Περιλαμβάνονται, με χρονολογική σειρά, δημοσιεύσεις στις οποίες έχουν χρησιμοποιηθεί δεδομένα από το εθνικό δίκτυο παρακολούθησης λιμνών.
Δημοσιεύσεις σε επιστημονικά περιοδικά
Markogianni, Vassiliki; Kalivas, Dionissios P.; Petropoulos, George P.; Giovos, Rigas; Dimitriou, Elias
Comparative Analysis of Trophic Status Assessment Using Different Sensors and Atmospheric Correction Methods in Greece’s WFD Lake Network Δημοσίευση σε επιστημονικό περιοδικό
In: Remote Sensing, vol. 17, iss. 11, no. 1822, 2025, ISSN: 2072-4292.
Περίληψη | Σύνδεσμοι | BibTeX | Ετικέτες: atmospheric correction (AC), Carlson’s Trophic State Index (TSI), GEE-platform, lake water quality, Landsat, Sentinel-2 imagery, WFD
@article{rs17111822,
title = {Comparative Analysis of Trophic Status Assessment Using Different Sensors and Atmospheric Correction Methods in Greece’s WFD Lake Network},
author = {Vassiliki Markogianni and Dionissios P. Kalivas and George P. Petropoulos and Rigas Giovos and Elias Dimitriou },
doi = {10.3390/rs17111822},
issn = {2072-4292},
year = {2025},
date = {2025-05-23},
urldate = {2025-05-23},
journal = {Remote Sensing},
volume = {17},
number = {1822},
issue = {11},
abstract = {Today, open-source Cloud Computing platforms are valuable for geospatial image analysis while the combination of the Google Earth Engine (GEE) platform and new satellite launches greatly facilitate the monitoring of national-scale lake Water Quality (WQ). The main aim of this research is to assess the transferability and performance of published general, natural-only and artificial-only lake WQ models (Chl-a, Secchi Disk Depth-SDD- and Total Phosphorus-TP) across Greece’s WFD (Water Framework Directive) lake sampling network. We utilized Landsat (7 ETM +/8 OLI) and Sentinel 2 surface reflectance (SR) data embedded in GEE, while subjected to different atmospheric correction (AC) methods. Subsequently, Carlson’s Trophic State Index (TSI) was calculated based on both in situ and modelled WQ values. Initially, WQ models employed both DOS1-corrected (Dark Object Subtraction 1; manually applied) and GEE-retrieved respective SR data from the year 2018. Double WQ values per lake station were inserted in a linear regression analysis to harmonize the AC differences, separately for Landsat and Sentinel 2 data. Yielded linear equations were accompanied by strong associations (R2 ranging from 0.68 to 0.98) while modelled and GEE-modelled TSI values were further validated based on reference in situ WQ datasets from the years 2019 and 2020. The values of the basic statistical error metrics indicated firstly the increased assessment’s accuracy of GEE-modelled over modelled TSIs and then the superiority of Landsat over Sentinel 2 data. In this way, the hereby adopted methodology was evolved into an efficient lake management tool by providing managers the means for integrated sustainable water resources management while contributing to saving valuable image pre-processing time.},
keywords = {atmospheric correction (AC), Carlson’s Trophic State Index (TSI), GEE-platform, lake water quality, Landsat, Sentinel-2 imagery, WFD},
pubstate = {published},
tppubtype = {article}
}
Today, open-source Cloud Computing platforms are valuable for geospatial image analysis while the combination of the Google Earth Engine (GEE) platform and new satellite launches greatly facilitate the monitoring of national-scale lake Water Quality (WQ). The main aim of this research is to assess the transferability and performance of published general, natural-only and artificial-only lake WQ models (Chl-a, Secchi Disk Depth-SDD- and Total Phosphorus-TP) across Greece’s WFD (Water Framework Directive) lake sampling network. We utilized Landsat (7 ETM +/8 OLI) and Sentinel 2 surface reflectance (SR) data embedded in GEE, while subjected to different atmospheric correction (AC) methods. Subsequently, Carlson’s Trophic State Index (TSI) was calculated based on both in situ and modelled WQ values. Initially, WQ models employed both DOS1-corrected (Dark Object Subtraction 1; manually applied) and GEE-retrieved respective SR data from the year 2018. Double WQ values per lake station were inserted in a linear regression analysis to harmonize the AC differences, separately for Landsat and Sentinel 2 data. Yielded linear equations were accompanied by strong associations (R2 ranging from 0.68 to 0.98) while modelled and GEE-modelled TSI values were further validated based on reference in situ WQ datasets from the years 2019 and 2020. The values of the basic statistical error metrics indicated firstly the increased assessment’s accuracy of GEE-modelled over modelled TSIs and then the superiority of Landsat over Sentinel 2 data. In this way, the hereby adopted methodology was evolved into an efficient lake management tool by providing managers the means for integrated sustainable water resources management while contributing to saving valuable image pre-processing time.
Tompoulidou, Maria; Karadimou, Elpida; Apostolakis, Antonis; Tsiaoussi, Vasiliki
A Geographic Object-Based Image Approach Based on the Sentinel-2 Multispectral Instrument for Lake Aquatic Vegetation Mapping: A Complementary Tool to In Situ Monitoring Δημοσίευση σε επιστημονικό περιοδικό
In: Remote Sensing, vol. 16, no. 5, 2024, ISSN: 2072-4292.
Περίληψη | Σύνδεσμοι | BibTeX | Ετικέτες: aquatic vegetation, General Earth and Planetary Sciences, GEOBIA, lake monitoring, Mediterranean lakes, remote sensing, Sentinel-2 imagery, WFD
@article{Tompoulidou2024,
title = {A Geographic Object-Based Image Approach Based on the Sentinel-2 Multispectral Instrument for Lake Aquatic Vegetation Mapping: A Complementary Tool to In Situ Monitoring},
author = {Maria Tompoulidou and Elpida Karadimou and Antonis Apostolakis and Vasiliki Tsiaoussi},
doi = {10.3390/rs16050916},
issn = {2072-4292},
year = {2024},
date = {2024-03-05},
urldate = {2024-03-05},
journal = {Remote Sensing},
volume = {16},
number = {5},
publisher = {MDPI AG},
abstract = {Aquatic vegetation is an essential component of lake ecosystems, used as a biological indicator for in situ monitoring within the Water Framework Directive. We developed a hierarchical object-based image classification model with multi-seasonal Sentinel-2 imagery and suitable spectral indices in order to map the aquatic vegetation in a Mediterranean oligotrophic/mesotrophic deep lake; we then applied the model to another lake with similar abiotic and biotic characteristics. Field data from a survey of aquatic macrophytes, undertaken on the same dates as EO data, were used within the accuracy assessment. The aquatic vegetation was discerned into three classes: emergent, floating, and submerged aquatic vegetation. Geographic object-based image analysis (GEOBIA) proved to be effective in discriminating the three classes in both study areas. Results showed high effectiveness of the classification model in terms of overall accuracy, particularly for the emergent and floating classes. In the case of submerged aquatic vegetation, challenges in their classification prompted us to establish specific criteria for their accurate detection. Overall results showed that GEOBIA based on spectral indices was suitable for mapping aquatic vegetation in oligotrophic/mesotrophic deep lakes. EO data can contribute to large-scale coverage and high-frequency monitoring requirements, being a complementary tool to in situ monitoring.},
keywords = {aquatic vegetation, General Earth and Planetary Sciences, GEOBIA, lake monitoring, Mediterranean lakes, remote sensing, Sentinel-2 imagery, WFD},
pubstate = {published},
tppubtype = {article}
}
Aquatic vegetation is an essential component of lake ecosystems, used as a biological indicator for in situ monitoring within the Water Framework Directive. We developed a hierarchical object-based image classification model with multi-seasonal Sentinel-2 imagery and suitable spectral indices in order to map the aquatic vegetation in a Mediterranean oligotrophic/mesotrophic deep lake; we then applied the model to another lake with similar abiotic and biotic characteristics. Field data from a survey of aquatic macrophytes, undertaken on the same dates as EO data, were used within the accuracy assessment. The aquatic vegetation was discerned into three classes: emergent, floating, and submerged aquatic vegetation. Geographic object-based image analysis (GEOBIA) proved to be effective in discriminating the three classes in both study areas. Results showed high effectiveness of the classification model in terms of overall accuracy, particularly for the emergent and floating classes. In the case of submerged aquatic vegetation, challenges in their classification prompted us to establish specific criteria for their accurate detection. Overall results showed that GEOBIA based on spectral indices was suitable for mapping aquatic vegetation in oligotrophic/mesotrophic deep lakes. EO data can contribute to large-scale coverage and high-frequency monitoring requirements, being a complementary tool to in situ monitoring.
Προφορικές παρουσιάσεις σε συνέδρια
Mavromati, Efpraxia; Kagalou, Ifigenia; Kemitzoglou, Dimitra; Apostolakis, Antonis; Tsiaoussi, Vasiliki
Linkages between physicochemical status and hydromorphology in Greek lakes under WFD policy Προφορική παρουσίαση σε συνέδριο
European Water 58, 01.09.2017.
Περίληψη | Σύνδεσμοι | BibTeX | Ετικέτες: Hydromorphology, Water Quality, WFD, Λίμνες
@misc{Mavromati2017,
title = {Linkages between physicochemical status and hydromorphology in Greek lakes under WFD policy},
author = {Efpraxia Mavromati and Ifigenia Kagalou and Dimitra Kemitzoglou and Antonis Apostolakis and Vasiliki Tsiaoussi},
url = {https://www.ewra.net/ew/pdf/EW_2017_58_41.pdf},
year = {2017},
date = {2017-09-01},
urldate = {2017-09-01},
pages = {273-279},
abstract = {The national monitoring network of waters in Greece, in the context of Water Framework Directive, has been operational since 2012. It comprises 50 lake water bodies, both natural and artificial (24 and 26 respectively). The aims of the study are i) to present the main features of Greek lakes; ii) to position them according to hydromorphological and physicochemical data from the first period of monitoring and iii) to investigate how the hydromorphological features influence water quality. Greek lakes are discerned in relation to hydromorphological aspects such as mean depth, volume, surface area, catchment area. Impacted and unimpacted lakes are separated when positioned along physical and chemical attributes, such as Secchi depth, TP and ion concentrations. The dataset covers a gradient of eutrophication, which seems to be the main anthropogenic pressure on lakes in Greece and probably one of the most widespread anthropogenic pressures on lakes across Europe. Catchment areas of the Greek lakes have undergone substantial agricultural, industrial, and urban development over recent years, leading to eutrophication and hydromorphological alterations. Management measures at a catchment scale aiming to control land uses would be needed in order to maintain and/or improve water quality in Greek lakes, supplemented by site-specific measures when appropriate. The monitoring network provides baseline data that will allow the assessment of status and trends of Greek lakes.},
howpublished = {European Water 58},
keywords = {Hydromorphology, Water Quality, WFD, Λίμνες},
pubstate = {published},
tppubtype = {presentation}
}
The national monitoring network of waters in Greece, in the context of Water Framework Directive, has been operational since 2012. It comprises 50 lake water bodies, both natural and artificial (24 and 26 respectively). The aims of the study are i) to present the main features of Greek lakes; ii) to position them according to hydromorphological and physicochemical data from the first period of monitoring and iii) to investigate how the hydromorphological features influence water quality. Greek lakes are discerned in relation to hydromorphological aspects such as mean depth, volume, surface area, catchment area. Impacted and unimpacted lakes are separated when positioned along physical and chemical attributes, such as Secchi depth, TP and ion concentrations. The dataset covers a gradient of eutrophication, which seems to be the main anthropogenic pressure on lakes in Greece and probably one of the most widespread anthropogenic pressures on lakes across Europe. Catchment areas of the Greek lakes have undergone substantial agricultural, industrial, and urban development over recent years, leading to eutrophication and hydromorphological alterations. Management measures at a catchment scale aiming to control land uses would be needed in order to maintain and/or improve water quality in Greek lakes, supplemented by site-specific measures when appropriate. The monitoring network provides baseline data that will allow the assessment of status and trends of Greek lakes.