Publications

Fang, C; Song, KS; Shang, YX; Ma, JH; Wen, ZD; Du, J (2019). Remote Sensing of Harmful Algal Blooms Variability for Lake Hulun Using Adjusted FM (AFAI) Algorithm. JOURNAL OF ENVIRONMENTAL INFORMATICS, 34(2), 108-122.

Abstract
Harmful algal blooms (HABs) have become a global issue due to their serious threat to environmental ecology and rapid expansion around the world. Northeast China, characterized by a long ice period, has been ignored in the previous studies of HABs. However, Lake Hulun, a great lake located in Northeast China, has been found intense HABs since the 1980s. To evaluate HABs more precisely and efficiently through satellite images in Lake Hulun, an adjusted FAI (AFAI) method with an automatically identified threshold was developed. The method took full advantage of Landsat series sensors and MODIS products, and built a threshold selection range (0.01 similar to 0.02 for Landsat and 0.05 similar to 0.12 for MODIS) rather than a single threshold on all images. With the long-term satellite data from year 1983 to 2016, occurrences of HABs in Lake Hulun were investigated. There were total 169 occurrences of HABs during the periods and the first outbreak was detected in 1984. Though the initial outbreak date of HABs varied in each year, most HABs happened in July and August. The water quality of Lake Hulun have experienced a serious degradation especially in the past nine years as the outbreak frequency of HABs increased a lot since 2009. The reason of the degradation may be attributed to the continuous grazing around the lake, tourism, and anthropogenic activities on lake surface even in freezing period. Surrounding land use and land cover (LUCC), meteorological conditions, and water chemical and physical parameters were also related with the outbreak of HABs to some extent.

DOI:
10.3808/jei.201700385

ISSN:
1726-2135