 1% calcium carbonate and 4% kaolin solution applied on citrus tree three times to investigate quality and sunburn of fruits. It showed highly significant positive correlation between FST and solar radiation (R = 0.788, p < 0.01), The FST increased up to 16℃ than ambient temperature at daytime. To estimate FST, a linear model y = 0.099 × (air temperature) + 0.018 × (solar radiation) + 20.779 (R = 0.687, p < 0.01) was derived. The canopy temperature of citrus trees was 5.1℃ lower in sprinkler system than in control. The incidence of sunburn showed at 2.1% in sprinkler system twice lower than in control and there was different significance. Fruit quality was similar between treatments. In conclusion, sunburn can be reduced by reflecting sunlight or downing of FST through sprinkler system.
Hyun-Dong Moon;Bo-Kyeong Kim;Kyeong-Min Kim;Subin Choi;Euni Jo;Hoyong Ahn;Jae-Hyun Ryu;Sung-Won Choi;Jaeil Cho
Korean Journal of Remote Sensing
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v.39
no.6_1
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pp.1427-1435
/
2023
Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, the anisotropic properties of the crop canopy surface can govern spectral reflectance and vegetation indices. In this study, we applied an ensemble of bidirectional reflectance distribution function (BRDF) models to high-resolution Sentinel-2 satellite imagery and compared the differences between correction results before and after reflectance. In the red and near-infrared (NIR) band reflectance images, BRDF-corrected outlier values appeared in certain urban and paddy fields of farmland areas and forest shadow areas. These effects were equally observed when calculating the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2). Furthermore, the outlier values in corrected NIR band were shown in pixels shadowed by mountain terrain. These results are expected to contribute to the development and improvement of BRDF models in high-resolution satellite images.
The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.
Lee In-Bok;Yun Nam-Kyu;Boulard Thierry;Roy Jean Claude;Lee Sung-Hyoun;Kim Gyoeng-Won;Hong Se-Woon;Sung Si-Heung
Journal of Bio-Environment Control
/
v.15
no.4
/
pp.296-305
/
2006
The heterogeneity of crop transpiration is important to clearly understand the microclimate mechanisms and to efficiently handle the water resource in greenhouses. A computational fluid dynamic program (Fluent CFD version 6.2) was developed to study the internal climate and crop transpiration distributions of greenhouses. Additionally, the global solar radiation model and a crop heat exchange model were programmed together. Those models programmed using $C^{++}$ software were connected to the CFD main module using the user define function (UDF) technology. For the developed CFD validity, a field experiment was conducted at a $17{\times}6 m^2$ plastic-covered mechanically ventilated single-span greenhouse located at Pusan in Korea. The CFD internal distributions of air temperature, relative humidity, and air velocity at 1m height were validated against the experimental results. The CFD computed results were in close agreement with the measured distributions of the air temperature, relative humidity, and air velocity along the greenhouse. The averaged errors of their CFD computed results were 2.2%,2.1%, and 7.7%, respectively.
This study has analyzed the vegetation structure to suggest a vegetation ecological restoration model by using the case of the afforestation for erosion control area with Pinus koreaiensis and Betula platyphylla, etc., on the hills of the Young-in mountains after its great fire in 2000. Of the area having a dimension of $1,152,404.3m^2$ selected as a survey site for the existing vegetation, the forest fire area accounted for 69.2% among which, brushwoods accounted the most for 24.67%. As a result of analysis of the 27 surveyed unit plots[unit dimension: $100m^2$] set up in consideration of the existing vegetation pattern and damaged state from the forest fire, the surveyed area was classified into 10 communities. Shrub layer's vegetation was found to be dominant in forest fire areas and the surveyed sites were classified into 5 plant communities, i.e. P. koraiensis community, Quercus variabilis community, P. thunbergii community, Q. serrata community, B. platyphylla community in forest fire areas, while non-forest fire areas were classified into 5 plant communities, such as P. densiflora community, Q. acutissima community, Q. serrata community, Q. mongolica-Q. serrata community, B. platyphylla community. Species diversity of forest fire areas was $0.3679{\sim}0.5907$ and that of non-forest fire areas was $0.5728{\sim}0.8865$. In addition, the number of the species in the forest fire areas was $5{\sim}8$ and that of non-forest areas was $8{\sim}12$; however, the population of forest fire areas$(156{\sim}456)$ was higher than that of non-forest fire areas$(61{\sim}227)$. In the analysis of growth density per layer$[of\;100m^2]$, there appeared $1{\sim}8$ trees of Q. mongolica and $3{\sim}5$ trees of Q. serrata in the upper layer species; $2{\sim}4$ trees of Q. serrata and one tree of Q. mongolica in the canopy layer. As for the characteristics of soil, acidity of forest fire areas was pH 5.45 and that of non-forest fire was pH 5.25. By setting up the middle D.B.H range of Q. mongolica-Q. serrata community as the vegetation restoration model, planting species, planting density and planting models are suggested.
The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66%, followed by G$\times$E interaction variability, 21%, and variability by environment, 13%. G$\times$E interaction was partitioned into two significant (P<0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.
A statistical model to predict soil temperature from the ambient meteorological factors including mean, maximum and minimum air temperatures, precipitation, wind speed and snow depth combined with Fourier time series expansion was developed with the data measured at the Suwon Meteorolical Service from 1979 to 1988. The stepwise elimination technique was used for statistical analysis. For the yearly oscillation model for soil temperature with 8 terms of Fourier expansion, the mean square error was decreased with soil depth showing 2.30 for the surface temperature, and 1.34-0.42 for 5 to 500-cm soil temperatures. The $r^2$ ranged from 0.913 to 0.988. The number of lag days of air temperature by remainder analysis was 0 day for the soil surface temperature, -1 day for 5 to 30-cm soil temperature, and -2 days for 50-cm soil temperature. The number of lag days for precipitaion, snow depth and wind speed was -1 day for the 0 to 10-cm soil temperatures, and -2 to -3 days for the 30 to 50-cm soil teperatures. For the statistical soil temperature prediction model combined with the yearly oscillation terms and meteorological factors as remainder terms considering the lag days obtained above, the mean square error was 1.64 for the soil surfac temperature, and ranged 1.34-0.42 for 5 to 500cm soil temperatures. The model test with 1978 data independent to model development resulted in good agreement with $r^2$ ranged 0.976 to 0.996. The magnitudes of coeffcicients implied that the soil depth where daily meteorological variables night affect soil temperature was 30 to 50 cm. In the models, solar radiation was not included as a independent variable ; however, in a seperated analysis on relationship between the difference(${\Delta}Tmxs$) of the maximum soil temperature and the maximum air temperature and solar radiation(Rs ; $J\;m^{-2}$) under a corn canopy showed linear relationship as $${\Delta}Tmxs=0.902+1.924{\times}10^{-3}$$ Rs for leaf area index lower than 2 $${\Delta}Tmxs=0.274+8.881{\times}10^{-4}$$ Rs for leaf area index higher than 2.
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