Operational algae bloom detection in the Baltic Sea using GIS and AVHRR data

Abstract

During the blooming season, algal colonies can, in extreme cases, cover up to 200 000 square kilometres of the Baltic Sea water surface. Because the position and shape of the blooms may significantly change in a very short time due to the influence of wind and waves, regular monitoring of the blooms' development is necessary. Currently, the desired monitoring frequency may only be achieved by means of remote sensing. The article presents a novel method of AVHRR data processing for the purpose of detection of algal blooms in the Baltic Sea. Instead of analysing the value of spectral reflectance of the algae, the algorithm analyses the frequency distribution of normalized difference in reflectance between the visible and near-infrared spectral bands. The proposed method has been implemented and tested as part of an operational Geographic Information System.

Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

“…In computer science, physical phenomena of various nature are commonly integrated, processed and analysed with the use of Geographic Information Systems [24,25]. Although data integration and analysis has thus far been constrained to GIS running on Desktop or Server-class computer systems, the recent advancements in both cross-platform GIS libraries and mobile computing device performance has enabled the construction of an innovative solution which integrates data collection, processing and analysis on a single low-power mobile device.…”

Modeling Dinophysis in Western Andalucía using an autoregressive hidden Markov model

“…Artificial neural networks have been applied to the coast of Huelva in Andalucía ( Velo-Suárez and Estrada 2007 ); however, that modeling effort used the last 5 weekly D. acuminata concentrations as the only input variables to predict the upcoming week’s concentration. Kulawiak (2016) used GIS and advanced very-high-resolution radiometer data to detect algae blooms in the Baltic sea, but this did not leverage toxin measurements. To our knowledge, it has been an unaddressed modeling challenge to account for the fact that DST can persist in water for extended periods of time, while also giving interpretable model parameters.…”