The aim of this study knows to occurrence characteristics and monthly transition of foreign marine debris by changing in the marine environment for the national marine debris monitoring areas in the west coastal area. The Jeju Island (5,112) had the highest number for foreign marine debris flowed in the coast. Many areas in the next were surveyed by Hajo Island (1,967), Imja Island (507). Plastic bottles were the most common type to 2,925 piece of the whole collection. Then, the monthly occurrence amount was concentrated in July, September. At this time, analysis results of the marine environment are as follows: The sea surface wind of southerly or southeasterly were predominated. In addition, the sea surface circulations were dominated by inflow of seawater southward along the China Coast and northward from the East China Sea.
Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, NDVI UAV and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And NDVI UAV in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to NDVI UAV and other meteorological factors were well reflected in the model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.