Ulva prolifera monitoring by GF-1 wide field-of-view sensor data

Abstract

Ulva prolifera, a kind of green macroalgae, is nontoxic itself, however, its bloom has bad effects on the marine environment, coastal scene, water sports and seashore tourism. Monitoring of the Ulva prolifera by remote sensing technology has the advantages of wide coverage, rapidness, low cost and dynamic monitoring over a long period of time. The GF-1 satellite was launched in April 2013, which provides a new suitable remote sensing data source for monitoring the Ulva prolifera. At present, segmenting image with a threshold is the most widely used method in Ulva prolifera extraction by remote sensing data, because it is simple and easy to operate. However, the threshold value is obtained through visual analysis or using a fixed statistical value, and could not be got automatically. Facing this problem, we proposed a new method, which can obtain the segmentation threshold automatically based on the local maximum gradient value. This method adopted the average NDVI value of local maximum gradient points as the threshold, and could get an appropriate segmentation threshold automatically for each image. The preliminary results showed that this method works well in monitoring Ulva prolifera by GF-1 WFV data.