Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Maria Tompoulidou"'
Publikováno v:
Remote Sensing, Vol 16, Iss 5, p 916 (2024)
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 Senti
Externí odkaz:
https://doaj.org/article/a03a0ae8278449409e6555ff0e158603
Autor:
LEONIDAS VARDAKAS, NICHOLAS KOUTSIKOS, COSTAS PERDIKARIS, OLGA PETRIKI, DIMITRA BOBORI, STAMATIS ZOGARIS, SOFIA GIAKOUMI, ELENI FITOKA, MARIA TOMPOULIDOU, VASILIKI TSIAOUSSI, DIMITRIS KOMMATAS, EVANGELOS KONSTANTINIDIS, ALCIBIADES N. ECONOMOU
Publikováno v:
Mediterranean Marine Science; Τόμ. 23 Αρ. 1 (2022); 223-265
Mediterranean Marine Science; Vol. 23 No. 1 (2022); 223-265
Mediterranean Marine Science; Vol. 23 No. 1 (2022); 223-265
This study provides an annotated checklist of the freshwater fish species recorded in lentic ecosystems of Greece. Species distributional data were derived from an extensive review of published and unpublished sources and were evaluated for their con
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 16:1536-1539
The wetlands are often coupled with anthropogenic systems. This makes them highly dynamic, and thus difficult to map and monitor from space. The Sentinel-1 constellation allows monitoring land changes regardless of cloud conditions and with a high fr
Transitional ecosystems along the Aegean coastline are formed at the interface between land and sea, connecting the terrestrial and marine environment. They are grouped in four major types: coastal marshes, coastal lagoons, river mouths/estuaries, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f1f4a17cb84703a739c3fadbf3ad811
https://doi.org/10.1007/698_2020_668
https://doi.org/10.1007/698_2020_668
Autor:
Rene Höfer, Antonis Apostolakis, Maria Tompoulidou, Charalampos Ververis, Eleni Fitoka, Kathrin Weise, Lena Hatziiordanou
Publikováno v:
Remote Sensing of Environment. 245:111795
Mapping and assessment of water-related ecosystems is a challenging task that requires advanced processing techniques with clear rules and standards in terminology and definition of class features. These ecosystems are hydrologically and ecologically
Publikováno v:
Geocarto International. 31:342-354
In recent decades, there is an increasing need for harmonised and accurate information on the status and extent of forests. However, delineating the extent of forest areas is a complex task, since the existence of more than 100 definitions of forest
Autor:
Maria Tompoulidou, Dimitris G. Stavrakoudis, Eleni Dragozi, Thomas Katagis, L. Stepanidou, Ioannis Z. Gitas, D. Grigoriadis, Alexandra Stefanidou
Publikováno v:
Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017).
Autor:
Alexandra Stefanidou, Ioannis Z. Gitas, Dionysios Grigoriadis, Dimitris G. Stavrakoudis, Eleni Dragozi, Maria Tompoulidou
Publikováno v:
Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016).
Efficient forest fire management is a key element for alleviating the catastrophic impacts of wildfires. Overall, the effective response to fire events necessitates adequate planning and preparedness before the start of the fire season, as well as qu
Publikováno v:
Fourth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2016).
Climate change and overall temperature increase results in changes in forest cover in high elevations. Due to the long life cycle of trees, these changes are very gradual and can be observed over long periods of time. In order to use remote sensing i
Autor:
Ioannis Z. Gitas, Alexandra Stefanidou, Eleni Dragozi, D. Grigoriadis, Maria Tompoulidou, Dimitris G. Stavrakoudis
Publikováno v:
GEOBIA 2016: Solutions and synergies.
A key issue in modern fire management planning is the accurate fuel type mapping, required at many different spatial and temporal scales. Fuel type classification is critical for improving fire prevention schemes, developing accurate fire dispersion