• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.5
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• pp.59-69
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• 2013

Global warming also has effects on the phenology. The limitation of phenology study is an acquisition of phenology data. Satellite images analysis can make up limitation of monitering data. This study is to analyze spatial distribution and characteristics of phenology changes using MODIS images. Research data collected images of 16 day intervals of 11 years from year 2001 to 2010. The data analyzed 228 images of 11 years. It can figure out changes of phenology by analyzing enhanced vegetation index of MODIS image. We made a comparison between changes of phenology and flowering of cherry blossoms. As a results, Startup of season spatially was getting late from southern area to north area. Startup of Phenology was foreshortened 13 days during 11 years, and change ratios of cherry blooming was getting more faster from 0.18 dat to 0.22 day per year during that same period.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.179-190
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• 2024

This study aims to compare supervised classification methods with phenology-based approaches, specifically pixel-based and segment-based methods, for accurate crop mapping in agricultural landscapes. We utilized Sentinel-2A imagery, which provides multispectral data for accurate crop mapping. 31 normalized difference vegetation index (NDVI) images were calculated from the Sentinel-2A data. Next, we employed phenology-based approaches to extract valuable information from the NDVI time series. A set of 10 phenology metrics was extracted from the NDVI data. For the supervised classification, we employed the maximum likelihood (MaxLike) algorithm. For the phenology-based approaches, we implemented both pixel-based and segment-based methods. The results indicate that phenology-based approaches outperformed the MaxLike algorithm in regions with frequent rainfall and cloudy conditions. The segment-based phenology approach demonstrated the highest kappa coefficient of 0.85, indicating a high level of agreement with the ground truth data. The pixel-based phenology approach also achieved a commendable kappa coefficient of 0.81, indicating its effectiveness in accurately classifying the crop types. On the other hand, the supervised classification method (MaxLike) yielded a lower kappa coefficient of 0.74. Our study suggests that segment-based phenology mapping is a suitable approach for regions like South Korea, where continuous cloud-free satellite images are scarce. However, establishing precise classification thresholds remains challenging due to the lack of adequately sampled NDVI data. Despite this limitation, the phenology-based approach demonstrates its potential in crop classification, particularly in regions with varying weather patterns.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.318-329
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• 2022

Plant phenology including flowering, leaf unfolding, and leaf coloring in a forest is important to understand the forest ecosystem. Temperature rise due to recent climate change, however, can lead to plant phenology change as well as snowfall in winter season. Therefore, accurate monitoring of forest environment changes such as plant phenology and snow cover is essential to understand the climate change effect on forest management. These changes can monitor using a digital camera system. This paper introduces the detection methods for plant phenology and snow cover at the mountain region using an unmanned camera system that is a way to monitor the change of forest environment. In this study, the Automatic Mountain Meteorology Stations (AMOS) operated by Korea Forest Service (KFS) were selected as the testbed sites in order to systematize the plant phenology and snow cover detection in complex mountain areas. Multi-directional Internet Protocol (IP) camera system that is a kind of unmanned camera was installed at AMOS located in Seoul, Pyeongchang, Geochang, and Uljin. To detect the forest plant phenology and snow cover, the Red-Green-Blue (RGB) analysis based on the IP camera imagery was developed. The results produced by using image analysis captured from IP camera showed good performance in comparison with in-situ data. This result indicates that the utilization technique of IP camera system can capture the forest environment effectively and can be applied to various forest fields such as secure safety, forest ecosystem and disaster management, forestry, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.11-18
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• 2012

Daily temperature data produced by harmonic analysis of monthly climate summary have been used as an input to plant phenology model. This study was carried out to evaluate the performance of the harmonic based daily temperature data in prediction of major phenological developments and to apply the results in improving decision support for agricultural production in relation to the climate change scenarios. Daily maximum and minimum temperature data for a climatological normal year (Jan. 1 to Dec. 31, 1971-2000) were produced by harmonic analysis of the monthly climate means for Seoul weather station. The data were used as inputs to a thermal time - based phenology model to predict dormancy, budburst, and flowering of Japanese cherry in Seoul. Daily temperature measurements at Seoul station from 1971 to 2000 were used to run the same model and the results were compared with the harmonic data case. Leaving no information on annual variation aside, the harmonic based simulation showed 25 days earlier release from endodormancy, 57 days longer period for maximum cold tolerance, delayed budburst and flowering by 14 and 13 days, respectively, compared with the simulation based on the observed data. As an alternative to the harmonic data, 30 years daily temperature data were generated by a stochastic process (SIMMETEO + WGEN) using climatic summary of Seoul station for 1971-2000. When these data were used to simulate major phenology of Japanese cherry for 30 years, deviations from the results using observed data were much less than the harmonic data case: 6 days earlier dormancy release, 10 days reduction in maximum cold tolerance period, only 3 and 2 days delay in budburst and flowering, respectively. Inter-annual variation in phenological developments was also in accordance with the observed data. If stochastically generated temperature data could be used in agroclimatic mapping and zoning, more reliable and practical aids will be available to climate change adaptation policy or decision makers.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1633-1641
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• 2013

The objective of this study was to analyze correlation between phenological characteristics of Salix spp. and meteorological factors in the Upo wetlands. Phenology of Salix subfragilis Andersson and Salix chaenomeloides Kimura was monitored from 2007 to 2012. Meteorological variables were monitored by Korea Meteorological Administration (Hap-chon). Average date of flowering, fruiting, seed dispersion was 86, 113, 136 days for S. subfragilis and 112, 140, 164 days for S. chaenomeloides as Julian days. Flowering of S. subfragilis and S. chaenomeloides were correlated with daily mean air temp. in March (r=-0.92, r=-0.85, p<0.05). Fruiting of S. subfragilis was correlated with total precipitation between Jan and March of previous year (r=-0.90, p<0.01), however, the fruiting of S. chaenomeloides was highly correlated with max. temp. in Jan of previous year (r=0.99, p<0.01). Seed dispersion of both species is correlated with min. temp. in Feb. Phenology monitoring will contribute to understanding Salix spp. response against climate change.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.30-42
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• 2016

Climate change are known to have had enormous impacts on plant phenology and thus to have damage on other species which are interacted within ecosystem. In Korea, however, it is difficult to analyze the relationship between climate and phenology due to the limitation of measurement data of plant phenological records. In this study, to be effective analysis of SOG(start of growing season), we used phenological transition dates by using satellite data. Then, we identified the most influential variable in variation of SOG throughout the relationship between SOG and temperature factors. As a result, there is a strong correlation between the SOG and April temperature, TSOGmin($3^{\circ}C$, 12days). This study is expected to be used for predicting plant phenological change using climate change scenario data.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.149-153
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• 1999

Prediction of rice developmental stage is necessary for proper crop management and a prerequisite for growth simulation as well. The objectives of the present study were to find out the relationship between the plastochrone index(PI) and the developmental index(DVI) estimated by non-parametric phenology model which simulates the duration from seedling emergence(DVI=0) to heading(DVI=l) by employing daily mean air temperature and daylength as predictor variables, and to confirm the correspondency of developmental indice to panicle developmental stages based on this relationship. Four japonica rice cultivars, Kwanakbyeo, Sangpungbyeo, Dongjinbyeo, and Palgumbyeo which range from very early to very late in maturity, were grown by sowing directly in dry paddy field five times at an interval of two weeks. Data for seedling emergence, leaf appearance, differentiation stage of primary rachis branch and heading were collected. The non-parametric phenology model predicted well the duration from seedling emergence to heading with errors of less than three days in all sowings and cultivars. PI was calculated for every leaf appearance and related to the developmental index estimated for corresponding PI. The stepwise polynomial analysis produced highly significant square-rooted cubic or biquadratic equations depending on cultivars, and highly significant square-rooted biquadratic equation for pooled data across cultivars without any considerable reduction in accuracy compared to that for each cultivar. To confirm the applicability of this equation in predicting the panicle developmental stage, DVI at differentiation stage of primary rachis branch primordium was calculated by substituting PI with 82 corresponding to this stage, and the duration reaching this DVI from seedling emergence was estimated. The estimated duration revealed a good agreement with that observed in all sowings and cultivars. The deviations between the estimated and the observed were not greater than three days, and significant difference in accuracy was not found for predicting this developmental stage between those equations derived for each cultivar and for pooled data across all cultivars tested.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Journal of Ecology and Environment
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• v.47 no.3
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• pp.134-145
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• 2023

Background: The flowering and fruiting periods play an important role in biological processes. The deciduous dipterocarp forest is an important forest type in Thailand, however the phenological studies are still limited, particularly in different plant life forms. Thus, the present study focused on the flowering and fruiting phenology of herbs, climbers, shrubs, and trees in the deciduous dipterocarp forest at Lampang province of Northern Thailand. Field visits were made to record plant life forms and observe reproductive phenological events at monthly intervals from November 2018 to October 2019 and September to December 2020. Results: The phenological observations were based on 126 species of 45 families and 102 genera. Flowering and fruiting periods showed similar patterns in herbaceous plants, climbers, and shrubs. Most of these species produced flowers and fruits from the end of the rainy season (October) to the winter season (November-January). Whereas most of flowering and fruiting trees were found from the summer season (March-April) to the beginning of the rainy season (May-June). Most of the dry-fruited species occurred during the dry period (winter and summer seasons), while the majority of fleshy-fruited species dominated in the wet period (rainy season). The statistical analysis supported the phenological patterns of flowering and fruiting in the present study. There were significant negative correlations between the number of flowering and fruiting species and temperature. The number of flowering and fruiting species is significantly impacted by the interaction between seasons and plant life forms. Conclusions: Plant life form seems to be the important factor that affects the different phenological patterns in the studied plants. The abiotic and biotic factors play major roles in reproductive phenology. However, long-term study and in-depth phenological observations are necessary for better understanding.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.213-218
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• 2014

Effects of elevated $CO_2$ on leaf phenology of Quercus acutissima were examined using open-top chambers, which had ambient and elevated $CO_2$ concentrations (ambient ${\times}1.4$, ambient ${\times}1.8$). To analyze the effect of chamber, non-treatment block was established near outside of the chambers. In 2013, budburst, leaf unfolding, coloring, and shedding were surveyed, and spring phenology was surveyed in 2014. Thermal sum (base temperature $+5^{\circ}C$) of each phenological event occurred was recorded. In addition, bud samples were collected and analyzed for carbohydrate contents in March 2014. Elevated $CO_2$ concentration advanced budburst and leaf unfolding, and delayed shedding in 2013. However, in 2014, the temperature of the spring season was high, and there was no significant effect of elevated $CO_2$ concentration on spring phenology. Carbohydrates content, such as starch, total non-structural carbohydrate and total soluble sugar, were significantly increased in response to elevated $CO_2$ concentration. It has been proposed that elevated $CO_2$ concentration could extend the growing season of temperate species with increased possibility of frost damage due to early bud opening and leaf unfolding. However, our analysis showed that the increased carbohydrate concentration in bud under elevated $CO_2$ would reduce the possibility of early spring frost damage by acting as cryoprotectant.