• Korean Journal of Environment and Ecology
• /
• v.23 no.5
• /
• pp.418-430
• /
• 2009

The main purpose of this study is to investigate the relationship between the topography of land and vegetation and the preferred habitat of wintering cranes. Investigations were conducted twelve times in Cheorwon basin, South Korea, during two wintering seasons (12/2005 - 2/2006; 1/2007 - 2/2007). The density of rice grain in the middle of rice paddies was higher than that of the areas along the edge of rice paddies. However it was observed that red-naped cranes preferred to feed along the edges of rice paddies rather than to feed in the middle of the paddies. White-naped cranes, on the other hand, Preferred to feed in the middle of paddies. To be more specific, red-crowned cranes preferred feeding sites such as levees of the paddies or the areas where the level of the rice beds was comparatively more elevated. But the preference of the white-naped cranes turned out to be just the opposite. Another finding was that both red-naped cranes and white-naped cranes preferred concealed areas for their feeding site, and the frequency rate of their feeding in concealed areas has little to do with weather factors. This finding contradicts a widely accepted view that cranes prefer open spaces for their feeding site. Besides, red-crowned cranes, compared with white-naped cranes, preferred to feed in more concealed areas. The frequency rate of feeding in both concealed areas and non-concealed areas had little to do with the size of feeding flocks. There was no difference between a flock of fewer than five cranes and a flock of more than five cranes in terms of frequency rate of their feeding. In conclusion, the result of these investigations indicate that red-naped cranes comparatively prefer concealed areas for their feeding site, and white-naped cranes are less prone to them, and there is no direct connection between their preference of feeding site or frequency and the size of their flock. This is presumed to be the characteristics unique to their individual species.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1029-1042
• /
• 2021

As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500-4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, thisstudy performed a sensitivity analysis of the key parameters (AOD, WV, and O₃) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysisshowed that AOD wasthe most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.4
• /
• pp.317-326
• /
• 2019

Salinity which is often detected on reclaimed land is a major detrimental factor to crop growth. It would be advantageous to develop an approach for assessment of salinity and drought damages using a non-destructive method in a large landfills area. The objective of this study was to examine applicability of the decision tree classifier using imagery for classifying for spring potatoes (Solanum tuberosum) damaged by salinity or drought at vegetation growth stages. We focused on comparing the accuracies of OA (Overall accuracy) and KC (Kappa coefficient) between the simple reflectance and the band ratios minimizing the effect on the light unevenness. Spectral merging based on the commercial band width with full width at half maximum (FWHM) such as 10 nm, 25 nm, and 50 nm was also considered to invent the multispectral image sensor. In the case of the classification based on original simple reflectance with 5 nm of FWHM, the selected bands ranged from 3-13 bands with the accuracy of less than 66.7% of OA and 40.8% of KC in all FWHMs. The maximum values of OA and KC values were 78.7% and 57.7%, respectively, with 10 nm of FWHM to classify salinity and drought damages of spring potato. When the classifier was built based on the band ratios, the accuracy was more than 95% of OA and KC regardless of growth stages and FWHMs. If the multispectral image sensor is made with the six bands (the ratios of three bands) with 10 nm of FWHM, it is possible to classify the damaged spring potato by salinity or drought using the reflectance of images with 91.3% of OA and 85.0% of KC.

• Korean Journal of Remote Sensing
• /
• v.35 no.2
• /
• pp.251-263
• /
• 2019

Sentinel-2 Multi Spectral Instrument(MSI) launched by the European Space Agency (ESA) offered high spatial resolution optical products, enhanced temporal revisit of five days, and 13 spectral bands in the visible, near infrared and shortwave infrared wavelengths similar to Landsat mission. Landsat satellite imagery has been applied to various previous studies, but Sentinel-2 optical satellite imagery has not been widely used. Currently, for global coverage, Sentinel-2 products are systematically processed and distributed to Level-1C (L1C) products which contain the Top-of-Atmosphere (TOA) reflectance. Furthermore, ESA plans a systematic global production of Level-2A(L2A) product including the atmospheric corrected Bottom-of-Atmosphere (BOA) reflectance considered the aerosol optical thickness and the water vapor content. Therefore, the Sentinel-2 L2A products are expected to enhance the reliability of image quality for overall coverage in the Sentinel-2 mission with enhanced spatial,spectral, and temporal resolution. The purpose of this work is a quantitative comparison Sentinel-2 L2A products and fully simulated image to evaluate the applicability of the Sentinel-2 dataset in cultivated land growing various kinds of crops in Korea. Reference image of Sentinel-2 L2A data was simulated by airborne hyperspectral data acquired from AISA Fenix sensor. The simulation imagery was compared with the reflectance of L1C TOA and that of L2A BOA data. The result of quantitative comparison shows that, for the atmospherically corrected L2A reflectance, the decrease in RMSE and the increase in correlation coefficient were found at the visible band and vegetation indices to be significant.