In this research, we focus on vessel detection using the satellite imagery of day/night band (DNB) on Suomi NPP in order to monitor the change of vessel activity on the region of South China Sea. In this paper, we consider the relation between the temporal change of vessel activities and the events on maritime environment based on the vessel traffic density estimation using DNB. DNB is a moderate resolution (350-700m) satellite imagery but can detect the fishing light of fishery boats in night time for every day. The advantage of DNB is the continuous monitoring on wide area compared to another vessel detection and locating system. However, DNB gave strong influence of cloud and lunar refection. Therefore, we additionally used Brightness Temperature at 3.7μm(BT3.7) for cloud information. In our previous research, we construct an empirical vessel detection model that based on the DNB contrast and the estimation of cloud condition using BT3.7. Moreover, we proposed a vessel traffic density estimation method based on empirical model. In this paper, we construct the time temporal density estimation map on South China Sea and East China Sea in order to extract the knowledge from vessel activities change.
The detection limit of DNB was proposed as a function of the brightness temperature (BT) at 3.7 μm, where the transmittance of cloud could be observed as a change of surface temperature. The shortwave infrared band exhibited a wide distribution in BT more than the thermal infrared band for the same level of DNB radiance. The lights from surface were identified even under the full Moon condition with the proposed method, where clouds were reflecting the lunar lights. A different distribution of clouds for day to day and a change of the Moon phase with its elevation make this problem more complicated. But the approach of contrast based evaluation of surface lights and lunar reflected lights could be one solution to distinguish the lights from the surface. Currently, a validation is necessary in the future to confirm this algorithm and to validate the detected pixels to be fishing boats with the stable light sources. The time series data of fishing boats could be studied to analyze the region of fishing area relative to the distribution of sea surface temperature and/or chlorophyll-a.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.