• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1343-1356
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• 2022

Clouds or shadows are the most problematic when monitoring crops using optical satellite images. To reduce this effect, a composite algorithm was used to select the maximum Normalized Difference Vegetation Index (NDVI) for a certain period. This Maximum NDVI Composite (MNC) method reduces the influence of clouds, but since only the maximum NDVI value is used for a certain period, it is difficult to show the phenomenon immediately when the NDVI decreases. As a way to maintain the spectral information of crop as much as possible while minimizing the influence of clouds, a Score-Based Composite (SBC) algorithm was proposed, which is a method of selecting the most suitable pixels by defining various environmental factors and assigning scores to them when compositing. In this study, the Sentinel-2A/B Level 2A reflectance image and cloud, shadow, Aerosol Optical Thickness(AOT), obtainging date, sensor zenith angle provided as additional information were used for the SBC algorithm. As a result of applying the SBC algorithm with a 15-day and a monthly period for Dangjin rice fields and Taebaek highland cabbage fields in 2021, the 15-day period composited data showed faster detailed changes in NDVI than the monthly composited results, except for the rainy season affected by clouds. In certain images, a spatially heterogeneous part is seen due to partial date-by-date differences in the composited NDVI image, which is considered to be due to the inaccuracy of the cloud and shadow information used. In the future, we plan to improve the accuracy of input information and perform quantitative comparison with MNC-based composite algorithm.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.3
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• pp.246-253
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• 1988

This survey was carried out to obtain the basic information for the stable high yield of income-crops. Cropping systems, soil morphological and chemical properties were investigated. The obtained results were summarized as follows: 1. In Jinan and Jangsu, cultivated area of radish was 76.5% and.65.4%, respecitively, but in Unbong Chinese Cabbage, 71.1%, by second Crop. 2. In topographycal distribution, the mountain foot slope area in Jinan, Jangsu and Unbong was 69, 77 and 85%, respectively. In the distribution of elevation, semi-Alpine region in Jinan and Unbong was 85 and 69%, respectively, but Alpine region in Jangsu was 62%, of cultivated area. 3. Ploughing depth was 0 to 10 cm in Jinan and Jangsu, and 11 to 15cm, in Unbong. Gravel content class was 4th class in Jinan and 3rd class in Jangsu and Unbong. 4. For the distribution of soil types, normal upland came to 69.2% in Unbong, sandy and skeletal upland, 46.1 % and normal and sandy upland, 39 and 38%, respectively, in Jangsu. 5. The uplands soil classified as the 5th class, with improper for adequate cropping were. 6. For the chemical properties according to topography available phosphate $(-0.344^*)$, Ca $(-0.398^*)$, K $(-0.485^{**})$ and CEC $(-0.325^{**})$ showed the negative significancy with the elevation. 7. Among the variations of chemical properties by continuous cropping, the soil pH $(-0.491^{**})$ and the content of organic matter $(-0.434^{**})$, Ca $(-0.705^{**})$, CEC $(-0.512^{**})$, total nitrogen $(-0.559^{**})$ showed the high negative correlations, while the contents of available phosphate $(0.671^{**})$ and K $(0.543^{**})$ showed the high positive correlations, with the number of years of continuous cropping.

• Horticultural Science & Technology
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• v.28 no.3
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• pp.335-342
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• 2010

Sulforaphane (SFN) and total phenolics (TPC) contents and antioxidant activity (AA) were analyzed from 13 radish genotypes (Rhaphanus sativus L.), cultivated at 3 locations with different altitudes (Gangneung: asl 5 m, Jinbu: asl 550 m, and Daegwallyeong: asl 750 m). SFN varied greatly from 0.1 to $120.5{\mu}g{\cdot}g^{-1}$ in dry weight test and was significantly affected by location ($P{\leq}0.001$), genotype ($P{\leq}0.001$) and $location{\times}genotype$ interaction ($P{\leq}0.01$). Radishes, cultivated at Daegwallyeong site, showed higher SFN than those of other locations. Among different genotypes, the root of 'Black radish' and leaves of 'Purunmu' of Daegwallyeong had the highest SFN (107.8 and $120.5{\mu}g{\cdot}g^{-1}$, respectively). TPC in root was affected by genotype ($P{\leq}0.001$), and $location{\times}genotype$ interaction ($P{\leq}0.01$), but not by location. In leaves, TPC was affected by location ($P{\leq}0.01$), genotype ($P{\leq}0.001$), and $location{\times}genotype$ interaction ($P{\leq}0.001$). AA expressed as electron donating ability was significantly influenced by location, genotype and $location{\times}genotype$ interaction and correlated positively with TPC ($Pearson's$ $r$=0.897) in root. These results suggest that radish could be a good source of functional food and high altitude location such as Daegwallyeong has potential for the production of radish with high content of health promoting factors.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.3
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• pp.361-367
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• 2011

Soil fertility of alpine soils in Gangwon-Do has been deteriorating because of heavy input of chemical fertilizers for intensive crop production. To reduce application of chemical fertilizers, use of livestock manure compost in alpine soils increases consistently. Soil loss and runoff due to heavy rainfall in alpine area cause nutrient loss from soil, and subsequently pollute stream water. Therefore, the objective of this study was to assess nutrient efficiency and loss in Chinese cabbage cultivated soil with different livestock manure composts in several slopes. As control, chemical fertilizer was applied at the rate of $250-78-168kg\;ha^{-1}$ for $N-P_2O_5-K_2O$. Each pig-and chicken manure compost was applied at the rate of $10MT\;ha^{-1}$. Chemical fertilizer + chicken manure compost was applied as same rate. Four treatments was practiced in 5, 20, and 35% filed slopes, respectively. We monitored the amounts of soil loss and runoff water after rainfalls, and we also analyzed the contents of nutrients in soil and runoff water through lysimeter installed in alpine agricultural institute in Gangwon-Do. T-N loss due to soil loss was much greater with increasing filed slops rather than different fertilizer treatments. T-N loss has positive relationship with field slopes, which showing soil loss (MT/ha) = 1.66 slopes (%) - 3.5 ($r^2$ = 0.99). Available phosphate and exchangeable cations showed similar tendency with increasing slopes. T-N and T-P losses caused by runoff water were highest in chemical fertilizer (NPK) + chicken manure compost treated plot, while lowest in chemical fertilizer treatment. T-N contents (2.13, 1.95%) in chinese cabbage treated either pig and chicken manure composts compared to that (2.65%) of chemical fertilizer were significantly less. This could be resulted from much greater T-N loss in soil treated with pig and chicken manure composts.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.989-998
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• 2021

In the utilization of optical satellite imagery, which is greatly affected by clouds, periodic composite technique is a useful method to minimize the influence of clouds. Recently, a technique for selecting the optimal pixel that is least affected by the cloud and shadow during a certain period by directly inputting cloud and cloud shadow information during period compositing has been proposed. Accurate extraction of clouds and cloud shadowsis essential in order to derive optimal composite results. Also, in the case of an surface targets where spectral information is important, such as crops, the loss of spectral information should be minimized during cloud-free compositing. In thisstudy, clouds using two spectral indicators (Haze Optimized Tranformation and MeanVis) were used to derive a detection technique with low loss ofspectral information while maintaining high detection accuracy of clouds and cloud shadowsfor cabbage fieldsin the highlands of Gangwon-do. These detection results were compared and analyzed with cloud and cloud shadow information provided by Sentinel-2A/B. As a result of analyzing data from 2019 to 2021, cloud information from Sentinel-2A/B satellites showed detection accuracy with an F1 value of 0.91, but bright artifacts were falsely detected as clouds. On the other hand, the cloud detection result obtained by applying the threshold (=0.05) to the HOT showed relatively low detection accuracy (F1=0.72), but the loss ofspectral information was minimized due to the small number of false positives. In the case of cloud shadows, only minimal shadows were detected in the Sentinel-2A/B additional layer, but when a threshold (= 0.015) was applied to MeanVis, cloud shadowsthat could be distinguished from the topographically generated shadows could be detected. By inputting spectral indicators-based cloud and shadow information,stable monthly cloud-free composited vegetation index results were obtained, and in the future, high-accuracy cloud information of Sentinel-2A/B will be input to periodic cloud-free composite for comparison.