title: Improvement of remote monitoring on water quality in a subtropical reservoir by incorporating grammatical evolution with parallel genetic algorithms into satellite imagery.
abstract: Parallel GEGA was constructed by incorporating grammatical evolution (GE) into the parallel genetic algorithm (GA) to improve reservoir water quality monitoring based on remote sensing images. A cruise was conducted to ground-truth chlorophyll-a (Chl-a) concentration longitudinally along the Feitsui Reservoir, the primary water supply for Taipei City in Taiwan. Empirical functions with multiple spectral parameters from the Landsat 7 Enhanced Thematic Mapper (ETM+) data were constructed. The GE, an evolutionary automatic programming type system, automatically discovers complex nonlinear mathematical relationships among observed Chl-a concentrations and remote-sensed imageries. A GA was used afterward with GE to optimize the appropriate function type. Various parallel subpopulations were processed to enhance search efficiency during the optimization procedure with GA. Compared with a traditional linear multiple regression (LMR), the performance of parallel GEGA was found to be better than that of the traditional LMR model with lower estimating errors.
authors: Department of Civil Engineering and Engineering Informatics, Chung Hua University, Hsinchu, Taiwan 30067, ROC. lichen@chu.edu.tw
authors: Li
authors: L
authors: Chen
authors: Chih-Hung
authors: CH
authors: Tan
authors: Shuh-Ji
authors: SJ
authors: Kao
authors: Tai-Sheng
authors: TS
authors: Wang
mesh_terms: D000465:Algorithms; D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D004784:Environmental Monitoring / Q000379:methods*; D015233:Models, Statistical; D017215:Satellite Communications; D013624:Taiwan; D014329:Tropical Climate; D014876:Water Pollution / Q000032:analysis*; D014881:Water Supply / Q000032:analysis
chemical_list: D002734:Chlorophyll; D000077194:Chlorophyll A