조류는 수생태계에서 소비자의 에너지를 공급하여 생태계 내 없어서는 안 될 1차 생산자로서 크게 녹조류, 남조류, 규조류로 나뉘어진다. 남조류의 경우 수온이 상승하여 여름철 발생하여 과대 증식하여 녹조현상의 주원인이 되며, 최근 기후 변화로 인해 녹조현상의 발생시기의 변화와 빈도수가 늘고 있는 추세이다. 기존의 조류 조사 방식은 채수 및 센서를 통한 측정으로 이루어지고 있으며 시간, 비용 및 인력의 한계가 나타난다. 이러한 기존 모니터링 방법의 한계를 극복 하기위해 위성영상이나 무인항공기(Unmanned Aearial Vehicles, UAV), 등 탑제체를 운용한 다중분광 및 초분광과 같은 분광기기를 이용하여 원격 모니터링을 수행하는 연구가 진행되어 왔다. 본 연구에서는 조류 배양액 및 하천수 채수를 통한 실험실 규모의 실험을 통해 원격 모니터링의 종 구분에 대한 가능성에 대하여 확인 해보고자 하였다. 초분광 영상을 취득하기 위해 400-1000 nm에서 분석할 수 있는 초분광 센서를 활용하였다. 채수한 하천수의 조류 종 구분을 위한 분광특성을 추출하기 위해 GF/C필터를 이용하여 여과를 진행하여 시료를 제조하여 영상을 수집하였다. 수집된 영상을 방사보정 및 Base (하천수 및 배양보존액 통칭) 제거를 진행하였고 조류의 분광 정보 추출 과정을 통해 시료별 분광 정보를 추출, 분석하여 조류의 분광특성을 파악, 비교분석하여 하천·호소에서의 초분광영상 기반 원격탐사 모니터링의 적용성을 검토하고자 하였다.
조류는 수생태계에서 소비자의 에너지를 공급하여 생태계 내 없어서는 안 될 1차 생산자로서 크게 녹조류, 남조류, 규조류로 나뉘어진다. 남조류의 경우 수온이 상승하여 여름철 발생하여 과대 증식하여 녹조현상의 주원인이 되며, 최근 기후 변화로 인해 녹조현상의 발생시기의 변화와 빈도수가 늘고 있는 추세이다. 기존의 조류 조사 방식은 채수 및 센서를 통한 측정으로 이루어지고 있으며 시간, 비용 및 인력의 한계가 나타난다. 이러한 기존 모니터링 방법의 한계를 극복 하기위해 위성영상이나 무인항공기(Unmanned Aearial Vehicles, UAV), 등 탑제체를 운용한 다중분광 및 초분광과 같은 분광기기를 이용하여 원격 모니터링을 수행하는 연구가 진행되어 왔다. 본 연구에서는 조류 배양액 및 하천수 채수를 통한 실험실 규모의 실험을 통해 원격 모니터링의 종 구분에 대한 가능성에 대하여 확인 해보고자 하였다. 초분광 영상을 취득하기 위해 400-1000 nm에서 분석할 수 있는 초분광 센서를 활용하였다. 채수한 하천수의 조류 종 구분을 위한 분광특성을 추출하기 위해 GF/C필터를 이용하여 여과를 진행하여 시료를 제조하여 영상을 수집하였다. 수집된 영상을 방사보정 및 Base (하천수 및 배양보존액 통칭) 제거를 진행하였고 조류의 분광 정보 추출 과정을 통해 시료별 분광 정보를 추출, 분석하여 조류의 분광특성을 파악, 비교분석하여 하천·호소에서의 초분광영상 기반 원격탐사 모니터링의 적용성을 검토하고자 하였다.
Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which...
Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.
Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.
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