Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces

Harmful algal blooms (HABs) cause multiple problems all around the world. Algal blooms are known to cause toxicity in the water, fish kills and biomass destruction. This leads to losses in the fishing industry, tourism and the natural environment. Early detection and monitoring of HAB behavior is ne...

Full description

Saved in:
Bibliographic Details
Main Authors: Desingco, John Darill B., Ngo, Arron Spencer K.
Format: text
Language:English
Published: Animo Repository 2015
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/5542
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-6053
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-60532021-11-03T08:25:08Z Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces Desingco, John Darill B. Ngo, Arron Spencer K. Harmful algal blooms (HABs) cause multiple problems all around the world. Algal blooms are known to cause toxicity in the water, fish kills and biomass destruction. This leads to losses in the fishing industry, tourism and the natural environment. Early detection and monitoring of HAB behavior is necessary to assess its impact on its surroundings. In recent years, remote sensing using satellite imagery and complex sensors has become popular for algae monitoring. Implementation of a smaller scale remote sensing system allows observation of less prominent bodies of water and allow flexibility in terms of the time and duration of data collection. The system is designed to mimic the functionality of satellite remote sensing systems for algae detection but using only a normal camera. The system is intended to model the correlation of concentration levels of algae with the visual features of water surfaces using regression analysis. However, visual color analysis does introduce other variables that may interfere with the visual analysis such as uneven illumination and varying lighting conditions. A methodology is proposed to determine the concentration levels by correcting for the weaknesses introduced by visual color analysis and creating a predictive model for future reference. Due to the scarcity of data, stemming from unexpected circumstances, data had to be simulated using floral foam particles as a substance with similar properties as algae particles. The system shows an average of 20% error in prediction for the simulated data. The results indicate that the information in a single and most significant color component was found to be insufficient for determining concentration levels at higher values. This can be seen as either the limitation of single variable analysis on color information for this application or that the samples reached maximum saturation since the value at which each model's accuracy drops is consistent. Color correction of the image sets produced models with increased consistency and inc 2015-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/5542 Bachelor's Theses English Animo Repository Algal blooms—Monitoring--Remote sensing Remote sensing Computer Sciences
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Algal blooms—Monitoring--Remote sensing
Remote sensing
Computer Sciences
spellingShingle Algal blooms—Monitoring--Remote sensing
Remote sensing
Computer Sciences
Desingco, John Darill B.
Ngo, Arron Spencer K.
Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
description Harmful algal blooms (HABs) cause multiple problems all around the world. Algal blooms are known to cause toxicity in the water, fish kills and biomass destruction. This leads to losses in the fishing industry, tourism and the natural environment. Early detection and monitoring of HAB behavior is necessary to assess its impact on its surroundings. In recent years, remote sensing using satellite imagery and complex sensors has become popular for algae monitoring. Implementation of a smaller scale remote sensing system allows observation of less prominent bodies of water and allow flexibility in terms of the time and duration of data collection. The system is designed to mimic the functionality of satellite remote sensing systems for algae detection but using only a normal camera. The system is intended to model the correlation of concentration levels of algae with the visual features of water surfaces using regression analysis. However, visual color analysis does introduce other variables that may interfere with the visual analysis such as uneven illumination and varying lighting conditions. A methodology is proposed to determine the concentration levels by correcting for the weaknesses introduced by visual color analysis and creating a predictive model for future reference. Due to the scarcity of data, stemming from unexpected circumstances, data had to be simulated using floral foam particles as a substance with similar properties as algae particles. The system shows an average of 20% error in prediction for the simulated data. The results indicate that the information in a single and most significant color component was found to be insufficient for determining concentration levels at higher values. This can be seen as either the limitation of single variable analysis on color information for this application or that the samples reached maximum saturation since the value at which each model's accuracy drops is consistent. Color correction of the image sets produced models with increased consistency and inc
format text
author Desingco, John Darill B.
Ngo, Arron Spencer K.
author_facet Desingco, John Darill B.
Ngo, Arron Spencer K.
author_sort Desingco, John Darill B.
title Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
title_short Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
title_full Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
title_fullStr Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
title_full_unstemmed Extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
title_sort extraction and utilization of visual features for determining plankton concentration levels from aerial images of lake water surfaces
publisher Animo Repository
publishDate 2015
url https://animorepository.dlsu.edu.ph/etd_bachelors/5542
_version_ 1718382491000111104